React Native is a cross-platform mobile application development framework created by Meta Platforms (formerly Facebook). It is based on React, a JavaScript library for building user interfaces. React Native allows developers to build native mobile applications using JavaScript and React. React Native uses the same design principles as React, so developers can use the same skills and knowledge to build mobile applications. This makes it a great choice for developers who are already familiar with React.

React Native also offers a number of advantages over other cross-platform mobile development frameworks, such as:

• Native performance: React Native applications are built using native components, so they have the same performance as native applications.
• Reusability: React Native components can be reused across different platforms, so developers can save time and effort.
• Community support: React Native has a large and active community of developers, so there is plenty of support available.

What is top use cases of React Native?

React Native is a versatile framework that can be used to build a wide range of mobile applications. Its ability to create native-like experiences across different platforms while using a single codebase makes it suitable for various use cases.

Here are some of the top use cases of React Native:

• Social media apps: React Native is a great choice for building social media apps because it offers native performance and reusability. This is important for social media apps that require a lot of user interaction. For example, Instagram and Facebook Messenger are both built with React Native.
• E-commerce apps: React Native is a great choice for building e-commerce apps because it offers native performance and a smooth user experience. This is important for e-commerce apps that need to load quickly and provide a seamless shopping experience. For example, Shopify and Airbnb are both built with React Native.
• News apps: React Native is a great choice for building news apps because it offers native performance and a responsive user interface. This is important for news apps that need to load quickly and display content in a visually appealing way. For example, Bloomberg and The New York Times are both built with React Native.
• Games: React Native is a great choice for building games because it offers native performance and a smooth user experience. This is important for games that need to run smoothly and respond to user input quickly. For example, Pokemon Go and Temple Run 2 are both built with React Native.
• Business apps: React Native is a great choice for building business apps because it offers native performance and a polished user interface. This is important for business apps that need to be reliable and easy to use. For example, Uber and Airbnb are both built with React Native.

What are the features of React Native?

Here are some of the features of React Native:

• Native performance: React Native applications are built using native components, so they have the same performance as native applications. This is important for applications that require a lot of interaction with the user, such as games and social media apps.
• Reusability: React Native components can be reused across different platforms, so developers can save time and effort. This is especially beneficial for large applications with a lot of shared code.
• Community support: React Native has a large and active community of developers, so there is plenty of support available. This is important for developers who need help with troubleshooting or learning new features.
• Easy to learn: React Native is based on React, a JavaScript library that is widely used for building user interfaces. This makes it easy for developers who are already familiar with React to learn React Native.
• Extensible: React Native is extensible, so developers can add custom components and functionality to their applications. This is important for developers who need to build custom features or integrate with third-party services.

What is the workflow of React Native?

The workflow of React Native can vary depending on the specific needs of your project. However, the steps outlined above are a general overview of the workflow that you can follow to develop and deploy your React Native app.

Here are some additional details about each step in the workflow:

• Planning: The planning stage is important for ensuring that your React Native project is successful. During this stage, you should decide what features you want your app to have, what platforms you want to support, and what third-party libraries you want to use. It is also important to create a timeline and budget for your project.
• Setup: The setup stage is where you will install the necessary tools and dependencies, and create a project directory. You will also need to choose a JavaScript development environment, such as Visual Studio Code or WebStorm.
• Development: The development stage is where you will write code for your React Native app. You will use React components to build the user interface, and JavaScript to handle the app’s logic. You should also test your app regularly to make sure it is working properly.
• Building: The building stage is where you will generate the native code for iOS and Android, and sign the app binaries. You will use the React Native CLI to build your app for the platforms you want to support.
• Deployment: The deployment stage is where you will submit your app to the app stores. You will need to create an account with Apple and google, and submit your app for review. Once your app is approved, it will be available for users to download.
• Maintenance: The maintenance stage is where you will fix bugs, add new features, and update the app for new versions of the operating systems. You will also need to monitor the app’s performance and user feedback.

How React Native Works & Architecture?

