Key Takeaways

1. Challenges like Reliability, complexity, scalability, data integrity, versioning, and many others can be solved by Azure. It simplifies the microservices application development process.
2. The serverless solution, Azure Functions, enables you to write less code and eventually it saves cost.
3. Azure manages the K8s (Kubernetes) API services. AKS (Azure Kubernetes Services) is a managed K8s cluster hosted on the Azure Cloud. So, agent nodes are the only thing you need to manage.
4. Azure also provides services like Azure DevOps Services, AKS, Azure Monitor, Azure API Management, etc. to automate build, test, and deployment tasks.

Nowadays, the usage of Microservices architectures is widely increasing and it is replacing the traditional monolithic application architecture. This approach is generally used by software development companies to develop large-scale applications with the use of public cloud infrastructure such as Azure. This infrastructure offers various services like Azure Functions, Azure Kubernetes Service (AKS), Azure Service Fabric, and many more. To know more about microservices, their implementation benefits, and how cloud infrastructure like Azure help businesses implement the microservices architecture, let’s go through this blog.

1. What are Microservices?

Microservices are known as one of the best-fit architectural styles for creating highly scalable, resilient, modern, large scale and independently deployable applications. There are various approaches available by which one can design and create microservices architecture. Microservice architecture can consist of autonomous and smaller services. And here each service is self-contained which means that it helps in implementing a single business capability within a defined bounded context. Here a bounded context means a natural division within a business that offers boundaries within each business domain.

Basically, microservices are easy to develop and maintain the developers as they are independent, small, and loosely coupled. Each service has its own separate codebase which can be easily maintained by a small development team. Besides this, when it is time to deploy services, it can be done independently. In addition to this, services are also responsible for persisting external or their own data which differs from the traditional method of app development.

Further Reading on: Microservices Best Practices
Microservices vs Monolithic Architecture

2. How can Azure be the Most Beneficial for Microservices Development and Deployment?

Here are some of the reasons that prove that Azure is very beneficial for the implementation of Microservices architectures –

2.1 Creates and Deploys Microservices with Agility

Microsoft Azure enables effortless management of newly released features, bug fixes, and other updates in individual components without forcing them to redeploy the entire application. This means that it enables continuous integration/continuous deployment (CI/CD) with the help of automated software delivery workflow.

2.2 Makes Applications Resilient

Azure microservices help replace an individual service or retire the services without affecting the entire software application. The reason behind this is that microservices platforms enable developers to use patterns like circuit breaking to handle the failure of individual services, their reliability, and security, unlike the traditional monolithic model. 

Build resilient, highly-scalable, independently deployable, and easily-evolved applications with #Azure microservices. A successful microservices architecture requires a different approach to designing and building applications. Read more here:https://t.co/pjCFEDnYvq pic.twitter.com/D6k2dkNiN7

— Azure Support (@AzureSupport) October 26, 2020

2.3 Microservices Scale with Demand

Microservices on Azure enables the developers to scale individual services based on the requirement of the resources without scaling out the entire application. For this, the developers have to gather the higher density of services into an individual host with the use of a container orchestrator such as Azure Red Hat OpenShift or Azure Kubernetes Service (AKS).

2.4 Finds the Best Approach for the Team

Another benefit of Azure Microservices is that it enables dedicated software development teams to select their preferred language, deployment approach, microservices platform, and programming model for each microservice. Besides, Azure API management enables the developers to publish microservice APIs for both external and internal consumption while maintaining crosscutting concerns like caching, monitoring, authentication, throttling, and authorization.

3. Building Microservices Architecture on Azure

Here are some steps that will help developers to create microservices architecture on Azure –

Step 1: Domain Analysis

When it comes to microservices, developers generally face issues related to defining the boundaries of each service in the system. And doing so becomes a priority according to the rule which states that each microservices should have a single responsibility. Therefore, by following this rule and putting it into consideration, microservices should be designed only after  understanding  the client’s business domain, requirements, and goals. If this is not the case, the design of the microservice will be haphazard with undesirable characteristics like tight coupling, hidden dependencies, and poorly designed interfaces. Therefore, it is necessary to design the microservices properly and for that analyzing the domain is the best first step. 

In addition to this, Domain-Driven Design (DDD) approach is used as it offers a framework that can help developers create a well-designed service. This approach comes in two different phases: strategic and tactical. In this method, strategic DDD ensures that the service architecture is created in such a way that it focuses on the business capabilities, while tactical DDD offers a set of design patterns for services. To apply Domain-Driven Design, there are some steps that the developers need to follow and they are – 

• The very first step is to analyze the business domain in order to get a proper understanding of the application’s functional requirements. Once this step is performed, as a result, the software engineers will get an informal description of the domain which can be reframed and converted into a formal set of service domain models.
• The next step is to define the domain’s bounded contexts. Here, each bounded context holds one domain model that represents a subdomain of an app. 
• After this, tactical DDD patterns must be applied within the bounded context, so that they can be helpful in defining patterns, aggregations, and domain services.
• The last step is to use the outcome from the previously performed step to identify the app’s microservices.

This shows that the use of the DDD approach enables the developers to design every microservice within a particular boundary and also helps in avoiding the trap that creates boundaries for business organizations or enables them to choose the designs. It enables the development team to keep a close observation of code creation. 

Step 2: Identify Boundaries and Define the Microservices

After setting the bounded contexts for the application and analyzing the domain model in the first step, now is the time to jump from the domain model to the application model. And for this, there are some steps that are required to be followed in order to derive services from the domain model. The below-listed steps help the development team to identify the microservices from the domain model. 

• To start with this process, first, one needs to check the functionalities required in the service and must confirm that it doesn’t span more than one bounded context. And as per the definition, the bounded context marks any particular domain model’s boundary. This basically talks about whether the software development teams want to find out that the microservices used in the system are able to mix different domain models or not. If yes, then domain analysis must be refined in order to make the microservices carry on their tasks easily.
• After that, the team needs to look at the domain’s aggregates. Generally, aggregates are known as good applicants for services and when they are well-defined, they have different characteristics –
  1. High functional cohesion
  2. Derived from business requirements and not technical concerns
  3. Loosely coupled
  4. Boundary of persistence
• Then the team needs to check domain services. These services are stateless operations that are carried out across various aggregates.
• The last step is to consider non-functional requirements. Here, one needs to check factors like data types, team size, technologies, requirements, scalability, and more. The reason behind checking these factors is that they lead to the further decomposition of microservices into smaller versions.

After checking and identifying the microservices, the next thing to do is validate the design of microservices against some criteria to set boundaries. For that, check out the below aspects – 

• Every service must have a single responsibility.
• There should not be any chatty calls between the microservices.
• In lock-step, no inter-dependencies require the deployment of two or more services.
• Small independent teams can create a service as it is small and simple.
  1. Services can evolve independently as they are not tightly coupled.

Step 3: Approaches to Build Microservices

The next step is to use any of the two widely used approaches to create microservices. Let’s go through both these approaches.

Service Orchestrators

Service orchestrator is an approach that helps in handling tasks that are related to managing and deploying a set of services. These tasks include: 

• Health monitoring of the services 
• Placing services on nodes 
• Load balancing 
• Restarting unhealthy services 
• Service discovery 
• Applying configuration updates
• Scaling the number of service instances. 

Some of the most popular orchestrators that one can use are Docker Swarm, Kubernetes, DC/OS, and Azure Service Fabric.

When the developer is working on the Microsoft Azure platform for microservices, consider the following options: 

Serverless

Serverless architecture is a concept that makes it easier for the developers to deploy code and host service that can handle putting and executing that code onto a VM. Basically, it is an approach that helps coordinated functions of the application to handle the events with the use of event-based triggers. For instance, when a message is placed in a queue the function that reads from the queue and carries out the messages might get triggered.

In this case, Azure Functions are serverless compute services and enable support to various function triggers such as Event Hubs Events, HTTP request, and  Service Bus queues.

Orchestrator or Serverless?

Some of the factors that give a clear idea of the differences between an orchestrator approach and a serverless approach are –

Step 4: Establish Communication between Microservices

When it comes to building stateful services or other microservices applications architecture, communication plays an important role. The reason behind it is that the communication between microservices must be robust and efficient in order to make the microservices application run smoothly. And in such types of applications, unlike traditional monolithic applications, various small and granular services interact to complete a single business activity, and it can be challenging. A few of these challenges are – resiliency, load balancing, service versioning, distributed applications tracing, and more. To know more about these challenges and possible solutions, Let’s go  through the following table –

But with the right use of Azure and Azure SQL databases, strong communication can be established without any issue. And for this, there are two basic messaging patterns with microservices that can be used. 

• Asynchronous communication: In this type of pattern, a microservice sends a message without getting any response. Here, more than one service processes messages asynchronously. 
• Synchronous Communication: Another type of pattern is synchronous communication where the service calls an API that another microservice exposes with the use of protocols like gRPC and HTTP. Also the caller service waits for the response of the receiver service to proceed further.  

Step 5: Design APIs for Microservices

 Designing good APIs for microservices is very important because all data exchange that happens between services is either through API calls or messages. Here, the APIs have to be efficient and effective to avoid the creation of chatty I/O. 

Besides this, as the microservices are designed by the teams that are working independently, the APIs created for them must consist of versioning and semantic schemes as these updates should not break any other service.

Here the two different types of APIs that are widely designed –

• Public APIs: A public API must be compatible with client apps which can be either the native mobile app or browser app. This means that the public APIs will mostly use REST over HTTP.
• Backend APIs: Another type of API designed for microservices is backend API which depends on network performance and completely depends on the granularity of the key services. Here interservice communication plays a vital role and it can also result in network traffic.

Here are some things to think about when choosing how to implement an API.

Step 6: Use API Gateways in Microservices

In microservices architecture, it generally happens that a client might interact more with the front-end service to know how a client identifies which endpoints to call or what might happen if existing services are re-engineered or new services are introduced. For all these things, an API gateway can be really helpful as it helps in addressing the defined challenges. An API gateway resides between the services and the clients which enables it to act like a reverse proxy for routing requests from the client side of the application to the services side. Here, it also performs many cross-cutting tasks like rate limiting, SSL termination, and authentication.

Basically, by using an API gateway in the microservices architectural approach, clients will have to send requests directly to front-end services if there is no deployment of a gateway. Here are some of the issues that might occur while exposing services directly to the application’s client-side –

• There can be complexity in the client code for which the client will have to keep a track of various endpoints and also resiliently handle failures.
• When a single operation is carried out, it might require various calls for multiple services and this can result in round trips of multiple networks between the server and the client. 
• Exposing services can create coupling between the front end (client-side) and the back end. And in this case, the client requires to have knowledge about the process of individual services being decomposed. This makes it difficult to handle the client and refactor services. 
• Services that have public endpoints are at the attack surface and require to be hardened. 
• Services must expose protocols like WebSocket or HTTP that are client-friendly and this limits the communication protocol choices. 

But with the right API gateway usage in services, the team can achieve business needs. The reason behind this is that a gateway can help in addressing these issues from services by decoupling the clients. Gateways have the capability to perform various functions and they can be grouped into the following design patterns – 

Some of the major examples of functionalities that can be offloaded by the development team to a gateway are – 

• Authentication
• SSL termination
• Client rate limiting (throttling)
• IP allow list or blocklist
• Response caching
• Logging and monitoring
• GZIP compression
• Web application firewall

For implementing an API gateway to the application, here are some major options – 

Step 7: Managing Data in Microservices Architecture

The next step is managing the data centers in service architecture. Here one can use the single responsibility principle.  This means that each service is responsible for its own data store which is private and cannot be accessed by other services. The main reason behind this rule is to avoid unintentional coupling in microservices as it can result in underlying data schemas. And when a change occurs to the data schema, it must be coordinated across each service that depends on that database.

Basically, if there is isolation between the service’s data store, the team can limit the scope of change and also safeguard the agility of independent deployments. Besides this, each microservice might have its own queries, patterns, and data models which cannot be shared if one wants to have an efficient service approach.

Now let’s go through some tools that are used to make data management in microservices architecture an easy task with Azure –

Step 8: Microservices Design Patterns

The last step in creating microservice architecture using Azure is design patterns that help in increasing the velocity of application releases and this can be done by decomposing the app into various small services which are autonomous & deployed independently. This process might come with some challenges but the design patterns defined here can help mitigate them –

• Anti-Corruption Layer: It can help in implementing a facade between legacy and new apps to ensure that the new design is not dependent on the limitations of legacy systems.
• Ambassador: It can help in offloading common client connectivity tasks like routing, monitoring, logging, and more.
• Bulkhead: It can isolate critical resources like CPU, memory, and connection pool for each service and this helps in increasing the resiliency of the system.
• Backends for Frontends: It helps in creating separate backend services for various clients like mobile or desktop.
• Gateway Offloading: It helps each microservice to offload the service functionalities that are shared.
• Gateway Aggregation: It aggregates single service requests to various individual microservices so that chattiness can be reduced.
• Gateway Routing: It helps in routing requests to various microservices with the use of a single endpoint.
• Strangler Fig: It enables incremental refactoring by slowly replacing the functionalities of an application.
• Sidecar: It helps in deploying components to offer encapsulation and isolation.

4. Conclusion

As seen in this blog, microservices architecture is very beneficial to develop large applications by accommodating various business needs, and using cloud infrastructure like Azure can enable easy migration from legacy applications. Azure and various tools can help companies to create and manage well-designed microservices applications in the competitive market.

5. Frequently Asked Questions about Azure Microservices:

1. What are Azure Microservices?

Microservices refers to the architectural methodology employed in the development of a decentralized application, wherein multiple services that execute specific business operations and interact over web interfaces are developed and deployed independently.

2. What are the Different Types of Microservices in Azure?

• Azure Kubernetes Service (AKS): The Kubernetes control plane is hosted and maintained by the Azure Kubernetes Service (AKS), which is a governed Kubernetes service.
• Azure Container Apps: The Azure Container Apps service simplifies the often-tricky processes of container orchestration and other forms of administration.
• Service Fabric: Microservices can be put together, deployed, and managed with the help of Service Fabric, which is a distributed systems platform. 

3. How do I Use Microservices in Azure?

Step-1: Domain analysis

The use of domain analysis to create microservice boundaries helps designers avoid several errors. 

Step-2: Design the services

To properly support microservices, application development must shift gears. Check out Microservices architecture design to learn more.

Step-3: Operate in production

Distributed microservices architectures need dependable delivery and monitoring mechanisms.

4. Is an Azure Function a Microservice?

Azure functions have the capability to be employed within a microservices architectural framework; however, it is important to note that Azure functions do not inherently possess the characteristics of microservices.

5. How Microservices are Deployed in Azure?

Build an Azure Container Registry in a similar place as your microservices and connect it to a resource group for deploying them. Deployed container instances from your registry will run on a Kubernetes cluster.

The post Building Microservices Architecture Design on Azure appeared first on TatvaSoft Blog.

Key Takeaways

1. .NET Multi-platform App UI (MAUI) is an open source, cross platform framework to develop native applications for Windows, iOS, macOS, and Android platforms using C# and XAML.
2. .NET MAUI is an evolution of Xamarin.Forms with UI control redesigned for extensibility and better performance, becoming a new flagship.
3. It also supports .NET hot reload by which you can update and modify the source code while the application is running.
4. .NET MAUI project uses a single codebase and provides consistent and simplified platform specific development experience for the users.
5. One can also develop apps in modern patterns like MVU, MVVM, RxUI, etc. using .NET MAUI.

1. What is .NET MAUI?

.NET MAUI (Multi-platform App UI) is an open source and cross platform framework to create native mobile and desktop apps using C# and XAML. Using this multi-platform UI, one can develop apps that run on

1. Android 
2. iOS
3. MacOS
4. Windows

.NET MAUI is an evaluation of Xamarin.Forms, extended from mobile to desktop scenarios, and rebuilt UI controls from the base level to improve the performance. It is quite similar to Xamarin Forms, another framework for creating cross-platform apps using a single codebase. 

The primary goal of .NET MAUI is to help you to develop as much of your app’s functionality and UI layout as possible in a single project.