React Native is a cross-platform mobile development framework that uses React, a JavaScript library for building user interfaces. React Native allows developers to build native mobile applications using JavaScript and React. React Native works by using a bridge between JavaScript and the native platform. The bridge allows JavaScript code to interact with native components and APIs. This means that React Native apps can access all of the features that are available on the native platforms, such as the camera, the accelerometer, and the GPS.

The architecture of React Native is divided into three layers:

• JS: The JavaScript layer is where the React code is executed. This layer is responsible for rendering the user interface and handling user input.
• Bridge: The bridge is the layer that allows JavaScript to interact with the native platform. This layer is responsible for translating JavaScript calls into native calls.
• Native: The native layer is where the native components and APIs are implemented. This layer is responsible for rendering the user interface on the device and handling user input.

How to Install and Configure React Native?

To install and configure React Native on your system, follow these steps:

1. Install Node.js and npm:

React Native requires Node.js and npm (Node Package Manager). You can download and install them from the official Node.js website: https://nodejs.org/

2. Install React Native CLI:

The React Native Command Line Interface (CLI) is needed to create and manage React Native projects. Open your terminal or command prompt and run the following command to install the React Native CLI globally:

<strong>npm install -g react-native-cli</strong>

3. Install a Code Editor:

Choose a code editor for writing your React Native code. Some popular choices are Visual Studio Code, Sublime Text, or Atom.

4. Install Java Development Kit (JDK):

For Android development, you’ll need the Java Development Kit. Download and install the appropriate version from the Oracle website: https://www.oracle.com/java/technologies/javase-downloads.html

5. Install Android Studio:

Android Studio provides the tools necessary for Android development. Download and install Android Studio from the official website: https://developer.android.com/studio

6. Set Up Android SDK:

After installing Android Studio, open it and go to the “SDK Manager.” Install the Android SDK, build tools, and required platform tools. Make sure to set the environment variables ANDROID_HOME and add %ANDROID_HOME%\platform-tools to your system’s PATH.

7. Configure Virtual Device:

In Android Studio, create an Android Virtual Device (AVD) to use the Android emulator for testing. You can create an AVD through the “AVD Manager.”

8. Install Xcode (For macOS):

For iOS development on macOS, install Xcode from the Mac App Store.

9. Set Up Xcode Command Line Tools:

After installing Xcode, open it and go to “Preferences” > “Locations.” Make sure the correct version of Xcode Command Line Tools is selected.

10. Install Watchman (Optional but Recommended):

Watchman is a tool that watches files for changes and triggers actions. It’s recommended to install it for better performance with React Native:

<strong>brew install watchman</strong>

(For macOS using Homebrew)

11. Create a New React Native Project:

Open your terminal or command prompt and navigate to the directory where you want to create your project. Run the following command to create a new React Native project:

<strong>react-native init YourProjectName</strong>

Replace YourProjectName with the desired name for your project.

12. Run Your App:

Navigate to your project directory:

<strong>cd YourProjectName</strong>

For Android:

<strong>react-native run-android</strong>

For iOS:

<strong>react-native run-ios</strong>

Spring is a popular open-source framework for building and developing enterprise-level Java applications. It provides a comprehensive programming and configuration model for developing modern, scalable, and maintainable applications. Spring is designed to address various aspects of application development, including dependency injection, aspect-oriented programming, transaction management, security, and more.

Spring provides a number of features that make it a powerful and versatile framework, including:

• Inversion of control (IoC): Spring uses IoC to decouple components in an application. This makes it easier to test and maintain applications.
• Dependency injection (DI): Spring uses DI to inject dependencies into components. This makes it easier to change dependencies without having to modify the components that use them.
• Aspect-oriented programming (AOP): Spring supports AOP, which allows you to modularize cross-cutting concerns in your application.
• Template engines: Spring supports a number of template engines, such as Thymeleaf and FreeMarker. This makes it easy to generate HTML, XML, and other types of output.
• Data access: Spring provides a number of data access technologies, such as JDBC, JPA, and Hibernate. This makes it easy to access data from a variety of sources.
• Web development: Spring provides a number of features for web development, such as MVC, WebSockets, and REST. This makes it easy to develop web applications.