The .NET MAUI is suitable for the developers who want to

• Use single codebase to develop app for android, iOS, and desktop with C# and Xamarin.Forms
• Share Code, tests, and logic across all platforms
• Share common UI layout and design across all platforms

Now, let’s look at how .NET MAUI works. 

2. How does .NET MAUI Work?

.NET MAUI is a unified solution for developing mobile and desktop app user interfaces. With it, developers can deploy an app to all supported platforms using a single code base, and also provide unique access to every aspect of each platform. .

The Windows UI 3 (WinUI 3) library, along with its counterparts for Android, iOS, and macOS, are all part of the .NET 6 and later family of .NET frameworks for app development. The .NET Base Class Library (BCL) is shared by all of these frameworks. This library hides platform specifics from your program code. The .NET runtime is essential to the BCL because it provides a setting in which your code will be executed. Mono, a representation of the .NET runtime, provides the environment implementation for Android, iOS, and macOS. On Windows, the  .NET CoreCLR serves as the execution runtime.

Each platform has its own way of building an app’s visual interface and its own model for defining how the elements of an app’s user interface interact with one another; nevertheless, the Base Class Library enables multi-platform app UI to interchange business logic. The user interface may be designed independently for each platform utilizing a suitable framework, but it requires a distinct code base for each group of devices.

Native app packages may be compiled from .NET MAUI code written on either a PC or a Mac:

• When an Android app is developed with .NET MAUI, C# is translated into an intermediate language (IL), and during runtime, the IL is JIT-converted into a native assembler.
• Apps for iOS developed with .NET MAUI are converted from C# into native ARM assembly code.
• For macOS, this MAUI apps employ Mac Catalyst, an Apple technology that ports your UIKit-based iOS app to the desktop and enhances it with extra AppKit and platform APIs.
• Native Windows desktop programs developed with .NET MAUI are created with the help of the Windows User Interface 3 (WinUI 3) library.

3. What’s Similar between .NET MAUI & Xamarin Forms?

The community is still developing apps with XAML and C#. To separate our logic from the view specification, we can use Model-View-Viewer (MVVM), Reactive User Interface (UI), or Model-View-Update.

We can create apps for:

• Windows Desktop
• iOs & macOS
• Android

It is easy to relate with .NET MAUI if you have prior experience with Xamarin. While the project configuration may shift, the code you write daily should seem like an old hat.

4. What is Unique about .NET MAUI?

If Xamarin is already available, then what makes .NET MAUI so different? To improve Xamarin, Microsoft is revamping its foundation. Forms, which boosted speed, unified the architectural systems and brought us beyond mobile to the desktop.

Major Advances in MAUI:

4.1 Single Project Experience

You can build apps for Android, iOS, macOS, and Windows all from a single  .NET MAUI project, which abstracts away the platform-specific development experiences you’d normally face.

When developing for several platforms, using a .NET MAUI single project simplifies and standardizes the process. The following benefits are there for using  .NET MAUI single project:

• A unified project that can develop for iOS, macOS, Android, and Windows.
• Your .NET MAUI applications can run with a streamlined debug target option.
• Within a single project, shared resource files can be used.
• A single manifest file that describes the name, identifier, and release number of an app.
• When necessary, you can use the platform’s native APIs and toolkit.
• Simply one code-base for all platforms.

4.2 .NET Hot Reload

The ability to instantly update running apps with fresh code changes is a huge time saver for .NET developers thanks to a feature called “hot reload.” 

It helps to save time and keeps the development flow going by doing away with the need to pause for builds and deployments. Hot Reload is being improved in .NET, with full support coming to .NET MAUI and other workloads.

4.3 Cross-Platform APIs for Device Features

APIs for native device features can be accessed across platforms thanks to .NET MAUI. The .NET Multi-platform App UI  (MAUI) provides access to functionalities like:

• Keep us posted regarding the device on which your app is installed.
• Control of device’s sensors, including the accelerometer, compass, and gyroscope.
• Select a single file or a batch from the storage device.
• The capacity to monitor and identify changes in the device’s network connectivity status.
• Read text using the device’s in-built text-to-speech engines.
• Transfer text between applications by copying it to the system clipboard.
• Safely store information using key-value pairs.
• Start an authentication process in the browser that awaits a response from an app’s registered URL.

5. How to Build Your First App Using .NET MAUI? 

1. Prerequisites

Installation of the .NET Multi-platform App UI workload in Visual Studio 2022 version 17.3 or later is required.

2. Build an Application

1. Start up Visual Studio 2022. To initiate a fresh project, select the “Create a new project” option.

2. Select MAUI from the “All project types” – menu, then choose the “.NET MAUI App” template and press the “Next” icon in the “Create a new project” window.

3. Give your project a name, select a location, and then press the “Next” button in the window labeled “Configure your new project”

4. Press the “Create” button after selecting the desired version of .NET in the “Additional information” window.

5. Hold off until the project is built and its dependencies are restored.

6. Choose Framework, and then the “.net 7.0-windows” option, from the “Debug” menu in Visual Studio’s toolbar:

7. To compile and launch the application, click the “Windows Machine” icon in Visual Studio’s toolbar.

Visual Studio will ask you to switch on Developer Mode if you haven’t already. This can be done via Settings of your device. Click “settings for developers” from VS code and on the “Developer Mode”. Also accept the disclaimer. 

8. To test this, open the app and hit the “Click me” icon many times to see the click counter rise:

6. Why .NET MAUI?

6.1 Accessibility 

.NET MAUI supports multiple approaches for accessibility experience. 

1. Semantic Properties: 

Semantic Properties are the approach to provide the accessibility values in apps. It is the most recommended one. 

2. Automation Properties

This is a Xamarin.Forms approach to provide accessibility values in apps. 

One can also follow the recommended accessibility checklist from the official page for more details. 

6.2 APIs to Access Services

Since .NET MAUI was built with expansion in mind, you may keep adding features as needed. Consider the Entry control, a classic illustration of a control that displays uniquely on one platform but not another. Developers frequently wish to get rid of the underlining that Android draws underneath the text field. Using .NET MAUI, you can easily modify each and every Entry throughout your whole project with minimal additional code.  

6.3 Global Using Statements and Field-Scoped Namespaces

.NET MAUI uses the new C# 10 features introduced in .NET 6, comprising global using statements and file-scoped namespaces. This is great for reducing clutter in your files. For example: 

6.4 Use Blazor for Desktop and Mobile

Web developers who want to create native client apps will find .NET MAUI to be an excellent choice. You may utilize your current Blazor web UI components in your native mobile and desktop apps thanks to the integration between .NET MAUI and Blazor. .NET MAUI and Blazor allow you to create a unified user interface (UI) for mobile, desktop, and web apps.

Without the requirement for WebAssembly, .NET MAUI will run your Blazor components locally on the device and render them to an in-app web view. Since Blazor parts are compiled and executed in the .NET procedure, they are not restricted to the web platform and may instead make use of features specific to the target platform, such as the platform’s filesystem, sensors, and location services. Your Blazor web UI can even have native UI controls added to it. Blazor Hybrid is a completely original hybrid app.

Using the provided .NET MAUI Blazor App project template, you can quickly begin working with Blazor and .NET MAUI.

With this starting point, you can quickly begin developing an HTML5, CSS3, and C#-based .NET MAUI Blazor app. The .NET MAUI Blazor Hybrid guide will show you how to create and deploy your very own Blazor app.

If you already have a .NET MAUI project and wish to start using Blazor components, you may do so by adding a BlazorWebView regulation to it:

Present desktop programs can now be updated to operate on the web or cross-platform with .NET MAUI due to Blazor Hybrid support for WPF and Windows Forms. BlazorWebView features for Windows Presentation Foundation and Windows Forms can be downloaded via NuGet. 

6.5 Optimized for Speed

.NET MAUI is developed for performance. .NET MAUI’s user interface controls are built on top of the native platform controls with a thin, decoupled handler-mapper design. This streamlines the display of user interfaces and makes it easier to modify controls.

In order to speed up the rendering and updating of your user interface, .NET MAUI’s layouts have been designed to follow a uniform management approach that improves the measure and setup loops. In the context of StackLayout, layouts are exposed that have already been optimized for certain use cases, such as HorizontalStackLayout and VerticalStackLayout.

It was started off with the intention of reducing app size and speeding up startup time when it was upgraded to .NET 6. The .NET Podcast example application, which used to take 1299 milliseconds to start up, now takes just 814.2 milliseconds—a 37.3% improvement .

To make these improvements available in a release build, these options are enabled by default.

Quicker code launches for your Android apps are possible using ahead-of-time (AOT) compilation. If you’re trying to keep your application’s size within the wifi installation threshold, full AOT can make your outputs too big. Startup Tracing is the solution to this problem. As the name suggests, it makes you achieve an acceptable balance between performance and size by performing partial AOT on only the portions of your program to run at startup.

Benchmark numbers from Pixel 5 device tests by GitHub :

6.6 Native UI

With .NET MAUI, you can create uniform brand experiences across many platforms (Android, iOS, macOS, and Windows) while also making use of each system’s unique design for the greatest app experience possible. Each system works and appears as intended right out of the box, without the need for any further widgets or ad hoc styling. For instance, WinUI 3, the best native UI component included with the Windows App SDK, supports .NET MAUI on Windows.

With .NET MAUI native UI, you can:

• Create your apps using a library of more than 40 controls, layouts, and pages using C# and XAML. 
• Built upon the solid foundation of Xamarin’s mobile controls, it extends them to include things like navigation bars, multiple windows, improved animation, and enhanced support for gradients, shadows, and other visual effects.

7. Conclusion

Microsoft’s newest addition to the .NET family is the .NET Multi-platform User Interface which was created to develop apps in C#,.NET, and XAML for Windows, Android, iOS, and macOS. Also, instead of creating numerous versions of your project for different devices, you can now create a single version and distribute it across all of them. 

We hope this article helped you gain a basic introduction to .NET MAUI. There are many wonderful improvements in MAUI that are expected in the future, but we will need to remain patient a bit longer for a release candidate edition of MAUI to include them all. So, stay tuned.

The post Introduction to .NET MAUI appeared first on TatvaSoft Blog.

Key Takeaways

1. Following a proper set of Java Best Practices enables the entire team to manage the Java project efficiently.
2. Creating proper project & source files structures, using proper naming conventions, avoiding unnecessary objects and hardcoding, commenting the code in a correct way helps in maintaining the Project Code effectively.
3. By using appropriate inbuilt methods and functionality, one can easily improve the performance of Java applications.
4. For exception handling, developers must utilise the catch and finally block as and when required.
5. By writing meaningful logs, developers can quickly identify and solve the errors.

For any developer, coding is a key task and making mistakes in it is quite possible. Sometimes, the compiler will catch the developer’s mistake and will give a warning but if it is unable to catch it, running the program efficiently will be difficult. And because of this, for any Java app development company, it is essential to make its team follow some of the best practices while developing any Java project. In this blog, we will go through various different types of Java best practices that will enable Java developers to create the application in a standardised manner.

1. Java Clean Coding Best Practices

Here we will have a look at the best practices of Java clean coding –

1.1 Create a Proper Project Structure

Creating the proper project structure is the first step to follow for Java clean coding best practices. Here, the developers need to divide and separate the entire code into related groups and files which enables them to identify the file objectives and avoid rewriting the same code or functions multiple times. 

A good example of the Java Project structure is as follow: 

• Source
  • Main
    • Java
    • Resource
  • Test
    • Java 
    • Resource

Now, let’s understand each directory in the structure:

Source files refers to the files like Controller, Service, Model, Entity, DTO, and Repositories files, while test source files refers to the test cases files which are written to test the code.

1.2 Use Proper Naming Conventions

Naming conventions mean the names of the interfaces and classes and see how to keep the names of constants, variables, & methods. The conventions set at this stage must be obeyed by all the developers in your team. Some of the best practices that entire team can follow are as follow:

• Meaningful distinctions: This means that the names given to the variables or other identifiers must be unique and they should have a specific meaning to it. For instance, giving names like i, j, k or p, q, r isn’t meaningful. 
• Self-explanatory: The naming convention must be such that the name of any variable reveals its intention so that it becomes easy for the entire Java development team to understand it. For instance, the name must be like “dayToExpire” instead of “dte”. This means that the name must be self-explanatory and must not require any comment to describe itself.
• Pronounceable: The names given by the developers must be pronounceable naturally just like any other language. For instance, we can keep “generationTimestamp” instead of “genStamp”.

Besides this, there are some other general rules that are required when it comes to naming conventions and they are –

• Methods of the Java code should have names that are starting with lowercase and are verbs. For instance, execute, stop, start, etc. 
• Names of class and interface are nouns which means that they must start with an uppercase letter. For instance, Car, Student, Painter, etc.
• Constant names must be in uppercase only. For instance, MIN_WIDTH, MAX_SIZE, etc.
• Underscore must be used when the numeric value is lengthy in Java code. For instance, the new way to write lengthy numbers is int num = 58_356_823; instead of int num = 58356823;.
• In addition to this, the use of camelCase notation is also done in Java programming naming conventions. For instance, runAnalysis, StudentManager, and more.

1.3 Avoid Creating Unnecessary Objects

Another best practice for Java clean coding is to avoid creating unnecessary objects. It is known as one of the best memory-consuming operations in Java. This means that the developers must only create objects that are required. 

You can often avoid creating unnecessary objects by using static factory methods in preference to constructors on immutable classes. 

For example, the static factory method Boolean.valueOf(String) is always preferable to the constructor Boolean(String). 

The constructor creates a new object each time whenever it’s called, while the static factory method is not required to do so.

1.4 Create Proper Source File Structure

A source file is something that holds information about various elements. And when the Java compiler enforces any type of structure, a large part of it is fluid. But when some specific order is implemented in a source file it can help in improving the code readability. And for this, there are some different types of style guides available for inspiration for developers. Here is the element’s ordering style that can be used in a source file – 

1. Package Statement
2. Import Statements
   • Static and non-static imports
3. One top-level Class
   • Constructors
   • Class variables
   • Instance variables
   • Methods

Besides this, the developers can also group the methods as per the scope and functionalities of the application that needs to be developed. Here is a practical example of it – 

# /src/main/java/com/baeldung/application/entity/Customer.java
package com.baeldung.application.entity;

import java.util.Date;

public class Patient {
    private String patientName;
    private Date admissionDate;
    public Patient(String patientName) {
        this.patientName = patientName;
        this.admissionDate = new Date();
    }

    public String getPatientName() { 
        return this.patientName; 
    }

    public Date getAdmissionDate() {
        return this.admissionDate;
    }
}

1.5 Comment on the Code Properly

Commenting on the written code is very beneficial when other team members are going through it as it enables them to understand the non-trivial aspects. And in this case, proper care must be taken as specific and to-the-point things must be described in the comments as if not done in a required manner, the comments can confuse developers. 

Besides this, when it comes to commenting on the Java code, there are two types of comments that can be used.

Here, we will have a look at the code that specifies the usage of the meaningful documentation comment:

/**
* This method is intended to add a new address for the employee.
* However do note that it only allows a single address per zip
* code. Hence, this will override any previous address with the
* same postal code.
*
* @param address an address to be added for an existing employee
*/
/*
* This method makes use of the custom implementation of equals 
* method to avoid duplication of an address with the same zip code.
*/
public addEmployeeAddress(Address address) {
}

Implementation Comments:

class HelloWorld {
    public static void main(String[] args) {
        System.out.println("Hello, World!"); 	// This will print “Hello, World!”
    }
}

1.6 Avoid Too Many Parameters in Any Method

When it comes to coding in Java, one of the best practices is to optimize the number of parameters in a method. This means that when any program has too many parameters in a method it can make interpreting the code difficult and complex. 

Let’s have a look at the example of this scenario. Here is the code where there are too many parameters –

private void employeeInformation(String empName, String designation, String departmentName, double salary, Long empId)

Here is the code with an optimized number of parameters –

private void employeeInformation(String empName, Info employeeInfo)

1.7 Use Single Quotes and Double Quotes Properly

In Java programming, single quotes are used to specify characters in some unique cases, and double quotes for strings. 

Let’s understand this with an example: 

Here, to concatenate characters in Java, in order to make a string, double quotes are used as they treat characters as simple strings. Besides this, single quotes specify integer values of the characters. Let’s have a look at the below code as an example – 

public class demoExample
{
 public static void main(String args[]) 
{
  System.out.printIn("A" + "B");
  System.out.printIn('C' + 'D');
}
}

Output:-
AB
135

1.8 Write Code Properly

Code written for any type of application in Java must be easier to read and understand. The reason behind it is that when it comes to Java, there is no single convention for code. Therefore, it is necessary to define a private convention or adopt a popular one. Here are the reasons why it is important and why it is essential to have indentation criteria – 

• The Java developers must use four spaces for a unit of indentation. 
• There must be a cap over the line length, but it can also be set to more than 80 owing.
• Besides this, expressions must be broken down with commas. 

Here is the best example of it – 

List employeeIds = employee.stream()
  .map(employee -> employee.getEmployeeId())
  .collect(Collectors.toCollection(ArrayList::new));

1.9 Avoid Hardcoding

Avoiding hard coding is another best practice that must be followed by developers. For instance, hard coding can lead to duplication and can make it difficult for the developers to change the code when required. 

Besides this, it can also lead to undesirable behaviour when the values in the code are dynamic. Also, hardcoding factors can be refactored in the following manner – 

• Developers must replace enum or constant value with defined methods or variables in Java.
• They can also replace class-level defined constants or the values picked from the configuration. 

For Example:

private int storeClosureDay = 7;
// This can be refactored to use a constant from Java
private int storeClosureDay = DayOfWeek.SUNDAY.getValue()

1.10 Review and Remove Duplicate Code

Reviewing the duplicate code is another important best practice that needs to be followed. It can happen that sometimes two or multiple methods have the same intent and functionality in your Java project code. In such cases, it becomes essential for the developers to remove the duplicate methods / class and use the single method / class wherever required.

2. Java Programming Best Practices

Here are some of the best practices of Java coding that developers can take into consideration – 

2.1 Keep Class Members as Private

Class members should be private wherever possible. The reason behind it is that the more inaccessible the member variables are, the better the programming is done. This is the reason why Java developers must use a private access modifier. Here is an example that shows what happens when fields of the class are made public –

public class Student {
  public String name;
  public String course;
} 

Anyone who has access to the code can change the value of the class Student as shown in the below code –

Student student= new Student();
student.name = "George";
student.course = "Maths";

This is why one should use private access modifiers when it comes to defining the class members. The private class members have the tendency to keep the fields hidden and this helps in preventing any user of the code from changing the data without using setter methods. For Example: 

public class Student {
  private String name;
  private String course;
  
  public void setName(String name) {
    this.name = name;
  }
  public void setCourse(String course)
    this.course = course;
  }
}

Besides this, the setter methods are the best choice when it comes to code validation or housekeeping tasks. 

2.2 For String Concatenation, Use StringBuilder or StringBuffer

Another Java best practice is to use StringBuffer or StringBuilder for String concatenation.  Since String Object is immutable in Java, whenever we do String manipulation like concatenation, substring, etc., it generates a new string and discards the older string for garbage collection. These are heavy operations and generate a lot of garbage in the heap. So Java has provided StringBuffer and StringBuilder classes that should be used for String manipulation. These are mutable objects in Java and also provide append(), insert(), delete, and substring() methods for String manipulation.

Here is an example of the code where the “+” operator is used –

String sql = "Insert Into Person (name, age)";
sql += " values ('" + person.getName();
sql += "', '" + person.getage();
sql += "')";

// "+" operator is inefficient as JAVA compiler creates multiple intermediate String objects before creating the final required string.

Now, let’s have a look at the example where the Java developer can use StringBuilder and make the code more efficient without creating intermediate String objects which can eventually help in saving processing time – 

StringBuilder sqlSb = new StringBuilder("Insert Into Person (name, age)");
sqlSb.append(" values ('").append(person.getName());
sqlSb.append("', '").append(person.getage());
sqlSb.append("')");
String sqlSb = sqlSb.toString();

2.3 Use Enums Instead of Interface

Using enums is a good practice rather than creating an interface that is solely used to declare some constants without any methods. Interfaces are designed to define common behaviours and enums to define common values, So for defining values, usage of enums is best practice. 

In the below code, you will see what creating an interface looks like –

public interface Colour {
    public static final int RED = 0xff0000;
    public static final int WHITE = 0xffffff;
    public static final int BLACK = 0x000000;
}

The main purpose of an interface is to carry out polymorphism and inheritance, not work for static stuff. Therefore, the best practice is to start using enum instead. Here is the example that shows the usage of an enum instead of an interface –

public enum Colour {
    RED, WHITE, BLACK
}

In case – the colour code does matter, we can update the enum like this:

public enum Colour {
 
   RED(0xff0000);
    BLACK(0x000000),
    WHITE(0xffffff),
   
    private int code;
 
    Color(int code) {
        this.code = code;
    }
 
    public int getCode() {
        return this.code;
    }
}

As we can see that the code is a bit complex because of the project and in such cases we can create a class that is dedicated to defining constants. An example of this is given below – 

public class AppConstants {
    public static final String TITLE = "Application Name";
 
    public static final int THREAD_POOL_SIZE = 10;
    
    public static final int VERSION_MAJOR = 8;
    public static final int VERSION_MINOR = 2;

    public static final int MAX_DB_CONNECTIONS = 400;
 
    public static final String INFO_DIALOG_TITLE = "Information";
    public static final String ERROR_DIALOG_TITLE = "Error";
    public static final String WARNING_DIALOG_TITLE = "Warning";    
}

By having a look at the code above, we can say that it is an unsaid rule that using enums or dedicated classes is a better idea than using interfaces. 

2.4 Avoid Using Loops with Indexes

Developers must avoid using a loop with an index variable wherever possible. Instead they can replace it with forEach or enhanced for loop. 

The main reason behind this is that the index variable is error-prone, which means that it may incidentally alter the loop’s body, or start the index from 1 instead of starting it from 0. Here is an example that enables the developer to iterate over an array of Strings:

String[] fruits = {"Apple", "Banana", "Orange", "Strawberry", "Papaya", "Mango"};
 
for (int i = 0; i < fruits.length; i++) {
    doSomething(fruits[i]);
}

The above code specifies that the index variable “i”  in this for loop is something that can be easily altered and can cause unexpected results. To prevent this, the developers must use an enhanced for loop like this:

for (String fruit : fruits) {
    doSomething(fruit);
}

2.5 Use Array Instead of Vector.elementAt()

Vector is known as a legacy implementation approach that is used with Java bundle. It is just like ArrayList but unlike it, Vector can be synchronised. It doesn’t require additional synchronisation when multiple threads try to access it but at the same time, it also degrades the performance of the Java application. And when it comes to any application, performance is the most important factor. Therefore, the array must be used instead of a Vector. 

Let’s take an example where we have used the vector.elementAt() method to access all the elements.

int size = v.size();
for(int i=size; i>0; i--)
{
    String str = v.elementAt(size-i);    
}

For best practice, we can convert the vector first into an array. 

int size = v.size();
String arr[] = (String[]) v.toArray();

2.6 Avoid Memory Leaks

Unlike most other programming languages for software development, when developers are working with Java, they do not need to have much control over memory management. The reason behind it is that Java is a programming language that manages memory automatically. 

In spite of this, there are some Java best practices that experts use to prevent memory leaks because any kind of memory loss can degrade an application's  performance and also affect the business. 

There are few more points to prevent memory leaks in Java.

• Do not create unnecessary objects.
• Avoid String Concatenation and use String Builder and String Buffer.
• Don't store a massive amount of data in the session and time out the session when no longer used.
• Do not use the System.gc() and also avoid using static objects.
• Always close the connections, statements and result sets in the Finally block.

2.7 Debug Java Programs Properly

Debugging Java programs properly is another practice that developers need to follow. For this, there is nothing much that they need to do. The developers just have to right-click from the package explorers. Then they can select the option Debug As and choose the Java application they prefer to debug. This can help them to create a Debug Launch Configuration which can be utilized by the experts to start the Java application. 

Besides this, nowadays, Java developers can edit and save the project code while they are debugging it without any need of restarting the entire program and this is possible because of the HCR (Hot Code Replacement). HCR is a standard Java approach that is added to enable expert Java developers to experiment with the code and have an iterative trial-and-error coding.

Debugging allows you to run a program interactively while watching the source code and the variables during the execution. A breakpoint in the source code specifies where the execution of the program should stop during debugging. Once the program is stopped you can investigate variables, change their content, etc. To stop the execution, if a field is read or modified, you can specify watchpoints.

Here is a post that describes the unique Java debugging tools:

2.8 Avoid Multiple if-else Statements

Another Java programming best practice is to avoid the usage of multiple if-else statements. The reason behind it is that when conditions like if-else statements are overused, they will affect the performance of the application as JVM will have to compare the conditions every now and then. 

Besides this, using conditions more than required can become worse if the same one is utilized by the developers in looping statements like while, for, and more. Basically, when there are too many statements or conditions used, the business logic of the application will try to group all the conditions and offer the boolean outcome. Here is an example that shows what happens when the if-else statement is overused and why it should be avoided -

if (condition1) {

    if (condition2) {

        if (condition3 || condition4) { execute ..}

        else { execute..}

Note: The above-defined code must be avoided and the developers must use this as follows:

boolean result = (condition1 && condition2) && (condition3  || condition4)  

One can use Switch in place of  if-else. Switch can execute one statement for multiple conditions. It is an alternative of the if-else-if  ladder condition. It also makes it easy to dispatch execution to different parts of code based on value of expression.

// switch statement 
switch(expression)
{
   // case statements
   // values must be of same type of expression
   case value1 :
      // Statements
      break; // break is optional
   
   case value2 :
      // Statements
      break; // break is optional
   
   // We can have any number of case statements
   // below is the default statement, used when none of the cases is true. 
   // No break is needed in the default case.
   default : 
      // Statements
}

2.9 Use Primitive Types Wherever Possible

Java developers should try using primitive types over objects whenever possible as the data of primitive types are on stack memory. While on the other hand, if objects are used, they are stored on heap memory which is comparatively slower than stack memory.

For example: Use int instead of Integer, double instead of Double, boolean instead of Boolean, etc.

Apart from this, developers must also avoid default initialization values to assign while creating any variable. 

3. Java Exception Handling Best Practices

Here are some of the best practices of Java Execution Handling -

3.1 Don’t Use an Empty Cache Block

Using empty catch blocks is not the right practice in Java programming and the reason behind it is that it can silently fail other programs or continue the program as if nothing has happened. In both cases, it makes it harder to debug the project code. 

Here is an example showing how to multiply two numbers from command-line arguments - (we have used an empty catch block here)

public class Multiply {
  public static void main(String[] args) {
    int a = 0;
    int b = 0;
    
    try {
      a = Integer.parseInt(args[0]);
      b = Integer.parseInt(args[1]);
    } catch (NumberFormatException ex) {
 	// Throwing exception here is ignored
    }
    
    int multiply = a * b;
    
    System.out.println(a + " * " + b + " = " + multiply);
  }
}

Generally, the parseInt() method is used which throws a NumberFormatException Error. But in the above code, throwing exceptions has been ignored which means that an invalid argument is passed that makes the associated variable populated with the default value.

3.2 Handle Null Pointer Exception Properly

Null Pointer Exception occurs when the developer tries to call a method that contains a Null Object Reference. Here is a practical example of the same situation -

int noOfStudents = office.listStudents().count;

Though there is no error in this code, if any method or object in this code is Null then the null pointer exception will be thrown by the code. In such cases, null pointer exceptions are known as inevitable methods but in order to handle them carefully, the developers must check the Nulls prior to execution as this can help them alter or eliminate the null in the code. Here is an example of the same -

private int getListOfStudents(File[] files) {
 if (files == null)
 throw new NullPointerException("File list cannot be null");

3.3 Use Finally Wherever Required

“Finally” block enables developers to put the important code safely. It enables the execution of code in any case which means that code can be executed whether exceptions rise or not. Besides this, Finally is something that comes with some important statements which are regardless of whether the exception occurs or not. For this, there are three different possibilities that can be carried out by the developers, and we will go through all these cases.

Case 1: Here, Finally can be used when an exception does not rise. The code written here runs the program without throwing any exceptions. Besides this, this code executes finally after the try block.

// Java program to demonstrate
// finally block in java When
// exception does not rise 
  
import java.io.*;
  
class demo{
    public static void main(String[] args)
    {
        try {
            System.out.println("inside try block");
            System.out.println(36 / 2);   // Not throw any exception
        }
        
        // Not execute in this case
        catch (ArithmeticException e) {
            
            System.out.println("Arithmetic Exception");
            
        }
        // Always execute
        finally {
            
            System.out.println(
                "finally : always executes");
            
        }
    }
}

Output -
inside try block
18
finally : always executes

Case 2: The second method where Finally is executed after the catch block when the exception rises.

// Java program to demonstrate final block in Java
// When exception rise and is handled by catch
  
import java.io.*;
  
class demo{
    
    public static void main(String[] args)
    {
        try {
             System.out.println("inside try block");
System.out.println(34 / 0);    // This Throw an Arithmetic exception
        }
  
        // catch an Arithmetic exception
        catch (ArithmeticException e) {
  
            System.out.println(
                "catch : arithmetic exception handled.");
        }
  
        // Always execute
        finally {  
          System.out.println("finally : always executes"); 
        }
    }
}

Output -
inside try block
catch : arithmetic exception handled.
finally : always executes

Case 3: The third case specifies the situation where the Finally is executed after the try block and is terminated abnormally. This situation is when the exception rises. In this case, in the end, Finally still works perfectly fine.

import java.io.*;
  
class demo{
    public static void main(String[] args)
    {
        try {
            System.out.println("Inside try block");  
            // Throw an Arithmetic exception
            System.out.println(36 / 0);
        }
  
        // Can not accept Arithmetic type exception; Only accept Null Pointer type Exception
        catch (NullPointerException e) {
            System.out.println(
                "catch : exception not handled.");
        }
  
        // Always execute
        finally {
  
            System.out.println(
                 System.out.println("finally : always executes");

        }
        // This will not execute
        System.out.println("i want to run");
    }
}

Output -
Inside try block
finally : always executes
Exception in thread "main" java.lang.ArithmeticException: / by zero
at demo.main(File.java:9)

3.4 Document the Exceptions Properly

Another best practice for Java exception handling is to document the exceptions of the project. This means that when any developer specifies any type of exception in the method, it must be documented. It helps the developers to keep records of all the information and also enables other team members to handle or avoid exceptions as per the requirement. And for this, the developer needs to add a @throws declaration in the Javadoc while documenting the exceptions and also describing the entire situation. 

If you throw any specific exception, its class name should specifically describe the kind of error. So, you don’t need to provide a lot of other additional information. Here is an example for it - 

/**
* This method does something extremely useful ...
*
* @param input
* @throws DemoException if ... happens
*/
public void doSomething(int input) throws DemoException { ... }

3.5 Do not Log and Rethrow the Exception

When any exception occurs in the application, it must be either logged or carried out with the app or rethrown and let another method be logged in to save the details. Both situations should never be carried out at the same time. 

This means that the exceptions that developers carry out in the application must never log the details and then rethrow the same. Here is an example for the same -

/* example of log and rethrow exception*/
try {
  Class.forName("example");
} catch (ClassNotFoundException ex) {
  log.warning("Class not found.");
  throw ex;
}

3.6 Catch the Most Specific Exception First

Developers must catch the most specific exceptions first. By following this practice, code gets executed easily, and the catch block can be reached faster. 

Here is an example of this where the first catch block enables the system to handle all NumberFormatExceptions and the second one enables handling of all IllegalArgumentExceptions that are not a part of NumberFormatException.