What are the top use cases of Spring?

Spring is a powerful and versatile framework that can be used to develop a wide variety of applications.

Here are some of the top use cases of Spring:

• Web development: Spring is a popular choice for web development. It provides a number of features that make it easy to develop web applications, such as MVC, WebSockets, and REST.
• Microservices: Spring is a good choice for microservices architectures. It provides a number of features that make it easy to develop and manage microservices, such as service discovery and load balancing.
• Data access: Spring provides a number of data access technologies, such as JDBC, JPA, and Hibernate. This makes it easy to access data from a variety of sources.
• Enterprise applications: Spring is a good choice for enterprise applications. It provides a number of features that make it easy to develop and maintain enterprise applications, such as security and transactions.
• IoT: Spring is a good choice for IoT development. It provides a number of features that make it easy to develop and manage IoT applications, such as device management and data streaming.
• Cloud computing: Spring is a good choice for cloud computing. It provides a number of features that make it easy to develop and deploy applications on cloud platforms, such as AWS, Azure, and Google Cloud Platform.

What are the features of Spring?

Spring is a powerful and versatile framework that provides a number of features that make it a good choice for Java development.

Here are some of the features of Spring:

• Inversion of control (IoC): Spring uses IoC to decouple components in an application. This makes it easier to test and maintain applications.
• Dependency injection (DI): Spring uses DI to inject dependencies into components. This makes it easier to change dependencies without having to modify the components that use them.
• Aspect-oriented programming (AOP): Spring supports AOP, which allows you to modularize cross-cutting concerns in your application.
• Template engines: Spring supports a number of template engines, such as Thymeleaf and FreeMarker. This makes it easy to generate HTML, XML, and other types of output.
• Data access: Spring provides a number of data access technologies, such as JDBC, JPA, and Hibernate. This makes it easy to access data from a variety of sources.
• Web development: Spring provides a number of features for web development, such as MVC, WebSockets, and REST. This makes it easy to develop web applications.
• Security: Spring provides a number of features for security, such as authentication, authorization, and encryption. This makes it easy to secure your applications.
• Testing: Spring provides a number of features for testing, such as unit testing, integration testing, and continuous integration. This makes it easy to test your applications.
• Performance: Spring is designed to be performant, making it a good choice for applications that require high performance.
• Scalability: Spring is designed to be scalable, making it a good choice for large applications.
• Reliability: Spring is designed to be reliable, making it a good choice for applications that need to be highly available.
• Documentation: Spring has extensive documentation, making it easy to learn and use.
• Community: Spring has a large and active community, making it easy to get help when you need it.

What is the workflow of Spring?

The workflow of Spring can be divided into the following steps:

• Define the components of your application: The first step is to define the components of your application. This includes defining the classes that will make up your application, as well as the dependencies between them.
• Configure the application: Once you have defined the components of your application, you need to configure it. This includes configuring the dependencies between the components, as well as configuring the application’s environment.
• Bootstrap the application: The next step is to bootstrap the application. This involves initializing the Spring IoC container and loading the application’s configuration.
• Create the beans: The Spring IoC container will then create the beans that make up your application. These beans are the objects that will perform the work of your application.
• Invoke the beans: Once the beans have been created, they will be invoked. This is when the application will start to do its work.
• Shut down the application: When the application is finished, it will be shut down. This involves destroying the beans and releasing any resources that they are using.

How Spring Works & Architecture?

Spring is a popular Java framework that provides a comprehensive infrastructure for developing Java applications. It is used by a wide variety of applications, from small web applications to large enterprise applications. Spring works by using the Inversion of Control (IoC) principle. IoC means that the Spring framework controls the creation and instantiation of objects in your application. This decouples your code from the details of how objects are created and instantiated, making your code more modular and easier to test.