Other Generic Exceptions will be caught in the last catch block.

public void catchMostSpecificExceptionFirst() {
	try {
		doSomething("A message");
	} catch (NumberFormatException e) {
		log.error(e);
	} catch (IllegalArgumentException e) {
		log.error(e)
	} catch (Exception e) {
		log.error(e)
	}
}

4. Java Logging Best Practices

Here are some of the best practices of Java Logging:

4.1 Use a Logging Framework

Using a logging framework is essential as it enables keeping records of all the methods and approaches of the code. And for robust logging, the developers must deal with concurrent access, format log messages, write alternative destinations of logs, and configure all the logs. 

Basically, when the developer is adopting a logging framework, he will be able to carry out a robust logging process without any issues. One of the widely used logging frameworks is Apache Log4j 2 framework. 

Additionally, you can use levels to control the granularity of your logging, for example: LOGGER.info, LOGGER.warn, LOGGER.error, etc.

4.2 Write Meaningful Messages

Another best practice while logging in to Java is to write meaningful messages. If the log events of the project contain meaningful and accurate messages about the given situation, it will be easy for the entire team to read and understand the code while working on it. And if any error occurs in the application, it can be really helpful as they will have enough information to understand and resolve the issue. Here is an example of the same - 

LOGGER.warn("Communication error");

The message must be written as - 

LOGGER.warn("Error while sending documents to events Elasticsearch server, response code %d, response message %s. The message sending will be retried.", responseCode, responseMessage);

The first message will inform you that there is a communication issue in the logging process but it doesn’t specify anything else which means that the developer working at that time on the project will have to find out the context of the error, the name of the logger, and the line of the code that has a warning.  

The second message provides all the information about the logging communication error which means that any developer will get the exact message that is required. This shows that when messaging is done in an easy way, it helps anyone to understand the error and the entire logging system.

4.3 Do not Write Large Logs

Writing large logs is not the right practice as when unnecessary information is incorporated it can reduce the value of the log as it masks the data that is required. It can also create problems with the bandwidth or the performance of the application. 

Too many log messages can also make reading and identifying relevant information from a log file whenever a problem occurs.

4.4 Make Sure You’re Logging Exceptions Correctly

Another Java best practices that the developers must follow while logging the Java code is to make sure that the exceptions are logged correctly. They must not be reported multiple times. Exceptions must be only monitored and reported by using automated tools as they also create alerts.

4.5 Add Metadata

Adding metadata in the logs enables other developers working on the project to find production issues faster. Metadata can be really useful which means that the more they are used the more it is beneficial for the project.

Eg: 

logger.info(“This process is for following user -> {}”,user.getUserName());

5. Conclusion

As seen in this blog, when any developer is developing a Java application, there are many things he must consider as in the long term other experts will be maintaining the same project. For this reason, the developer must create an application by following the Java best practices that are the standardized approaches for it. In this way, in the future, any other developer will be comfortable handling and maintaining the software development project.

The post Java Best Practices for Developers appeared first on TatvaSoft Blog.

The main reason behind it is that early on, companies ran applications on physical servers and had no defined resource boundaries for the same. For instance, if there are multiple apps that run on a physical server, there are chances that one app takes up the majority of the resources and others start underperforming due to the fewer resources available. For this, containers are a good way to bundle the apps and run them independently. And to manage the containers, Kubernetes is majorly used by Cloud and DevOps Companies. It restarts or replaces the failed containers which means that no application can directly affect the other applications. 

Basically, Kubernetes offers a framework that runs distributed systems and deployment patterns. To know more about Kubernetes and key Kubernetes challenges, let’s go through this blog.

1. Kubernetes: What It can Do & Why Do You Need It?

Traditionally, companies used to deploy applications on physical servers which had no specific boundaries for resources and this led to an issue in which the performance of apps might suffer because of other apps’ resource consumption. 

To resolve this, bundling the apps and running them efficiently in containers – is a good way. This means that, in the production environment, the software development team needs to manage the containers that run the applications, and after that, the developers need to ensure that there is no downtime. For instance, if the container of the application goes down, another one needs to start. And handling this behavior can be really easy with Kubernetes. It offers a framework that can run distributed systems flexibly. 

Features

Kubernetes provides many great features

Examples:
– data config.
– automatic load balancing
– self-healing mechanisms
– easy management of secrets

It’s also extensible: you can use it with various tools and services.

— Francesco (@FrancescoCiull4) April 22, 2023

Kubernetes platform takes care of the app failover & scaling, offers deployment patterns, and much more. Besides this, Kubernetes has the capability to provide:

2. Key Kubernetes Challenges Organizations Face and Their Solutions

As we all know, many organizations have started adopting the Kubernetes ecosystem and along with that they are facing many Kubernetes challenges. So, they need a robust change program that is – a shift in mindset and software development practices which comes with two important standpoints – the organization’s viewpoint and the development teams’ viewpoint. Let’s go through the key Kubernetes challenges and possible solutions: 

2.1 Security

One of the biggest Kubernetes challenges users face while working with Kubernetes is security. The main reason behind it is the software’s vulnerability and complexity. This means that if the software is not properly monitored, it can obstruct vulnerability identification. Let’s look at where K8s best fit within the entire software development process for security:

Basically, when multiple containers are deployed, detecting vulnerabilities becomes difficult and this makes it easy for hackers to break into your system. One of the best examples of the Kubernetes break-in is the Tesla cryptojacking attack. In this attack, the hackers infiltrated the Kubernetes admin console of Tesla which led to the mining of cryptocurrencies on AWS, Tesla’s cloud resource. To avoid such security Kubernetes challenges, here are some recommendations you can follow:

Infrastructure Security

Containers Security

Other Recommendations

2.2 Networking

Kubernetes networking allows admins to move workloads across public, private, and hybrid clouds. Kubernetes is mainly used to package the applications with proper infrastructure and deploy updated versions quickly. It also allows components to communicate with one another and with other apps as well.

Kubernetes networking platform is quite different from other networking platforms. It is based on a flat network structure that eliminates the need to map host ports to container ports. There are 4 key Kubernetes challenges that one should focus on:

1. Pod to Pod Communication
2. Pod to Service Communication
3. External to Service Communication
4. Highly-coupled container-to-container Communication

Besides this, there are some areas that might also face multi-tenancy and operational complexity issues, and they are:

• During the time of deployment, if the process spans more than one cloud infrastructure, using Kubernetes can make things complex. The same issue arises when the same thing happens from different architectures with mixed workloads. 
• Complexity issues are faced by the users when mixed workloads from ports on Kubernetes and static IP addresses work together. For instance, when IP-based policies are implemented because pods make use of an infinite number of IPs, things get complex and challenging. 
• One of the Kubernetes challenges with traditional networking approaches is multi-tenancy. This issue occurs when multiple workloads share resources. It also affects other workloads in the same Kubernetes environment if the allocation of resources is improper.

In these cases, the container network interface (CNI) is a plug-in that enables the programmer to solve the networking Kubernetes challenges. This interface enables Kubernetes to easily integrate into the infrastructure so that the users can effectively access applications on various platforms. This issue can be resolved using service mesh which is an infrastructure layer in an application that has the capability to handle network-based intercommunication through APIs. It also enables the developers to have an easy networking and deployment process. 

Basically, these solutions can be useful to make container communication smooth, secure, seamless, and fast, resulting in a seamless container orchestration process. With this, the developers can also use delivery management platforms to carry out various activities like handling Kubernetes clusters and logs.

2.3 Interoperability

Interoperability can also be a serious issue with Kubernetes. When developers enable interoperable cloud-native applications on this platform, the communication between the applications starts getting tricky. It starts affecting the cluster deployment and the reason behind is that the application may have an issue in executing an individual node in the cluster. 

This means Kubernetes doesn’t work as well at the production level as it does in development, staging, and QA. Besides this, when it comes to migrating an enterprise-class production environment, there can be many complexities like governance, interoperability, and performance. For this, there are some measures that can be taken into consideration and they are:

• For production problems, fuel interoperability. 
• One can use the same command line, API, and user interface. 
• Leveraging collaborative projects in different organizations to offer services for applications that run on cloud-native can be beneficial. 
• With the help of Open Service Broker API, one can enable interoperable cloud-native applications and increase the portability between providers and offers. 

2.4 Storage

Storage is one of the key Kubernetes challenges that many organizations face. When larger organizations try to use Kubernetes on their on-premises servers, Kubernetes starts creating storage issues. The main reason behind it is that the companies are trying to manage the whole storage infrastructure of the business without using cloud resources. This leads to memory crises and vulnerabilities. 

The permanent solution is to move the data to the cloud and reduce the storage from the local servers. Besides this, there are some other solutions for the Kubernetes storage issues and they are:

1. Persistent Volumes:
   • Stateful apps rely on data being persisted and retrieved to run properly. So, the data must be persisted regardless of pod, container, or node termination or crashes. For this, it requires persistent storage – storage that is forever for a pod, container, or node.
   • If one runs a stateful application without storage, data is tied to the lifecycle of the node or pod. If the pod terminates or crashes, entire data can be lost.
   • For solution, one requires these three simple storage rules to follow:
     1. Storage must be available from all pods, nodes, or containers in the Kubernetes Cluster.
     2. It should not depend upon the pod lifecycle.
     3. Storage should be available regardless of any crash or app failure.
2. Ephemeral Storage:
   • This type of storage refers to the volatile temporary data saving approach that is attached to the instances in their lifetime data such as buffers, swap volume, cache, session data, and so on.
   • Basically, when containers can utilize a temporary filesystem (tmpfs) to write & read files, and when a container crashes, this tmpfs gets lost.
   • This makes the container start again with a clean slate.
   • Also multiple containers can not share the temporary filesystem.
3. Some other Kubernetes challenges can be solved through:
   • Decoupling pods from the storage
   • Container Storage Interface (CSI)
   • Static provisioning and dynamic provisioning with Amazon EKS and Amazon EFS

2.5 Cultural Change

Not every organization succeeds even after adopting new processes, and team structures, and implementing easy-to-use new software development technologies and tools. They also tend to constantly improve the portfolio of systems which might affect the work quality and time. Due to this reason, businesses must establish the right culture in the firm and come together to ensure that innovation comes at the intersection of business and technology.

Apart from this, companies should make sure that they start promoting autonomous teams that can have their own freedom to create their own work practices and internal goals. This helps them get motivated to create high-quality and reliable output.

Once they have a qualitative and reliable outcome, companies should focus on reducing uncertainties and creating confidence which is possible by encouraging experimentation and all these things benefit companies a lot. Any organization that is constantly active, trying new things and re-assessing is more suited to create an adaptive architecture that is easy to roll back and can be expandable without any risk.

Automation is the most essential thing when it comes to evolutionary architecture. Adopting new architecture and handling the changes that the architecture has brought in an effective manner includes provisioning end-to-end infrastructure as code with the use of tools like Ansible and Terraform. Besides this, automation can also include adhering to software development lifecycle practices such as testable infrastructure with continuous integration, version control, and more. Basically, the companies that nurture such an environment, lean towards creating interactive cycles, safety nets, and space for exploration.

2.6 Scaling

Any business organization in the market aims to increase its scope of operations over a period of time. But not everyone gets successful in this desire as their infrastructure might be poorly equipped to scale. And this is a major disadvantage. In this case, if companies are using Kubernetes microservices, because of its complex nature, it generates a huge amount of data to be deployed, diagnosed, and fixed which can be a daunting task. Therefore, without the help of automation, scaling can be a difficult task. The main reason behind it is that for any company working with mission-critical apps or real-time apps, outages are very damaging to user experience and revenue. This also happens to companies offering customer-facing services through Kubernetes.

If such issues aren’t resolved then choosing an open-source container manager for running Kubernetes can be a solution as it helps in managing and scaling apps on multi-cloud environments or on-premises. These containers can handle functions like- 

• Easy to scale clusters and pods.
• Infrastructure management across multiple clouds and clusters.
• User-friendly interface for deployment. 
• Easy management of RBAC, workload, and project guidelines.

Scaling can be done Vertical as well as Horizontal.

• Suppose, an application requires roughly 3 GiB RAM, and there is not much going on the cluster, then you will require only one node. But for the safer side you can have a 5GiB node where 3 GiB node will be in use and the remaining 2 GiB in stash. So, when your application starts consuming more resources, you can immediately have those 2 GiB node available.  And you start paying for those resources when in use. This is Vertical Scaling.

• K8s also supports horizontal auto-scaling. New nodes will be added to a cluster whenever CPU, RAM, Disk Storage, I/O reaches a certain usage limit. New nodes will be added as per the cluster topology. Let’s understand it from following image: 

2.7 Deployment

Last challenge on our list is the deployment of containers.

What is a deployment in K8s?

A K8s Deployment defines the desired state of a containerized app, managing:
– its rollout
– updates
– scaling

It ensures the correct number of replicas (multiple containers with the same image) and smooth transitions between versions. pic.twitter.com/Tft4T7raZ3

— Francesco (@FrancescoCiull4) April 22, 2023

Companies sometimes face issues while deploying Kubernetes containers and these issues occur because Kubernetes deployment requires various manual scripts. This process becomes difficult when the development team has to perform various deployments using Kubernetes manual scripts. And this slows down the process. For such issues, some of the best Kubernetes practices are:

• Spinnaker pipeline for automated end-to-end deployment.
• Inbuilt deployment strategies.
• Constant verification of new artifacts.
• Fixing container image configuration issue.
• Kubernetes enables solving issues about fixing node availability.

Common Errors Related to Kubernetes Deployments and Their Possible Solutions:

3. How have Big Organizations Benefited after Using Kubernetes?

Here are some of the instances that show that big organizations have benefited from Kubernetes:

4. Conclusion

As seen in this blog, Kubernetes is an open-source container orchestration solution that helps businesses manage and scale their containers, clusters, nodes, and deployments. As this is a unique system, developers face many different Kubernetes challenges while working with its infrastructure and managing and scaling business processes between cloud providers. But once they master this tool, Kubernetes can be used in a way that offers an amazing, declarative, and simple model for programming complex deployments.

The post Key Kubernetes Challenges and Solutions appeared first on TatvaSoft Blog.

Jenkins has built-in functionality for CI CD process implementation. Using Jenkins, CI CD pipeline alongside your assignment will substantially accelerate your software development process.

You’re at the ideal place if you want to learn more about the Jenkins CI CD pipeline. Continue on, and in this article, you’re going to discover how to build up the CI/CD pipeline using Jenkins.

1. What is Continuous Integration (CI)/Continuous Delivery (CD)?

“Continuous Integration” refers to the process of integrating the new code into an existing repository in real time. As a preventative measure, it employs automated checks to spot issues before they become major. While CI can’t guarantee bug-free code, it can speed up the process of locating and fixing problems.

With the “Continuous Delivery” process, modifications to the code are performed before deployment. During this stage, the team determines what will be released to consumers and when. Deployments are the crucial stage in the entire process.

1. CI/CD stands for Continuous Integration and Continuous Deployment.

It’s a process where code changes are regularly merged into a shared repository, and then automatically deployed to a staging or production environment.

— Nikki Siapno (@NikkiSiapno) March 5, 2023

When these two methods are combined, the resulting process is called continuous integration/continuous delivery (CI/CD) since all the stages are automated. With CI/CD in place, the team can deliver code more rapidly and reliably. With this procedure, the team becomes more nimble, productive, and self-assured.

The most popular DevOps tool for CI/CD pipelines is Jenkins. Therefore, let’s take a look at the creation part of CI/CD pipelines using Jenkins. 

2. What is Jenkins?

Jenkins is a free and open-source automation server. The tool streamlines the process of incorporating code modifications into the development. Jenkins performs Continuous Integration with the aid of plugins.

Jenkins’s adaptability, approachability, plugin-capability, and user-friendliness make it the ideal tool for constructing a CI/CD pipeline.

Here are some of the advantages of Jenkins:

• Jenkins can be utilized as a simple continuous integration server or CD (Continuous delivery) hub for any project. 
• Jenkins can be useful with any operating system like Windows, Linux, MacOS, etc. 
• It also has an intuitive online interface for installation and configuration, along with real-time error checking and contextual guidance. Hence, provides a seamless set up.
• Jenkins is compatible with nearly every tool or plugins used in the CI/CD.
• Jenkins can also be extended by using various plugins. 
• Tasks can be easily distributed among various machines using Jenkins. So, the development, testing and deployment process can become faster across multiple machines. 