Spring also provides a number of other features that make it a powerful and versatile framework, including:

• Dependency injection: Spring uses dependency injection to inject dependencies into objects. This means that you don’t have to worry about creating and managing dependencies yourself. Spring will do it for you.
• Aspect-oriented programming (AOP): Spring supports AOP, which allows you to modularize cross-cutting concerns in your application. This makes your code more readable and maintainable.
• Template engines: Spring supports a number of template engines, such as Thymeleaf and FreeMarker. This makes it easy to generate HTML, XML, and other types of output.
• Data access: Spring provides a number of data access technologies, such as JDBC, JPA, and Hibernate. This makes it easy to access data from a variety of sources.
• Web development: Spring provides a number of features for web development, such as MVC, WebSockets, and REST. This makes it easy to develop web applications.

How to Install and Configure Spring?

Here are the steps on how to install and configure Spring:

1. Install Java Development Kit (JDK). Spring requires a JDK to run. You can download the latest version of the JDK from the Oracle website.

2. Install Spring Boot CLI. Spring Boot CLI is a command-line tool that can be used to create and manage Spring Boot applications. You can download the latest version of Spring Boot CLI from the Spring Boot website.

3. Create a new Spring Boot project. You can use the Spring Boot CLI to create a new Spring Boot project. To do this, run the following command:

spring init --build=maven --dependencies=web my-project

This will create a new project called my-project with the following dependencies:

• Spring Web
• Spring Boot DevTools

4. Add your code. Once you have created a new project, you can add your code to the src/main/java directory. The main class for your application should be called DemoApplication.java.

5. Run your application. To run your application, you can use the following command:

mvn spring-boot:run

Hello everyone, to see emerging software advancement in the IT corporate world and due to their trending IT infrastructure. So, today in this article, we are going to give lessons on the installation process of Jira on Mac Os so, we will look at prerequisites and then we will download Jira for Mac Os, how to start and shutdown Jira (Tomcat), set up the home directory and then finally, we will set up Jira for use. Let’s have a look!

Let us begin.

Step 1:

Prerequisites for installing Jira on the mac operating system

Java must be installed in your system so to check you can go to your terminal and say java –version and this shows you your java version currently installed in case you are not getting this you can install java first and then if you will have this prerequisite completed step number two will be

Step 2:

How to download Jira for Mac OS

You will download Jira for the mac operating system and this is the site

https://www.atlassian.com/software/jira/download

Where you will download it from so you will go to google and you can say download Jira and you will get that site, you will go there and there you will get that information it is free for thirty days for unlimited users and there you can select your operating system so, you will select OS 10 and then download so it will take a few seconds to a few minutes to download so you have already downloaded it if you will go to your downloaded zip file so if you will go to your downloads folder you will see that zip file which will get downloaded and you will unzip this so, you will have unzipped it and kept on your desktop there so this will be unzipped folder so now the third step is

Step 3:

How to start and shutdown Jira

Or you can also say the Jira tomcat server because Jira comes with the tomcat server so you will have to go to the bin directory inside the folder and you will find startup.SH and shutdown got SH files and these are the files that you will run to start and shutdown Jira server so, we will learn that you will go inside your folder and there you will see there will be bin directory and inside the bin, you will find that startup.SH and shut down. SH there you will have a startup.SH and there you will have a shutdown.SH so, to start you will go to the terminal and go to the location bin folder so for example, you will just press command on your keyboard to get that information and copy the location of that folder and then you will go to your terminal and you will change the directory to that bin folder of Jira and now you can say SH startup.SH and hit enter and you will see that information and it would show you tom get started and to check you can go to your browser and you can go to localhost 8080 so as of now it will not run or you may run this command again and yes, you will see the Jira server is up but there will some problem and it will say we cannot locate the Jira home directory so you will have to set up the home directory so what you will do you will shut it down so you will say sh shutdown.SH and tomcat will stop so if you go to localhost 8080 now so you will see the server will be stopped and you will learn how to set up the home directory and that you have already seen that you will go to localhost 8080.

Step 4:

How to set home directory

To check if the Jira has server is running and to set the home directory you will have to go to that file Jira application. Properties which is inside web-inf glasses folder and  

Go to file Jira-application .properties located in Jira folder >> Atlassian–Jira >> Web-INF>> classes

there you will have to provide a location for Jira home so you will see how to do that so you will go to the Jira folder and you will have to go to atlassian Jira folder there you will have web-inf and there you will have classes and there you would find a file Jira application properties so you can open that file with any text editor on your system if you have a text wrangler, you will open this and you will see it will ask for your location for Jira home so you can create any folder and then provide that folder as Jira home so you will create a folder on your desktop itself and you will name that folder as Jira Home hit enter and just press command I to copy its location and you will give the same location on that file, you will give that location so that will Jira home and you can save it and close it okay and see you if you will open this folder as of now that will empty but as you will now start your Jira servers you will see there are folders and files getting created there all the logs will get there as well so now you will go back to your terminal and again say SH startup.asset and it’s storm get started you will go to your browser localhost 8080 you will run the start command again and you will go to localhost 8080 and now you will see atlassian Jira is starting up so it means it will take up your home directory as well it might take a few seconds to start up also if you will now go to your Jira home folder you will inside the folder and you can see all these logs and all these information will now getting created inside that folder. Now, for the first time, it will have this information if you want to set it up yourself or you want to set it up for me so, this is our next step.

Step 5:

Setup Jira for use

You will have to set up Jira for use so you will have started your Jira server and now you will complete the setup so you can click on set it up for me and continue there you will have to select the product so you will select Jira software and select Jira software server you can name any organization there up and running and then generate license so there it will give you the information of your license you will say yes confirmation and there it will ask you for some email ids and then password and retype the password so you will give some email id there and password say next so now it will finally set up all the instances and everything that Jira requires on that particular machine so you will wait for few seconds for that setup to get completed meantime you will look at some tips so instead of localhost you can also use the IP 127.0.0.1 which is the Ip for localhost or you can also use your system public IP instead of localhost so instead of localhost there you can use that IP and you will now see the Jira will ready to go and you can get started with Jira. I hope this information will be helpful for you and it will give you privileges as an onboarding learning concept with valuable steps.

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Hello everyone, you know the different phases of programming and about its evaluation on that, it is performing their task. So, we are going to learn about Gitlab CI/CD from very basic & scratch and if you don’t have primer knowledge on the above topic so, don’t worry, we will go up step by step. And in this lesson, we will engage with various topics like what is Gitlab CI/CD? We will create a .gitlab-ci.yml file, this is a file where we add our jobs and create a pipeline and I will show you how to do that then we will run CI/CD pipeline in Gitlab so, this is going to be very easy and interesting.

What is Gitlab CI/CD?

Let us learn about what is Gitlab CI/CD? So, you will go to Google & search for continuous integration and delivery. You will go to images and select one image there. You will see there, you will have continuous integration then CI stands for continuous integration so, the continuous delivery is CD and again, we will call continuous deployment is CD so, this is what we call CI/CD. And there, if you will look at continuous integration. There will be a process where you will have these three jobs and processes, chained and linked with each other. Why is it will be linked? I mean, if the first dev process or dev job runs and passes. And it will trigger the next job that is in the test job application test. If the passes it will trigger then the next job that is an integration test and you will have our continuous integration pipeline completed so this is what is called as CI or continuous integration and if this all these jobs in this cycle are chained with each other and our automated triggered we call it as a continuous integration system now if you also add an acceptance test job or acceptance test process which is also automated and linked this becomes a continuous delivery because after this step our application or our product will be ready for delivery so this becomes continuous delivery and if we also add our deployment job or a deployment process that will reply to the production and all these jobs are automated and chained and can be automatically triggered then this becomes a continuous deployment pipeline so this is what we call as continuous integration and continuous delivery and continuous deployment. Now, in GitLab as well we have this corners integration delivery and deployment, and here this GitLab CI is an open-source CI service or a continuous integration service included with GitLab and by default, this is integrated with every in your GitLab since version 8.0 so, if you are using version 8.0 or above GitLab then in all your projects by default you will have GitLab CI integrated and enabled by default and to go to the settings and to configure GitLab CI you should be a maintainer or our owner or an admin on your project so, you go to your GitLab account if you just go to your Gitlab you will sign in so, you can see there your projects and if you see the projects there you will be maintainer on one projects and owner on the other projects so, you can configure GitLab CI/CD so, this is what GitLab CI/CD is now.