3. Building CI/CD Pipeline with Jenkins

3.1 Prerequisites

In order to proceed the instructions and scenarios in this article, you will need the following:

1. Git SCM. The most up-to-date 64-bit Windows version of Git (2.40.0) is used in this article.
2. A repository on Github that can be integrated with the Jenkins CI CD system.
3. Jenkins. 

Now, let’s first create a new github repository that we will use to build CI/CD pipelines on Jenkins. 

3.1.1 Preparing the GitHub Repository

1. Start up your browser and sign in to your GitHub profile and go to the repositories section.

2. Now, you may create a new repository by filling in the various  information such as Repository name, description, etc.  Some fields are optional so you can skip if you wish. You can also choose who can see your repository on the internet by turning the profile public or private. Once you are done filling the details, click on “Create Repository”.

3. Next, add a new document to the repository titled “Jenkins”. The Jenkins file is a text file that includes the description of a Jenkins Pipeline. This document belongs in the repository where you create the code.

Under your repository tab, select Add file —> Create new file.

4. Now, copy the script below and paste it into the Jenkins file.

A pipeline is a series of commands expressed in programming for continuous delivery.

The stage block comprises a number of stages in a pipeline, showing the Jenkins pipeline flow.

A step is a single job that performs a certain procedure at a predetermined time. A pipeline comprises a succession of stages.

pipeline {
    agent any

    stages {
        stage('Build') {
            steps {
                echo 'Building Example'
            }
        }
        stage('Test') {
            steps {
                echo 'Testing Example'
            }
        }
        stage('Deploy') {
            steps {
                echo 'Deploying Example'
            }
        }
    }
}

After creating the code, the file will appear much like the snapshot below.

5. Go to the end of the page and tap on the button “Commit new file”.

6. Lastly, copy the GitHub Repository URL. In order to do so, select the Code button and tap on the Copy icon right hand side of the given link. You will require the resultant URL for the Jenkins CI CD pipeline construction.

3.2 Creating a Jenkins CI/CD Pipeline

Several modifications and additions to the code are necessary when creating any new feature. There are various tasks such as changes in commitment, compilation, testing, packaging, etc. to be done in the intervals when the code is updated. 

Jenkins and similar automation platforms make these procedures quick and foolproof. In this section we will learn to create  CI/CD pipelines through Jenkins.

Step:1 Install Jenkins

First step is the Jenkins Installation. If you already have that in your pc, you can move on to the next step. 

• Here is the official link of Jenkins website: https://www.jenkins.io/
• To download the latest version of Jenkins, use this link: https://www.jenkins.io/download/#downloading-jenkins
• For installation guidelines, follow the steps given in this link: https://www.jenkins.io/doc/book/installing/
  • You can select the subsections as per your PC OS or other requirements. 
  • In case you have a windows operating system, you can directly use this link as well: https://www.jenkins.io/doc/book/installing/windows/
  • For Linux users, go through this link: https://www.jenkins.io/doc/book/installing/linux/ 
    • Here are the few commands for reference: 
      • sudo dnf install jenkins: To Install Jenkins
      • Use sudo systemctl enable Jenkins to enable the Jenkins services
      • sudo systemctl start jenkins : To start the Jenkins Services
      • Use sudo systemctl status jenkins to Check the status of the Jenkins Services
  • The Jenkins .WAR file can also be started on any OS with a version of JAVA supported with it. 

Step:2 Creating a Jenkins CI-CD Pipeline

1. Start a web browser, enter your Jenkins URL (http://localhost:8080/) into the address bar, and sign in. Use “admin” as a username. You will get the password from Drive C > ProgramData > Jenkins > .jenkins > secrets > initialAdminPassword file.

2. Create a new Jenkins Job: Select the New Item icon on the left side of the Jenkins Dashboard.

3. Type the title of the new pipeline. Choose the “Pipeline” template and give it the label as “pipelines-demo” for this article. The final step is to click OK. Here, 

“Pipeline” enables any developer to define the entire application lifecycle. 

Here, other available options are Freestyle Project and Multi-configuration project. 

• Jenkins Freestyle project allows developers to automate jobs like testing, packaging apps, creating apps, producing reports, etc. 
• With a Multi-configuration project, one can create a single job with many configurations. 

4. On the configuration screen, select the General tab, and then select the GitHub project box. The Project URL should then be updated to include the URL you obtained from the repository.

5. Select the “GitHub hook trigger for GITScm polling” in the Build Triggers section, as seen in the picture below.

Configure a Pipeline Job with SCMScript

6. If you are specifically configuring with the SCMScript, go to the Pipeline section and make the following selections/specifications there:

• In Definition box, select: Pipeline script from SCM
• SCM box, select: Git
• Repository URL box, enter: Your git repository URL
• In Branches to Build section, write “*/*” in the branch specifier field. 

7. After that, Write the file name “Jenkins” in the Script path field. Now, you complete the configurations. Click on the “Save” button. 

Configure a Pipeline Job through a Direct Script

6.  If you directly want to configure the pipelines without git, you can write the pipelines creation script by selecting the “Pipeline script” option in the “Definition” field. Checkout the below image for the reference.

After writing the script here, click on the “Save” button in the end. 

3.3 Configuring a Webhook in GitHub

Jenkins project requires a webhook to be set up in the GitHub repository before you execute a new job. In the event of a push to the repository, Jenkins server will be notified via this webhook.

Establish a Webhook by following the below steps: 

1. Open your GitHub repository’s “Settings” menu, then select the “Webhooks” tab. Choose “Add webhook” on the “Webhooks” page.

2. Then, add the Payload URL field to your Jenkins URL(/github-webhook/). For instance, HTTP://addJenkinsURL/github-webhook/.

Alter the property of Content type to “application/json” as well.

3. On “Which events would you like to trigger this webhook” selection, click the “Let me select individual events” option.

4. Click the “Pull request reviews”, “Pushes” and “Pull requests” boxes at the bottom of the page. When these conditions are met, GitHub will trigger the sending of a payload to Jenkins.

5. Add the webhook by pressing the button at the end of the page to validate the webhook.  If everything checked out with the webhook successfully, a message like the one in the snapshot would appear at the very top of the page.

3.4 Executing the Jenkins CI/CD Pipeline Job

How would you verify the functionality of the pipeline after you’ve set it up? You may see the current state of your pipeline with the use of Jenkins’ Pipeline Stage View add-on.

1. Click on the  “Build Now” option to begin the build procedure and create the initial build data. 

2. Put the pipeline through its paces by adding a dummy file to the repository. Simply navigate back to your GitHub repository and select Add File —> Create new file to start.

Create a new file with the name “demofile” and fill it with any demo text.

After you complete, select “Commit new file” in the page’s footer.

3. If you return to the status page for your Jenkins pipeline, you will find a new build entry with a single commit, as seen below. You will get this result in the case when you choose to Configure pipeline jobs with SCMScript.

4. If you are Configuring pipeline jobs through a direct script, below is the kind of result you’ll get when you click on the “Build now” option. Once you add or update any changes in GitHub, it will appear here. 

4. Conclusion

In this article, we gained an understanding of how to implement a Jenkins CI CD pipeline for the purpose of automating the software development lifecycle. As an added bonus, you now know how to utilize Jenkins to keep a CI/CD action chain in a software project running well.

Moreover, you may find a wealth of additional information on the Internet that can aid in your comprehension of pipelines. So, how likely are you to implement the Jenkins CI CD pipeline in your projects? Let us know in the comments!

The post CI/CD Implementation with Jenkins appeared first on TatvaSoft Blog.

docker’s main function is to create images and containers.

Kubernetes’ main function is to orchestrate containers.

One very confusing question I get sometimes is:

“Shall I just use Kubernetes now ??”

This is a wrong question because they do different things.

…

— Francesco (@FrancescoCiull4) May 24, 2021

1. What is Docker? 

Docker, a commercialized containerization platform and a container runtime, is used to create, launch, and execute containers. It uses a client server architecture and employs a single API for both automation and basic instructions. Nothing about this should come as a surprise, as it was essential in popularizing the idea of containers, which in turn sparked the development of tools like Kubernetes.

Docker is a tool that makes it easier to create, deploy, and run applications using containers. Containers allow a developer to package up an application with all the parts it needs, such as libraries and other dependencies, and ship it all out as one package.

— Simon (@simonholdorf) January 7, 2023

Docker also has a toolkit that is often used to bundle apps into immutable container images. This is done by making a Dockerfile and then running the commands needed to make the container image using the Docker server.

While developers are not required to use Docker to work with containers, it does make the process simpler. These container images may then be used on any container-friendly platform.

Let’s take a look at basic Docker architecture: 

1.1 Features of Docker 

Open-Source Platform: The freedom to pick and choose among available technologies is a key feature of an open-source platform. The Docker engine might be helpful for solo engineers that need a minimal, clutter-free testing environment.

Accelerated and Effective Life Cycle Development: Docker’s main goal is to speed up the software development process by eliminating repetitive, and mundane configuration tasks. The objective is to have your apps be lightweight, easy to build, and simple to work on.

Isolation and Safety: Docker’s built-in Security Management functionality stores sensitive data within the cluster itself. Docker containers offer a high degree of isolation across programs, keeping them from influencing or impacting one another.

Simple Application Delivery: The ability to quickly and easily set up the system is among Docker’s most important characteristics. Due to this feature, entering codes is simple and quick.

Reduction in Size: Docker provides a lot of flexibility for cutting down on app size during development. The idea is that by using containers, the operating system footprint may be minimized.

1.2 Key Benefits of Using Docker

• Send and receive container requests over a proxy.
• Manage the entire container lifecycle. 
• Keep tabs on container activities.
• It does not provide containers unrestricted access to all of your resources.
• For packaging, running, and creating container images, docker build and docker compose are used. 
• Data may be pushed to and pulled from image registries.

1.3 Rise of the Containerization with Docker

Limiting ecosystems is not new, and Docker isn’t the only containerization platform out there, but it has become the de facto standard in recent years. One of Docker’s key components is the Docker Engine, a virtual machine. Any development computer may be used to create and execute containers, and a container registry, such as Docker Hub or Azure Container Registry, can be used to store or distribute container images.

Handling them becomes more complicated when applications expand to use several containers hosted on different hosts. Docker is an open standard for delivering software in containers, but the associated complexity may quickly mount up.

When dealing with a large number of containers, how can you ensure that they are all scheduled and delivered at the right times? How does communication occur between the various containers in your app? Is there a method for efficiently increasing the number of running container instances? Let’s see if Kubernetes can answer these scenarios!

2. What is Kubernetes? 

When it comes to deploying and managing containers or containerized applications, Kubernetes is one of the best open-source solutions. K8s(Kubernetes) tools, services, and support are widely available. According to the CNCF (Cloud native computing foundation), 96% of the organizations are either  using or evaluating K8s. 

In the Kubernetes cluster, a special container acts as the control plane, allocating tasks to the multiple containers (the worker nodes). The master node is responsible for deciding where apps will be hosted and how they will be organized and orchestrated. 

Kubernetes simplifies the process of locating and managing the many components of an application by clustering them together. This makes it possible to manage large numbers of containers over their entire lifecycles. K8s has a Container Runtime Interface (CRI) plugin that enables the use of a wide variety of container runtimes. There is no need to recompile the cluster components while using CRI. 

Let’s take a look at the Kubernetes cluster. 

2.1 Features of Kubernetes

Bin Packing Automation:
With Kubernetes, the app can be prepared automatically, and the containers can be scheduled according to their needs and the resources available, without compromising on availability. Kubernetes strikes an equilibrium between essential and best-effort activities to guarantee full resource usage and reduce cost.

Orchestration of Data Storage: Kubernetes is equipped with a number of storage management options out of the box. This function enables the automated installation of any storage solution, whether it be local storage, a public cloud provider like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), or any other network storage system.

Load Balancing and Service Discovery: Kubernetes takes care of networking and communicating for you by dynamically assigning IP addresses to containers and creating a single DNS domain for a group of containers to load-balance information within the cluster.

Manage Confidential Information and Settings: Kubernetes allows you to alter the application’s settings and roll out new secrets without having to recompile your image or risk exposing sensitive information in your stack’s settings.

Self-Healing: Kubernetes’s functionality plays the role of a superhero. Any failed containers are automatically rebooted. If a node fails, the containers it holds are reallocated to other nodes. If containers fail to react to Kubernetes’s user-defined check ups, access is restricted until the containers are operational.

2.2 Key Benefits of Using Kubernetes 

• Container deployment on a cluster of computers is planned and executed automatically.
• It uses load balancing and makes a container accessible online.

The Kubernetes API makes it easy to do client-side load balancing. The Endpoints Load Balancer is a great example. https://t.co/jPL4qz7sMQ pic.twitter.com/oJxTbk7Wzx

— Kelsey Hightower (@kelseyhightower) November 6, 2016

• New containers are started up mechanically to deal with large loads.
• Self-repair is a feature of this item.
• It updates applications and checks for problems in their functioning.
• The Storage orchestration is fully automated.
• It allows for dynamic volume provisioning.

2.2 Container Orchestration with Kubernetes

With Kubernetes, you can manage a group of virtual machines and make them execute containers depending on the resources each container needs. Kubernetes’ primary functional unit is the pod, which is a collection of containers. You can control the lifetime of these containers and pods to maintain your apps online at any size.

3. Kubernetes vs Docker: Key Comparison

4. Use Cases of Docker

4.1 Reduce IT/Infrastructure Costs

When working with virtual devices, a full copy of the guest OS must be made. Fortunately, Docker doesn’t have this problem. While using Docker, you can run more applications with less infrastructure, and resource use can be optimized more effectively.

For instance, to save money on data storage, development teams might centralize their operations on a single server. Docker’s great scalability also lets you deploy resources as needed and dynamically grow the underlying infrastructure to meet fluctuating demands.

Simply said, Docker increases production, which implies you may save money by not having to hire dedicated developers as you would in a more conventional setting. 

4.2 Multi-Environment Standardization

Docker gives everyone in the pipeline access to the same settings as those in production. Think of a software development team that is changing over time. Each member of the team is responsible for updating and installing the operating system, databases, node, yarn, etc. for the newest team member. Just getting the machines set up might take a few days.

For instance, you will require to acquire two variants of a library if you utilize multiple variations in multiple apps. In particular, before running these scripts, you should set any necessary custom environment variables. So, what happens if you make some last-minute modifications to dependencies in production but neglect to do it in production?

Docker creates a container with all the necessary tools and guarantees that there will be no clashes between them. In addition, you may keep tabs on previously unnoticed environmental disruptors. Throughout the CI/CD process, Docker ensures that containers perform consistently by standardizing the environment.

4.3 Speed Up Your CI/CD Pipeline Deployments

Containers, being much more compact and more lightweight than monolithic apps, may be activated in a matter of seconds. Containers in CI/CD pipelines allow for lightning-fast code deployment and easy, rapid modifications to codebases and libraries.

However, keep in mind that prolonged build durations might impede CI/CD rollouts. This arises because each time the CI/CD pipeline is run, it must pull all of its dependencies from fresh. Docker’s built-in cache layer, however, makes it simple to work around this build problem. Nevertheless, it is inaccessible from remote runner computers as it only functions on local workstations.

4.4 Isolated App Infrastructure

Docker’s isolated application architecture is a major benefit. You may forget about dependency problems because all prerequisites are included in the container’s deployment. Several applications of varying operating systems, platforms, and versions can be deployed to and run simultaneously on a single or numerous computers. Imagine two servers running incompatible versions of the same program. When these servers are operated in their own containers, dependency problems may be avoided.

Docker also provides an SSH server per container, which may be used for automation and troubleshooting. As each provider runs in its own separate container, it’s simple to track everything happening within that container and spot any problems right away. As a consequence, you may run an immutable infrastructure and reduce the frequency of infrastructure-related breakdowns.

4.5 Multi-Cloud or Hybrid Cloud Applications

Because of Docker’s portability, containers may be moved from one server or cloud to another with minimum reconfiguration.