Create .gitlab-ci.yml file

Actually, create a GitLab CI/CD pipeline, you will have to add a file called .gitlab –ci.yml so, yml files or ml is a format of writing text files, and like you have JSON and XML. Ml is also a format and I will show you that how to create it and you have to create this file in the root folder of your project or your repository so, whatever the root folder is and you will be creating this file in the main folder or the root folder of your project. Now, before we start creating this file so, this is used to configure our pipelines and in every project, you will be having, you will be adding this file where you can add the details and it will define the structure and order of the pipeline and once you create it you will know exactly what you mean do not worry if there is there are some things that you are not getting once you create the file and run it you will know exactly what it means? So, you will create a file now if you are on Mac, you can use any text editors like you have text editors on Mac then you have text wrangler anything will work if you are on windows, you can again use notepad or notepad ++ or in fact, you can use any editor but you have to make sure the syntax is correct and I will show you how you can check the syntax so, you will open your window with notepad++. You will open a new file and on your mac, you will open your text wrangler file so that you can create it there so to create a file you will just give some name of the job you will say that is demo job one. So, you will say demo job one any name you can give there and give a colon go to the next line and you will give five spaces so, you can give any number of spaces but you will have to be consistent with that so now you will say tags and there give a colon again go the next line give two spaces and you will give a hyphen and spaces and I can give any tag here now tags are important because in your gitlab you will be having the gitlab runners and they have some tags and the text should match only then the gitlab runner will run this particular file so if you go to my project on gitlab and there if you go to settings and go to CI/CD and you have runners there you will click on expand and you can see you had created this runner earlier and you had given this these tags there CI and SSS so you should be having one of these tags so that the runner can pick up this file and run it so, you will say CI there and you will go again to next line now again you will give there script and this is in line with tags again go to next line two spaces – and there you can write any command or script you want to run so, you will say hello echo hello world so they should run this command in this job this is a very simple file where you are running that script echo hello world so they should print hello world on the console and now you can also do the same thing on your windows on the notepad so you can create it like this and now you will have to make sure the syntax is correct and for that you can copy the contents and you can just go to google and search for any ml file validator utility or application and you will see that you have yam lint, yaml validator online this all you will go to yaml lint and paste your contents of the ml file and there you have to go button you will click there go and check and yes everything is fine it will says it is a valid YAML so that is fine you will now just save this so you will save this file and you have to make sure the name there should be .gitlab –ci.yml as of now you will save on desktop but you will move it to your project folder so, you will say as it is. I hope this will more authenticate your performances and give you a hike in the sections of Gitlab CI/CD.

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Before we start let’s talk about what is SRE. SRE is the one who works with the software engineers with the collaboration between developers and operation teams.

SRE is a practice that combines both software development skills and mindset to IT operations. The main focus of SRE is to enhance the reliability and performance of applications, with automation and continuous integration and delivery.

SRE has changed the traditional way of working as an operation team by incorporating new technologies, ideas, and methods. SRE was originated at Google.

After originated more than 1000 SRE engineers employed at Google. Even though after spread about SRE, other software companies also started adopting SRE engineers gradually. As per the 2021 report, 22% of organizations in a survey of 2,000 respondents have adopted the SRE model.

SRE accepts failure because they know failure is a part of success and not a single system is perfect. SRE and DevOps both work to bridge the gap between development and operations teams to deliver faster services. SRE has removed the “silos” between development and operation teams to function effectively.

SRE also works with the DevOps team to help them in operational works to give reliable service to the customer.

SRE Skillsets

SRE is a role that requires a software developer with operational experience or as a system admin or engineer for an IT operations role that has software development skills as well.