Teams utilizing multi-cloud or hybrid cloud infrastructures may release their applications to any cloud or hybrid cloud environment by packaging them once leveraging containers. They can also quickly relocate apps across clouds or back onto a company’s own servers.

4.6 Microservices-Based Apps

Docker containers are ideally suited for microservices-architected applications. Because of orchestration technologies like Docker Swarm and Kubernetes, developers may launch each microservice in its own container and then combine the containers to construct an entire application.

Theoretically, you can deploy microservices within VMs or bare-metal servers as well. Nevertheless, containers are more suited to microservices apps due to their minimal resource usage and rapid start times, which allow individual microservices to be deployed and modified independently.

More Interesting Read: Microservices Best Practices

5. Use Cases of Kubernetes

5.1 Container Orchestration

Orchestration of containers streamlines their rollout, administration, scalability, and networking. Orchestration of containers may be employed in any setting wherein containers are deployed. The same application may be deployed to several settings with this method, saving you time and effort in the designing process. Storage, networking, and protection may all be more easily orchestrated when microservices are deployed in containers.

To launch and control containerized operations, Kubernetes is the go-to container orchestration technology. Kubernetes’s straightforward configuration syntax makes it suitable for managing containerized apps throughout host clusters.

5.2 Large Scale App Development

Kubernetes is capable of managing huge applications because to its declarative setup and automation features. Developers can build up the system with fewer interruptions thanks to functions like horizontal pod scalability and load balancing. Kubernetes keeps things operating smoothly even when unexpected events occur, such spikes in traffic or broken hardware.

Establishing the environment, including IPs, networks, and tools is a difficulty for developers working on large-scale apps. To address this issue, several platforms have begun using Kubernetes, including Glimpse.

Cluster monitoring in Glimpse is handled by a combination of Kubernetes and cloud services including Kube Prometheus Stack, Tiller, and EFK Stack.

5.3 Hybrid and Multi-Cloud Deployments

Several cloud solutions can be integrated during development thanks to hybrid and multi-cloud infrastructure architectures. By utilizing many clouds, businesses may lessen their reliance on any one provider and boost their overall flexibility and application performance.

Application mobility is made easier with Kubernetes in hybrid and multi-cloud setups. Because it works in every setting, it doesn’t require any apps to be written specifically for any one platform.

Services, ingress controllers, and volumes are all Kubernetes ideas that help to hide the underlying system. Kubernetes is an excellent answer to the problem of scalability in a multi-cloud setting because of its in-built auto-healing and fault tolerance.

5.4 CI/CD Software Development

The software development process may be automated with the help of Continuous Integration and Continuous Delivery. Automation and rapid iteration are at the heart of the principles around which CI/CD pipelines are built.

The process of CI/CD pipelines involves DevOps technologies. Together with the Jenkins automation server and Docker, Kubernetes has become widely used as the container orchestrator of preference.

The pipeline will be able to make use of Kubernetes’ automation and resources control features, among others, if a CI/CD process is established.

5.5 Lift and Shift from Servers to Cloud

This is a regular phenomenon in the modern world, as more and more programs move from local servers to the cloud. In a traditional data center, we get an application running on physical servers. Because of its impracticality or expense, it has been chosen to host it in the cloud, either on a Virtual Machine or in large pods within Kubernetes. Moving it to large K8s pods isn’t a cloud-native strategy, but it can serve as a temporary solution. 

To begin, a large application running on-premises is migrated to a similar application running in Kubernetes. After that, it’s broken down into its constituent parts and becomes a standard cloud native program. “Lift and shift” describes this approach, and it’s a perfect example of where Kubernetes shines.

5.6 Cloud-Native Network Functions (CNF)

Large telecommunications firms encountered an issue a few years ago. Its network services relied on components from specialist hardware vendors, such firewalls and load balancers. Naturally, this made them reliant on the hardware suppliers and limited their maneuverability. Operators were tasked with upgrading their current devices to provide new features. When a firmware upgrade wasn’t an option, new hardware was required. 

To combat this shortcoming, telecommunications companies have decided to use network function virtualization(NFV) using Virtual Machines and OpenStack.

6. Kubernetes vs Docker: The Conclusion

Despite their differences, Kubernetes and Docker are a formidable pair. Docker is the containerization element, allowing programmers to quickly and easily run containers and apps in their own contained environments using the command line. This allows developers to deploy their code throughout their infrastructure without worrying about incompatibilities. As long as the program can be tested on a single node, it should be able to run on any number of nodes in production.

Kubernetes orchestrates Docker containers, launching them remotely within IT settings and arranging them for when they need spikes. Kubernetes is a container orchestration tool that also facilitates load balancing, self-healing, and robotic deployments and rollbacks. Also, it is quite user-friendly due to its graphical user interface.

However, Kubernetes might be a good option for firms that plan to scale their infrastructure down the road. For those already familiar with Docker, Kubernetes simplifies the transition to scale by reusing current containers and workloads.

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MEAN stack is a set of JavaScript-based tools used for application development. MERN Stack is a popular replacement for MEAN Stack, in which classic frontend framework Angular is substituted with React.js library. 

Not sure which one to choose from the MEAN stack vs MERN stack? Well, to choose the best technology stacks for your company, you must be savvy enough to weigh the merits of MEAN stack vs MERN stack. Therefore, this article provides a detailed comparison of the two stacks to assist you in making the best decision for your company.

1. What is MEAN Stack?

The MEAN Stack is the most widely useful technology stack for building apps for both web and mobile platforms, especially by full-stack developers. It also uses multiple third-party libraries and tools for large-scale projects.

MEAN stack leads to faster application development as well as the deployment. Using MEAN stack, one can 

• Create scalable apps for cloud deployment
• Simplify deployment process with a built in web server
• Manage large amount of data

The MEAN stack consists of four significant elements: MongoDB, Express.js, Angular, and Node.js.

2. What is MERN Stack?

A popular alternative to the MEAN Stack is the MERN Technology Stack, which swaps out the cumbersome and time-consuming Angular in favor of the more straightforward and simple React.js in any software development.

MongoDB, Express.js, React.js, and Node.js form the “MERN” acronym, which describes this combination of technologies. Let’s examine the functions of each of these parts in further detail.

3. MEAN Stack vs MERN Stack

Let’s first understand the architecture of both the stacks. 

3.1 MEAN Stack Architecture

The MEAN architecture was created to drastically simplify the process of creating a JavaScript-based web application capable of working with JSON.

Angular.js as a Front-end Framework

Angular, which calls itself a “JavaScript MVW Framework”, is classically used in the MEAN stack.

Compared to manually coding a website in static HTML and JavaScript, Angular makes it much easier to construct dynamic, interactive online experiences by extending your HTML tags with information (or jQuery).

Form authentication, localization, and two-way communication with your back-end service are key features of Angular. Here is the Quora answer from Google’s UX Engineer on usefulness of Angular in the MEAN Stack.

3.2 MERN Stack Architecture

With the MERN architecture, you can quickly and simply build a full front-to-back-to-database stack just in JavaScript and JSON.

React.js as a Front-end Library

React.js, the expressive JavaScript library for developing interactive HTML client-side apps, is the crown jewel of the MERN stack. Using React, you can construct sophisticated user interfaces with elementary building blocks, bind them to server-side data, and output the result as HTML.

When it comes to domain-specific, data-driven UI, React shines. It also includes all the features you’d want from a professional web framework, such as excellent coverage for forms, error detection, events, listings, and many more.

3.3 MEAN and MERN Stack Common Architectural Components

Express.js and Node.js Server Tier

Express.js is a web framework that you can deploy on a Node.js server. It describes itself as a “rapid, unbiased, simple web framework for Node.js,” which it is.

Express has strong techniques for handling HTTP requests, responses, and URL routing, which is the activity of linking an arriving URL with a server operation. Your Angular.js app’s front end may communicate with the backend Express.js services using XML HTTP requests (XHRs), GETs, and POSTs.

Those methods then access and modify the MongoDB database utilizing the Node.js drivers through callbacks or using promises.

MongoDB Database Tier

You’ll need a database that’s as straightforward to deal with as Angular or React, Express, and Node if the app keeps personal profiles, data, remarks, transfers, events, and so on.

Here is when MongoDB enters through: JSON documents may be sent to the Express.js servers after being produced by the Angular.js or React front end also validated and (if found to be correct) saved in MongoDB.

4. Tabular Comparison: MEAN Stack vs MERN Stack

5. When to Use MEAN Stack? 

Display tier (Angular.js or Angular), application tier (Express.js and Node.js), and database tier (MongoDB) are the three components that makeup MEAN’s take on the classic three-tier JavaScript stack structure.

You should give MEAN significant consideration if you’re developing a JavaScript project, especially in Node.js and angular.

While the MongoDB Query Language (MQL) is expressed in JSON, the command line interface (CLI) is a JavaScript translator, and the data itself is stored in a JSON-like format (BSON, a binary JSON extension). MongoDB is a JavaScript/JSON data repository that also supports robust native Node.js drivers and is built for horizontal scalability, and offers sophisticated capabilities like indexing and searching deep into JSON documents. Using MongoDB Atlas, MongoDB developers develop the cloud-native database as a service, cloud-based application development has never been simpler.

MEAN is the best stack for developing Node.js apps, whether you’re making a microservice, a basic web app, or an API with maximum bandwidth.

6. When to Use MERN Stack?

Since the MERN Stack uses JavaScript, there is no requirement for the programmer to transition between different contexts. When it comes to abstracting the UI layer, React js library in the MERN Stack, excels. To facilitate the straightforward development fostered by the MVC architecture design, MERN provides a library with an easily accessible interface that allows rapid code execution. Big, reactive JSON data that can move easily between the front and back ends of an application is ideal since it can be easily managed and updated.

MERN is a general-purpose web stack, so you may use it to create anything you choose; however, it shines in scenarios that need significant use of JSON, are native to the cloud, and have interactive web interfaces.

Project management, data aggregation, to-do applications and calendars, engaging forums and social goods, and anything else you can think of are all examples.

7. Conclusion

Due to their tight relationship, MEAN and MERN stacks make it difficult to pick only one for web development. The foundations and competencies of both technologies are dependable. Yet, MEAN is more useful for large-scale apps, whereas MERN for faster development of smaller apps due to structural differences. Consequently, it is important to pick from the MEAN stack vs MERN stack based on the requirements of your application.

The post MEAN Stack vs MERN Stack: Which Stack to Choose? appeared first on TatvaSoft Blog.

Before we proceed further, let us first know what exactly Infrastructure automation means and why it is important.

1. What is Infrastructure Automation?

The process of Infrastructure automation reduces the requirement for human interaction with IT systems as it creates functions that can be used by other software or on command. Having an automated infrastructure allows repeatability so that developers can quickly set up environments where a particular environment consists of a single objective: user acceptance testing, integration development, or production.  So, contemporary architectures, like microservices and monolithic architecture, majorly benefit from infrastructure-level automation. 

This concept can be instilled to make processes automated and easily control IT elements including storage, development, servers, operating network, network elements, and more. The main aim of this is to improve the efficiency of an organization’s IT operations and staff. 

Amazon ECR, Docker hub, JFrog Container registries, and many more tools are useful part of Infrastructure automation. 

2. Why is it Important?

The majority of IT organizations face issues when it comes to growing infrastructure complexity and size. With limited time and resources, every IT team often struggles in keeping pace with the growth, and this results in delayed updates, resource delivery, and patching. For this, if automation is applied to common and repetitive tasks  such as configuring, provisioning, deploying, and decommissioning processes, it can easily simplify the scale of all the operations by enabling businesses to regain control over and visibility into their infrastructure.

Infrastructure automation is a process that comes with a lot of benefits, and some of those are – 

2.1 Provisioning:

Infrastructure automation is an approach that can help organizations reduce provisioning time for new networking & VMs from weeks to minutes. And this process is very much valuable in recent times’ multi-cloud hybrid IT environments as nowadays orchestration and automation work hand in hand to ensure smooth business operations and product deployment instead of workload placement.

2.2 Capacity Planning:

Another advantage of applying infrastructure automation in an IT firm is that it helps in under-and over-provisioning performance organization-wide. This means that in every organization, some kind of waste can occur due to a lack of professional standards in workloads or project deployment. In such cases, infrastructure automation can help in reducing inconsistencies by eliminating the complexity and increasing the standardization of processes in the organization. Applying infrastructure automation can help in identifying the incorrect provisioning areas that are impacting workload deployments and resource allocation processes. 

2.3 Cost:

The person who is managing an IT budget keeps a compulsive eye on every cent going out. But what if you lose visibility on how much cost is hitting your budget and where it’s going? This problem relates to cloud resource consumption where an Environment as a Service infrastructure automation tool having features like Torque, can help manage and eliminate runaway costs. 

2.4 Reduce Human Error:

Automating Infrastructure reduces vulnerabilities associated with human error during manual provisioning and allows you to focus on core development rather than investing efforts in repetitive processes.

2.5 Business Risk:

Some amount of business risk comes from security deficiencies. It is hard to maintain security and compliance at the same time as it requires a lot of time and effort, is prone to error, and standards can change over time. This is where your blueprint environment is helpful. With this, IT teams can make sure that software developers spun up the cloud environments who need them.

2.6 Improving Workflows:

Infrastructure Automation allows for repeatability and accuracy while performing IT provisioning processes. Operations teams are required to set the expected requirements for the provisioning of infrastructure and automation tools and execute the tasks when those conditions are met.

2.7 Inability to Scale:

Several companies find it hard to scale for some reason. Bottlenecks in environment provisioning can lead to such problems, but it is also caused by fragile toolchains resulting from disparate tools that are being used by each pipeline. This is where infrastructure automation helps IT teams to simplify and improve DevOps toolchains and reduce the burden of troubleshooting with built-in troubleshooting and validation features.

Several Other Benefits Include, 

• Modifications to the system are common, without any stress for IT staff members or users, the system can do this.
• Users have the ability to manage, define, and provision the resources that they need, without needing IT staff to do it for them.
• IT infrastructure allows you to change rather than being a constraint or an obstacle.
• IT staff invest a huge amount of time in valuable things that engage their abilities to perform repetitive tasks.
• Solutions to problems are proven through testing and implementing them, rather than by only discussing them in documents and meetings.

3. Which IT Infrastructure Processes can be Automated?

Here are the IT infrastructure processes that can be automated for tech companies – 

4. Challenges in Implementing Infrastructure Automation

As we all know, the demand for automated infrastructure management is increasing as it is now becoming a necessity for every organization. With time, more and more IT organizations have started adopting new techniques and they’re getting used to them but this doesn’t mean they don’t face any challenges instead they started facing more challenges. 

Basically, the introduction of new technologies in any organization for higher productivity and smoother functioning sometimes does not make performance better. And this has led to slower processing as the new technology requires time to optimize, understand, and configure the IT infrastructure. Besides this, there are other issues that companies face while trying to adopt infrastructure automation and they are – 

4.1 Outdated Infrastructure

When it comes to working with the productive concepts or following practices of the latest technologies like DevOps, automation is the key. In such cases, an outdated infrastructure that has little automation or no self-service can never be efficient. The reason behind it is that infrastructure automation requires constant upgrades and improvements to avoid any type of challenges. For good automation, strategies take shape when an IT organization is equally reliable between pre-production and real environments, the firm is resilient to failure, and has quick access to its processes.

4.2 Culture

Every IT organization requires a new culture but for that learning and disruption are important requirements. This means that when the employees of the organization are not in the right mindset that it can lead to project failure. The main reason behind it is that the process of optimizing infrastructures can slow down the operational processes and development if the mindset of the entire team is not the same. This means that adapting to advanced and new technology is very difficult for employees who don’t have the right technical background and mindset for it. 

Therefore, organizations first need to resolve that issue and help employees enhance their skills before adopting automation which comes with the latest technologies. 

4.3 Tools and Apps

One of the major challenges faced by IT organizations when it comes to automation infrastructure is modifying an application. It requires you to invest a lot of time and effort to make changes to an application as it is a challenging task and the reason is the gap between software developers and business users. In certain cases, users are not aware of the complexity that comes with the back-end integration process and they consider that a single app helps them to overcome all their problems. On the contrary, developers don’t follow a systematic view of the business and due to this reason they might fail to understand why a quick-fix tool won’t perform. But if the developers and users tend to use an unauthorized tool, it can make the situation even worse and the process more complex.