SRE needs some skillsets to have are-

Deep knowledge of version control.

Sound knowledge of operating Systems (like LINUX).

Should be aware of DevOps concepts and best practices.

CI/CD implementation expertise.

Issue troubleshooting experience.

Communication & Collaboration skills.

Good knowledge of Cloud-native applications.

Good understanding of “Distributed computing”

Should know “coding”

Even though with these skills they should know tools sets as well which will be used by the SRE team.

Some toolsets are –

S.no       Problems                                        Tools                           

1              Operating Systems              –               Centos/Ubuntu & VirtualBox & Vagrant

2              Cloud                                   –                 AWS

3              Containers                           –                Docker & Kubernetes – Helm

4              Planning and Designing –             –                Jira & Confluence

5              Source Code Versioning                –            –                   Git using Github

6              Webserver                          –                    Apache HTTP & Nginx

7              Configuration & Deployment Management            –            Ansible

8              Infrastructure Coding                            –           Terraform

9              Services mesh Data planes & Control Planes            –      Envoy & Istio

10           Network configurations and Service Discovery         –        Consul

11           Continuous Integration                  –                   Jenkins

12           Securing credentials                       –          HashiCorp Vault & SSL & Certificates

13           Infrastructure Monitoring                   –            Datadog, Prometheus with Grafana

14           Log Monitoring                  –                   Splunk & ELK stake

15           Performance & RUM Monitoring                   –                 NewRelic

16    Emergency Response & Alerting & Chat & Notification – SMTP, SES, SNS, Pagerduty & Slack    

SRE Roles and responsibilities. 

SRE teams are responsible for how code is deployed, configured, and monitored, as well as the availability, latency, change management, emergency response, and management capacity of services in production.

SRE helps teams to determine what new features can be incorporated and when by using service-level agreements (SLAs) to define the required reliability of the system through service-level indicators (SLI) and service-level objectives (SLO).

SRE takes back the collected data to the development team to fix the issue (means the vulnerabilities which shouldn’t be there while development) and not make it again next time.

Monitoring and logging are keys to SRE roles. In monitoring, they are keeping track of what’s happening in real-time. Logging is an archive of what has happened, so you can examine it later.

Monitoring will give you the ability to anticipate failures and see them coming, so you can proactively solve them.

Logging is like, when you get an unanticipated failure, it makes you get back and see what happened. So you can do RCA (Root cause analysis) and find out how to solve it, not for now but for the future.

So as an SRE expert you are responsible to monitor the product and fixing the issues, bugs, blot wares, etc by the use of automation to eliminate some extent of manual work. 

Automation is an essential part of the SRE. With automation, we can reduce the manual work even though fix the issue on which we have to work again n again. This also helps to reduce the toil.

Maintaining the balance between operations and development work is also one of the roles of SRE.

Training Place

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The key players covered in this study
LogicMonitor
AppDynamics
New Relic
Dynatrace
Solarwinds
SmartBear
Riverbed
Geckoboard

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Market segment by Type, the product can be split into
SaaS-based
Websites & Applications
Mobile Apps

Market Segment by Application, split into
Enterprise IT
Developers
Operations

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A new report, the 2021 State of Secrets Sprawl on GitHub, published today by GitGuardian, a provider of a tool for monitoring usage of application secrets, suggests developers are not especially good at keeping those secrets safe.

Based on an analysis of every single commit made to GitHub, the report finds there has been a 20% year-over-year increase in the number of secrets – such as application programming interface (API) keys, private keys, certificates, usernames and passwords – discovered on a public repository.

Developers, as they build an application, make secrets easily accessible as plain text for the sake of convenience. However, when those applications are deployed in a production environment, developers often forget to delete the secrets they stored in GitHub.

GitGuardian CEO Jeremey Thomas noted that cybercriminals are now actively scanning repositories looking for secrets that would enable them to compromise applications.