4.4 Communication and Processes

Infrastructure automation technology such as DevOps is all about other departments working with each other simultaneously. This means that in an organization, all the team members must be on the same page. Besides this, provisioning the resources can also take a lot of time when the communications are outdated and the test processes are manually built. 

4.5 Budgeting

The last challenge that companies face while implementing infrastructure automation is budgeting. In any organization, capital and operational expenses are always interconnected. When companies adopt automation, they begin to scale up their infrastructure which adds expenses to the existing infrastructure which can not be quite budget-friendly for all the companies.

5. How does Infrastructure Automation Work in Any Organization?

Infrastructure automation helps organizations to deliver repeatability and predictability to the processes that are used for handling the IT workload configuration. It enables the IT department to meet their service level agreements (SLAs) by freeing up valuable IT resources and reducing complexity. This helps organizations focus on business value rather than low-level infrastructure management. And this can eventually help companies to increase uptime and accelerate the consistency in the deployment of new workloads.

Besides this, as infrastructures grow in any organization, automation enables the teams of the company to manage complex environments with the existing staff. This means that infrastructure automation streamlines ongoing operations like user access management, network management, storage administration, IMAC (install, move, add, change) of workloads, data administration, troubleshooting, deploying application workloads, and debugging. In addition to this, infrastructure automation is a concept that enables businesses to take advantage of multi-cloud provisioning and self-service with consistency across different clouds.

There are 3 main phases of infrastructure automation, that are:

5.1 Adopt and Establish a Provisioning Workflow

Manually provisioning and updating infrastructure more than once a day from different sources using a variety of workflows is like inviting chaos. At times, teams might face difficulty while sharing a view of the organization’s infrastructure and collaborating. So to overcome this problem, businesses must adopt and establish infrastructure provisioning workflows that are consistent for any cloud, private data center, or service.

5.2 Operate at Scale and Optimize

Just having a standardized workflow is not enough, businesses must continuously optimize their infrastructure and operate at scale to reap the benefits of infrastructure automation. For this, you need to extend automated and self-service infrastructure provisioning to programmers with proper policies in place to remediate policy violations.

5.3 Standardize the Workflow

To standardize the provisioning workflow across your organization, make sure that it offers all the required security and maximizes efficiency. Years ago, we used a ticket-based approach to infrastructure provisioning making IT a gatekeeper. That time they act as infrastructure governors but also create bottlenecks and restrict developer productivity. So to avoid this, organizations must have a standardized workflow that reduces redundant work and includes proper guardrails for operational consistency and security.

6. Well-known Infrastructure Automation Tools

Here are the top infrastructure automation tools that can be used by companies to automate their infrastructure and smoothen day-to-day business. 

6.1 AWS CloudFormation

AWS CloudFormation is known as the best cloud-based infrastructure automation tool. This tool enables businesses to make their working model easy & smooth. Besides this, it also helps in setting up the AWS resources with the use of infrastructure as code. This tool helps in monitoring and managing resources & applications on AWS which helps in saving time and effort. It also provisions and configures resources with the use of templates that helps in creating, updating, and deleting stacks. 

If you’re using AWS CloudFormation to build infrastructure as code make sure to consider some factors such as:

• To ensure the AWS CloudFormation templates are working as expected, test them periodically. 
• Automate AWS CloudFormation testing with TaskCat.
• Create modular templates.
• Use the same names for common parameters.
• Utilize existing repositories as submodules.
• Make use of parameters to identify paths to your external assets.
• Use an integrated development environment with linting.

Basically, AWS CloudFormation enables IT organizations to scale their infrastructures globally. It also meets compliance, safety, and configuration regulations for all AWS regions and accounts. 

Pros:

• While deploying new resources, you can easily apply changes to your current resources with AWS CloudFormation.
• AWS CloudFormation helps to improve the overall security of the AWS environment by eliminating the risk of human errors that the cloud turns into breaches.
• You can easily apply the same configuration repeatedly using CloudFormation templates to define and deploy AWS resources.
• While creating an AWS CloudFormation template to manage AWS resources, you can deploy multiple instances of the same resources using a single template.
• AWS CloudFormation allows you to track changes without looking through logs.

Cons:

• AWS CloudFormation might not work well sometimes for developers as there is a size limit of 51MB on the stacks.
• Nested stacks are difficult to manage and implement in the AWS Cloud environment.
• The modularization in cloud formation is not mature as compared to other similar tools.

6.2 AWS Pipelines

AWS CodePipeline is one of the most popular infrastructure automation solutions in the market that enables IT organizations to reliably process and move data between various AWS storage services and compute alongside on-premises data sources. 

How does AWS CodePipeline work?

AWS CodePipeline is a fully managed continuous delivery service used to determine the data flow between two or more data sources. It allows you to automate your release pipelines for more reliable application and infrastructure updates.

Have a look at some best practices for CodePipeline resources:

• Try using authentication and encryption for the source repositories that allow you to connect to your pipelines. 
• You can also integrate code pipelines with third-party tools such as GitHub and Jenkins and then use them efficiently.
• You can use logging features available in AWS to track user actions. 
• Install Jenkins on the Amazon EC2 instance and activate a separate EC2 profile.  

Pros: 

• You can bring your own build tools and programming runtimes.
• It is not required to pay for idle build server capacity.
• No need to set up, update, and manage software and build servers.
• It allows you to rapidly release new features and automates your software release process.
• It is easy to transform the data and automate the moments.

Cons:

• The overall usability and console UI is poor.
• It has to be composed of multiple AWS services which makes it extremely complex and overly dependent on AWS.
• Your infrastructure is entirely dependent on AWS.

6.3 Azure DevOps

Azure DevOps comes with a support for collaborative culture. It offers a set of processes that has the capability to bring together project managers, developers, and contributors to create software. It also enables IT organizations to develop and improve products at a faster rate in comparison to traditional software development approaches. In addition to this, with the help of Azure DevOps, organizations working on the cloud or on-premises can make the process smooth as Azure DevOps offers integrated features such as:

Azure Boards: It delivers value to your users using proven agile tools to discuss, plan, and track work across various teams.

Pipelines: You can easily build, test, and deploy applications with CI/CD that work with any language, platform, and cloud as well as Azure pipelines allow you to connect to GitHub and deploy continuously.

Kubernetes Service: It helps you to ship containerized applications faster and operate them easily using a fully managed Kubernetes service.

Monitor: Using Azure monitor, you’ll get full observability into your network, applications, and infrastructure.

Azure Test Plans: You can effectively ship and test with an exploratory test toolkit.

Pros:

• It allows you to run containerized web applications on various operating systems such as Linux and Windows.
• It offers excellent features such as reduced complexity, better product delivery, faster issue resolutions, and much more.
• Azure DevOps allows you to use automation so that you can build faster and more efficiently.
• It makes sure that the application quality is maintained and reliably delivered at a more rapid pace.
• Manage and operate your infrastructure efficiently with reduced risks.

Cons: 

• As a complex technology, the learning curve of Azure DevOps is steep.
• The infrastructure cost is expensive for a DevOps environment.
• It comes with unrealistic goals and added complexity.

6.4 Jenkins

Jenkins is a leading open-source automation server that offers numerous plugins to support building, deploying, and automating any project. If an organization wants to use this tool, it needs to be associated with a version control system such as SVN or GitHub. This means that when there is a new code to be pushed in the repository, this server will be used to create and test the code and notify the IT team about the changes made or the result received. 

Pros:

• As an open-source tool, it can be freely and easily installed.
• It offers 100+ plugins which ease your task and it also allows you to share it with the community.
• It is built with Java, so it can be easily portable to all major platforms such as Windows UNIX, and MacOS which is great.
• Enhances the user interface by incorporating user inputs.
• It can easily distribute work across various machines for faster development, testing, and deployment.

Cons:

• Jenkins uses a single server architecture which limits the usage of resources and causes performance issues.
• There is a lack of federation which creates a large number of standalone Jenkins servers that are hard to manage.
• Jenkins plugins have dependencies that increase the management burden.

6.5 GitHub Actions

Another popular infrastructure automation tool is GitHub Actions. This is a really useful action to use along with other actions that add or modify files to your repositories. This tool offers a great way to set up an organization’s continuous integration pipelines. This means that with the help of GitHub Actions, different types of integrations and workflows are available that can help in setting up a CI/CD pipeline. This tool can also be useful on enterprise and public GitHub accounts. In addition, this is a concept where the GitHub runners enable the organizations to set up a CI execution environment. GitHub Actions allows developers to automate their workflows across various problems, pull requests, and more. It brings automation directly into the SDLC on GitHub through event-driven triggers.

Pros:

• It has the ability to implement automations right in your repository that you can easily integrate to your preferred tools.
• It supports various operating systems such as MacOS, Windows, and Ubuntu Linux so that it becomes easy for you to build, test, and deploy code directly to the OS of your choice.
• GitHub Actions brings CI/CD directly to the GitHub flow and allows developers to create their own custom CI/CD workflows.
• Easily build and test code as well as automate build and test workflows.
• You can freely use all public repositories.

Cons:

• GitHub actions are hard to implement and debug.
• You cannot run extremely heavy jobs on GitHub actions because its maximum execution time per job is 6 hours.
• It does not provide proper and efficient testing services.

6.6 Docker

Docker is a tool that works on the process-level virtualization approach which helps in creating isolated environments for applications known as containers. These containers are shipped to a different server without any modification to the application and this is why Docker is considered the next step in virtualization. In addition to this, Docker comes with a huge developer community, and with time it is gaining popularity among DevOps developers in cloud computing.

Pros:

• Docker environment is highly secure and isolated from each other, making a clean app removal.
• The cost is optimized as it allows you to significantly reduce infrastructure costs.
• Developers can run applications in a consistent environment from design and development to support and maintenance.
• Developers have the ability to create containers for every process and deploy them instantly.
• Docker is capable of increasing the speed and efficiency of the CL/CD pipeline and increasing productivity.

Cons:

• Large amount of containers in Docker requires a lot of time to process which makes the process time-consuming.
• Docker is not suitable for applications that require a  rich graphics user interface.
• There is no cross-platform compatibility.

6.7 Kubernetes Operators

Kubernetes is a popular container orchestration tool that enables organizations to automate and manage the web application with the use of custom user-defined logic. It is specially designed for automation and can be used with the GitOps methodologies to take complete benefit of the automated Kubernetes deployments. Those who tend to run workloads on Kubernetes might use automation to take care of repeatable tasks.

Pros:

• It is simple, flexible and has the ability to automate many functions simultaneously.
• Operators allow you to use custom resources to manage applications and their components.
• It offers primitives and basic commands that operators can use to define complex actions.
• Kubernetes operations provide more flexibility and ensure scalability.
• Kubernetes services provides load balancing to simplify the process of managing containers on multiple hosts.

Cons:

• There are constant innovations and numerous additions which makes the landscape confusing for new users.
• It is slow, complicating, and difficult to manage.
• It has a steep learning curve.

6.8 Terraform

Terraform is one of the most popular cloud-agnostic infrastructure provisioning tools. It is a tool that is written in Go and is created by Hashicorp. This tool supports all private and public cloud infrastructure provisioning. It works well when it comes to maintaining the state of any organization’s infrastructure as it uses the concept called state files. Automation of Terraform comes in various forms and to varying degrees. 

Pros:

• Terraform allows you to store local variables like passwords and cloud tokens.
• You can edit, build, and version your infrastructure using various coding techniques.
• Easily define your application and activate configuration files.
• Support various cloud solutions.
• You can easily find providers and modules to use with a private registry.

Cons:

• You cannot use revert function or incorrect changes to the resources.
• Security and collaboration features are costly and only included in the expensive enterprise plans.
• It does not support plans using Terraform’s Remote State.

6.9 Ansible

Ansible is an agentless configuration management and orchestration tool. The configuration modules in this tool are known as Playbooks which are written in YAML format. These modules are easy to write in comparison to other configuration management tools available in the market. 

Pros:

• No technical skills are required to easily set up and use Ansible.
• You can orchestrate the entire software environment no matter on which platform it is deployed.
• You can easily automate the implementation of applications that are internally generated to your production programs.
• Automates a variety of devices and systems such as databases, firewalls, networks, and much more.
• It allows you to model complex IT workflows and create infrastructure components easily.

Cons:

• Ansible simplifies sequential tasks and does not track dependencies.
• It comes with a lot of issues related to performance, debugging, control flow, and complex data structure.
• Insufficient user interface and lack of notion of state.

7. Conclusion 

As seen in this blog, infrastructure automation tools are really important for  IT orchestration, efficiency, and an organization’s digital transformation as well as it is highly required in IT organizations to enable teams to manage tasks easily and efficiently. But when any IT organization decides to implement infrastructure automation, it is very important to select the right set of tools. Those tools can help automate monotonous tasks and enhance the efficiency level of the team members. 

If you’re still confused about choosing the right infrastructure tools then make sure to consider some major factors such as skillset, cost, usage, and functionality. It is not necessary that one tool can fit all the requirements of your organization. Sometimes you may need multiple tools to fulfill your requirements. So the selection of tool sets must be as per the team’s requirements so that it can effectively ship and test with an exploratory test toolkit.

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1. What is a Monolith?

Monolithic Application, also referred as “Monolith”, is an application that is built using a single code base that contains all the functionalities. This single codebase includes all the components such as backend code, frontend code, configuration files, and everything. These apps are primarily developed to perform a number of interconnected functions. 

Monolithic architecture is a traditional approach for developing an application. Many businesses moved from Monolith to the modern Microservices architecture pattern but some businesses still benefit by using the Monolith pattern. For example, if the project has small team size, or the scope of the application is limited, then Monoliths suits best as it’s easy to develop and deploy. However, there are many challenges one can face like scalability, difficulty in debugging, etc. while using this pattern.

2. What is Microservices Architecture?

Microservices architecture is an alternative to monolithic design. In this pattern, the entire codebase is splitted into smaller and independent components that perform a single specific task. Each component here can be developed, tested, deployed, and scaled independently. These components can also communicate with one another using Application Programming Interface (APIs). 

Microservices are easier to create and test from a software engineering point of view. Development teams can make faster progress due to continuous integration and continuous delivery (CI/CD). 

Further Reading on: Microservices Best Practices

3. Monolithic vs Microservices: Key Differences

3.1 Architecture

Let’s have a grasp on Microservices vs. Monolithic architectures before we get further into the other components of these two practices.

A monolith is a single, homogeneous construct of software. There are typically three components: client side user interface, a database, and server-side program. All HTTP requests and the actual processing of business logic are typically handled by the server-side application. Server-side logic, user interface logic, batch tasks, etc. are all included within a single EAR, WAR, or JAR file in monolithic architectures.

Whereas, a microservices architecture separates broad categories of functionality and business operations into micro, and more manageable components. Each service may be built separately from the rest, has its own database, and interacts with other services via API endpoints.

The goal of this architectural approach is to construct a complex system out of smaller service suites. To make this work, each microservice runs its own processes and makes use of lightweight communication channels, such as APIs for accessing resources through the HTTP protocol. These microservices are deployed and managed separately from one another, and each is created separately around the business logic.

3.2 Use Cases

When to use Monolithic Architecture? 

When to use Microservices Architecture? 

3.3 Deployment Strategies

The scalability of software at the enterprise level is well-known to be a strength of any  architecture. While the monolithic architecture  pattern has seen widespread adoption, many businesses are having trouble devising a plan to overcome significant obstacles, such as deconstructing it into a microservices-based application. 

For the Monolithic application deployment, multiple identical copies of the application run on multiple servers. It can be done by equipping N number of virtual or physical servers and executing all the instances of an application. There might be hundreds of services in a microservices application, all of which were developed using different programming languages and tools. Each service acts like a standalone program and has its own set of requirements for things like deployment, scalability, and monitoring.

Although still in its infancy, the microservice architecture offers a promising new approach to app development. When building a microservices-based application, you’ll need in-depth knowledge of the several microservices frameworks and programming languages used by the individual services. It’s a significant obstacle because every service has its own requirements for deployment, resources, scalability, and monitoring.

Services for deployment should be efficient in time and money invested. In order to cope with a flood of requests from several interconnected parts, most microservice deployment techniques are readily scalable. Various options for deploying microservices are outlined here so that you may select the best fit for your company’s needs.

1. Multiple Service Instances Per Host

Deploy Multiple Services or multiple instances of different services on a single host. Host can be either a physical or a virtual machine. 

There are various ways for the deployment of service instances:

1. Deploy every individual microservice instance as a JVM process. 
2. Deploy multiple microservice instances in the same JVM. 

2. Single Service Per Host

Deploy each microservice on its own host.

The key benefits one can get using this approach are:

1. Each service is isolated from another one. 
2. Rare possibility of conflicting dependency and resource requirements. 
3. Easy to Manage, test, monitor, and redeploy each service. 

3. Serverless Deployment

Deploy each microservice directly on the deployment infrastructure. This method hides the concept of deployment on physical or virtual hosts or containers. The deployment infrastructure is mainly operated by a cloud service provider. It uses inbuilt containers or virtual machines to isolate the microservices. For this kind of deployment, one is not required to manage physical hosts, virtual servers, operating systems, etc. 

Some examples of serverless deployment environments are:

1. AWS Lambda
2. Azure Functions
3. Google Cloud Functions

4. One Service per Container

Deploy each service as a container by packaging it as a docker (container) image. 

Key benefits: 

1. Containers are fast to build and run. 
2. By changing the number of container instances, one can easily scale up or down any microservice. 
3. Each service is isolated from another one.
4. Internal details of the microservice are encapsulated by the container. 

3.4 Cost

The term “cost” encompasses several different considerations. The total cost of ownership includes the initial investment, as well as the costs of maintenance, progression, durability, performance, and productivity. When making the ultimate choice to implement any software design, cost is a major element that comes to the minds of executives.

Monolithic architecture would cost less in case of MVP (Minimum Viable Product) development, small applications creation, initial phase of an application, smaller team size, limited technical expertise, etc. while Microservices architecture would cost comparatively less in case of complex application development.  

3.5 Scalability

There are a number of different techniques to adjust the size of a monolith. Using a load balancer to send requests to various virtual machines is one option.

By decomposing the entire application into smaller services, microservices architecture provides more flexibility and scalability. Each service can be scaled vertically as well as horizontally. There are a variety of methods and tools available to scale the microservice in both ways. Amazon Elastic Container Service, Docker, Kubernetes, and Amazon Elastic Container Service are just a few of the widely used tools out there. Microservices are the best option for exact scaling and efficient resource use.

3.6 Monolithic vs Microservices Architecture: Advantages and Disadvantages

Let’s first go through the advantages of both the architectures: 

Monolithic Architecture:

Microservices Architecture: 

Now, let’s see the disadvantages of both the architectures: 

Monolithic Architecture: 

Microservices Architecture: 

Below is the Statista survey report for the Microservices architecture: 

4. When to Use the Microservice Architecture?

Knowing when it’s appropriate to employ this architecture is difficult. The issues that this method addresses are not always present while creating the initial version of an app. More so, development time will increase when a complex distributed architecture is used. Startups frequently have the greatest obstacle in fast evolving the business model and supporting applications, therefore this might be a serious issue for them. 

While vertically decomposing the monolith application, quick iterations can be more difficult. Therefore, when the problem is how to scale while employing functional decomposition, you may find it challenging to break down your monolithic application into a collection of services due to the complexity introduced by the intertwined dependencies. The founder of Microservices.io Chris Richardson is adding more value to it via his tweet.

Monolith First is generally good advice. But it’s not universally applicable. Sometimes it might make sense to start with microservices. To understand why, let’s analyze the trade-offs using dark energy and dark matter. pic.twitter.com/zrXfy13DMH

— Chris Richardson (@crichardson) November 29, 2022

5. Tips to Migrate From Monolithic Architecture to Microservice Architecture

The process of transferring or refactoring the monolithic application into Microservices based application is called Application Modernization. First, verify that your software delivery issues are caused by outgrowing your monolithic design before making the switch to a microservices model. If you can enhance your software development process, you may be able to shorten the time it takes to release.

The monolith may be strangled and replaced by microservices in three basic ways:

1. Add functionalities as a service.

2. Divide the front-end from the back-end.

3. Remove the complexity of the monolith by splitting features into separate services.

The first tactic is used to halt the expansion of the monolith. It’s a fast approach to proving microservices’ worth and winning over skeptics ahead of a larger move. Other two methods dismantle the giant structure. The third technique, in which a feature is transferred from the monolith into the strangler application, is the one you will always employ when reworking your monolith. You can get clear picture from Bilgin Ibryam‘s tweet.

[Video] AWS Serverless architectural patterns and best practices (ARC307-R3) https://t.co/jAs5tTHpoh pic.twitter.com/Xw9Aaq3fyW

— Bilgin Ibryam (@bibryam) November 19, 2022

Subsequently moving the monolith’s functions into separate services is the primary strategy for decomposing it. Getting the most valuable services out of a system should be a top priority. Whenever a new service is created, it will inevitably have to communicate with the monolith. 

Supporting both the in-memory session-based network security of the monolithic application and the token-based system security of the services is required during remodeling to a microservice architecture.

 An easy workaround is to have the API gateway send security tokens included in cookies generated by the monolith’s login handler.

Here are some of the most followed considerations to keep in mind while in the migration phase.

5.1 Build Optimization

Time and space have been occupied by monoliths. The first thing to do is simplify your development process. The build will be more stable if you take off the external elements and dependencies that are causing problems.

5.2 Decouple the Dependencies

The modular dependencies of the monoliths should be eliminated once the build process has been simplified. If you want to reach such a level of separation in your code, you might need to rework it.

5.3 Enhance Regional Growth

The development, deployment, and testing processes on the local development environment should go more quickly. It’s important to adopt Docker and similar tools at the neighborhood level as well. Tasks like installing a local database, etc., are sped up as a result.

5.4 Expanding in a Concurrent Manner

It is recommended to split the code repository into multiple branches, one for each microservice. Because of this configuration, all monoliths may be developed simultaneously, which will boost the agility of software development lifecycle (SDLC).

5.5 Adopt Infrastructure as Code (IaC)

A more standardized and reliable infrastructure is made possible by IaC adoption. With the support of a realistic approach to environment construction, developers may bring the cloud closer to their computers. 

While introducing new features as services is tremendously valuable, the only means of eradicating the monolith is to systematically remove modules from the monolith and transform them into services. 

For example, let’s say that your team wishes to increase the productivity of the company and client happiness by swiftly repeating the courier scheduling algorithm. It will be a way simpler for them to concentrate on the delivery management logic if it’s a distinct Delivery Service. To achieve that, the team needs to decouple delivery management from order management and transform it into operation.

Here’s a graphical representation of how your team can ace the process:

6. Conclusion

Adopting a microservices architecture is a challenging move. Not all architectures are same. The same is true for software, which can vary widely. The idea is to gradually implement microservices and the related technologies and techniques. Microservice architectures shine when used with advanced software that is constantly changing. Adopting microservices, however, will be an immense challenge without the necessary knowledge and experience with these tools. 

This article compares two common types of software architectures, microservices and monoliths, to help you decide which is best for your needs. In the end, you’ll need to settle on a strategy that’s most effective in your particular setting. But have no worry; that’s exactly why we exist! Never hesitate to call upon us for assistance.

The post Monolithic vs Microservices Architecture appeared first on TatvaSoft Blog.

1. What is GitOps?

GitOps is an open-source control system that can be used to manage infrastructure automation, provisioning, deployment, and application configurations for any project or product. GitOps is a popular operational framework that developers use to utilize Git. With the help of GitOps, developers can be sure that Git is the key source that can be used for application source code, configuration and infrastructure management. The name GitOps means Git (the version control system) + operations (software development’s operations management aspect).

“In the DevOps world, #GitOps is perhaps unique in that it can potentially benefit both operations team members and developers.”

Learn more from @TechBradD and @pritianka. https://t.co/Eg1VJl0Bf2

— GitLab (@gitlab) October 10, 2019

Besides this, Git is a technology that developers use to manage the deployment automation of the application. The Git repository enables retaining the entire state of the system while maintaining a detailed history of all the changes made by the developers in the system. Besides this, GitOps is a special framework designed to help developers perform management activities while they are using software development tools, processes, and techniques.

History

In the year 2017, Weaveworks focused on Kubernetes solutions and introduced the concept of ‘GitOps’. It was a set of best practices for application management and deployment by leveraging cloud services as an extension of the DevOps approach.

GitOps is a very useful, popular, and mission-critical tool for software development. It enables the developers to pull requests and code review workflows. Pull requests make the visibility of incoming changes clear to a codebase and also encourage discussion, communication, and review of changes. Pull requests are known as the pivotal feature of Git. They help developers collaborate on software development tasks and handle the changed way teams and businesses create a software solution. Besides this, pull requests have the capability to offer transparency and measurability to previous opaque processes. GitOps pull requests also enable the evolution of DevOps processes and because of all these things that GitOps started to offer, the system admins who were hesitant to make changes are now embracing this new practice of software development.

Before GitOps was launched in the market, the systems administration was managing the software development process manually by either connecting to the machine and provisioning IT infrastructure in a physical server rack or by provisioning it on the cloud. This process required large amounts of manual configuration and admins would have to keep custom collections of imperative scripts and configurations. But with GitOps coming into the picture, everything got automated. Now, collaborating on the tasks, infrastructure configuration, managing the app development process, and deploying the solutions can all be done easily with the GitOps workflow approach.

Besides this, when the GitOps idea was initially hatched and shared by WeaveWorks, the entire Kubernetes management firm has since proliferated throughout the DevOps community. The reason behind it is that GitOps has the capability to add some magic to the pull request workflow that synchronizes the live system to the static configuration repository.

“GitOps is game-changing for the industry. It is a replicable, automated, immutable construct where your change management, everything happens in Git.” – Nicolas Chaillan, Chief Software Officer of the U.S. Air Force

2. What is DevOps?

DevOps is one of the most popular practices that is a combination of cultural philosophies and tools used to increase any company’s ability to deliver software solutions and services at high velocity. DevOps benefits the software development lifecycle of any organization in a great way as it enables the development team to evolve and improve the products at a faster pace than before. This is done by modernizing the traditional development and infrastructure management processes. DevOps offers quick solutions which enable organizations to provide better service to their customers. Besides this, the development and operations teams of the firm can collaborate well, create solutions faster and launch them more effectively in the market.

History

The use of DevOps was started in the years 2007 and 2008. During this time, the IT operations and software development communities had raised concerns about this technology and its fatal effect on the industry. They wanted to stick up to the traditional software development model in which the code was written at the organizational level and the deployment & support were considered to be a part of the functional level. During those times, the developers and operation professionals had separate objectives, department leadership, and key performance indicators. As per these factors they were judged and different floors were allocated to them in the company’s building and because of all these things, the teams had to work for long hours. The separated work departments also caused issues in creating software which lead to unhappy customers.

But after DevOps came into the practice, the companies started to work on modern cloud infrastructure which centralized the entire app development process of the company. The developers started using agile methodologies for software planning and development after adopting DevOps. DevOps offers an approach that helps developers in managing modern cloud infrastructure, create and update code confidently without any issues, and have a unique transformation in the company’s system infrastructure modifications.

Basically, DevOps methodologies enable the development teams to work efficiently and offer the best results to their clients. Before going through the major differences between GitOps and DevOps, let’s have a look at some statistics. As per Statista, both DevOps and GitOps are the most important practices for open-source professionals in the year 2022 by 45%.

3. GitOps vs DevOps: How is GitOps different from DevOps?

Here are the major differences between GitOps vs DevOps –

Approach

GitOps: The main approach that GitOps uses is utilizing the Git tools that can manage software deployment and infrastructure provisioning.

DevOps: DevOps follows an approach that focuses on Continuous Integration/Continuous Delivery and isn’t tied to specific tools.

Focus

GitOps: The main focus of GitOps is on correctness which means doing DevOps correctly.

DevOps: The main focus of DevOps is on automation and frequent software changes and deployments.

Flexibility

GitOps: GitOps is a bit stricter and less open.

DevOps: DevOps is less strict and more open.

Main tool

GitOps: This technology uses all Git tools available in the market.

DevOps: This technology uses CI/CD pipeline.

Other tools

GitOps: Some tools that GitOps uses are Kubernetes, Infrastructure as Code, and separate CI/CD pipelines.

DevOps: Some tools that DevOps uses are cloud configuration as code and supply chain management.

Correctness

GitOps: GitOps is designed by keeping correctness in mind.

DevOps: DevOps is designed to maximize automation.

4. How can GitOps benefit you?

Any company can easily integrate GitOps with DevOps, and because Git is the standard tool for the software team, the majority of the developers are familiar with it which allows them to be a part of various processes that happen in the organization. GitOps is a process that allows any changes that are made in the firm’s system to be tracked and monitored. Besides this, with GitOps locating the source of the issues, creating a culture of transparency in system architecture is easy, and it also helps in complying with the security regulations. In addition to this, GitOps also offers continuous integration (CI) and continuous delivery (CD) on top of declarative infrastructure which helps developers not worry about scripting and start the deployment process quickly, says Kelsey Hightower a famous American software engineer who works on Kubernetes and cloud computing.

Basically, when any organization adopts GitOps, it can easily increase the team’s productivity by enabling the developers to experiment with new infrastructure configurations freely. This is possible because Git comes with a history of functions that enables the teams to revert changes that don’t help the system’s improvement. This is why GitOps is the best and most handy tool for developers who want to work with complex infrastructure in an easy way.

5. GitOps Use Cases

GitOps Use Case!#GitOps #GitHub #Git #DevOps #AIOps #DevSecOps #Kubernetes #Dockers #100DaysOfCode #code #CodeNewbie #Developers #OpenSource #Python #Java #tech #API #technology #Data #AWS #cloud #Hadoop #BigData #microservices #design #architecture #Engineering #AI #RT #bot pic.twitter.com/haaMQpLm2V

— 𝔸𝕞𝕚𝕥𝕒𝕧 𝔹𝕙𝕒𝕥𝕥𝕒𝕔𝕙𝕒𝕣𝕛𝕖𝕖 (@bamitav) November 20, 2021

Here are some of the major use cases of GitOps –

• Network slicing – GitOps helps the software development services providers to differentiate service tiers and users to pay only for the required bandwidth. This includes a premium subscription for any video streaming application and lower prices for IoT-based devices connected to it.
• Smart city services – When it comes to implementing the services related to the smart city, there are many challenges that the developers face like roll-out or managing complex platforms. In this case, GitOps can help in handling all the difficult systems and operations.
• Addressing network congestion – In big cities, users face network congestion issues while being connected to a 4G network. But with 5G coming into the market, this problem seems to have lessened still it requires cloud-native principles to manage various edge nodes. To solve this issue, network-providing companies use GitOps.

6. DevOps Use Cases

Here are some of the major use cases of DevOps –

• Online Financial Trading Company: DevOps methodologies can be useful in creating and testing applications in the financial trading company. The use of DevOps while deployment makes the process faster and the clients can get the product features implemented quicker.
• Car Manufacturing Industries: Car manufacturing industries use DevOps to help employees catch errors easily while scaling production.
• Early Defects Detection: Any type of organization can use DevOps to detect errors efficiently at the earliest stage possible.

7. Conclusion

As mentioned in this blog, GitOps has offered real value to many organizations by being a powerful tool that helps in managing system’s cloud infrastructure which offers a lot of benefits to the software service provider companies without blocking the developer out with too many tooling choices, and by increasing the productivity of a devops team. DevOps brings a cultural change in the way any company’s development or operational team works in a much collaborative way. Also both these technologies offer benefits like communication, stability, visibility, and system reliability. Adopting these approaches can be beneficial but which to use is dependent on type of operations the firm carries out.

The post GitOps vs DevOps: In-depth Comparison appeared first on TatvaSoft Blog.