As the number of application development projects being launched increased, so too did the number of application secrets being stored in repositories like GitHub. The GitGuardian report notes 60 million repositories were created in the last year, representing a 35% increase over the previous year. GitGuardian claims it detected more than 5,000 application secrets per day. Most of those secrets have been detected in repositories that belong to developers (85%), while the other 15% belonged to organizations. The top four countries where secrets were disclosed were India, Brazil, the United States and Nigeria.

GitGuardian also notes it sent out 937,539 pro bono alerts to 558,086 developers last year that informed developers that application secrets were exposed. The mean time for GitGuardian’s algorithm to detect a leak is four seconds. The average mean time to response of a developer when informed of the issues is about 25 minutes, the report noted.

As a best practice, GitGuardian recommends not storing unencrypted secrets in git repositories, and that unencrypted secrets should never be shared via messaging systems like Slack. DevOps teams should also restrict API access and permissions.

As more attention is paid to how software supply chains are managed in the wake of some recent, high-profile breaches, there is no doubt the number of audits conducted will increase. Many of those auditors will specifically be trying to ascertain how application secrets are being managed. Developers may have to get used to a new, higher level of scrutiny, especially as DevSecOps practices become more widely adopted.

In the meantime, DevOps teams may want to review their dependency on public repositories. There are plenty of private repository options that provide most of the same source code sharing capabilities as a public repository. That may mean someone on the DevOps team is required to manage the private repository, but, given the fact that many regulatory bodies will soon be looking to make an example of organizations that don’t secure application secrets, chances are good those costs will be trivial compared to a fine that would be levied.

The move to continuous integration/continuous deployment (CI/CD) and agile development methodologies means that application development now requires network IT operation teams (NetOps) and security operation teams (SecOps) to work together, which puts increased stress on developers and engineers.

Add heterogeneous computing environments to the mix, and it’s no wonder that the role of application delivery and security within DevOps has never been more onerous. Selecting an application delivery solution that maximises automation and integrates into an existing DevOps environment is critical.

Here are four reasons why application delivery is critical to supporting DevOps.

Production-ready automation
CI/CD and agile development methodologies require IT experts from different domains, (i.e., application, storage, network security, application delivery) to deploy new application services and their associated policies. Traditionally, they’ve had to invest in long, tedious provisioning and programming tasks that are often repetitive and require specific domain expertise to execute.

In a DevOps-driven world, this is no longer possible. IT requires workflow automation so that even non-technical experts can develop and craft application delivery and security workflows. According to Radware research, over half (53%) of organisations don’t integrate application protection into CI/CD processes.

This is why IT operations require an evolution, transitioning from simple scripts to standard-based, production-ready modules. The goal? To enable anybody from different teams to deploy and manage services regardless of the domain expertise he or she possesses.

Automated ADC and security
The marketplace for application delivery and security solutions is as diverse as its capabilities. Selecting one that integrates with an application provisioning and deployment solution, such as Ansible, is critical to enabling end-to-end automation.

Traditionally, deploying a new application delivery service has meant writing and managing a monolithic, gargantuan script to automate the workflow. Each application deployment requires a different workflow, and thus, a different script. DevOps requires these monolithic codes to be broken into discrete operations to speed time to development and deployment.

Underlying application delivery and security services that support these applications are no exception to this rule. An enterprise-grade ADC should provide pre-defined/production-ready modules and integration with DevOps orchestration tools to allow non-technical users to spin up and deploy application and security services.

Traditionally, if an error occurs, a review and QA of the code would be required. In a module-based world, errors become more transparent and segmented. For example, if only the application security policy is incorrect, the problem can be identified, fixed and only the security policy rerun, versus the entire script-based workflow.

Reuse and repurpose
Production-ready modules provide the ability to reuse and repurpose. If a particular module, such as the application security module, requires an update, SecOps can make that update, create a subversion if necessary and apply it to other application workflows. Changes are isolated to the specific module and don’t impact other aspects of the workflow.

Finally, an application owner, versus an ADC expert, can make these changes to the application security module or other modules. For example, while application servers and security policies can reside with the application owner, VLAN operations might be a network administrator’s responsibility. Now, a single person can manage these usually disparate responsibilities, thereby saving time to market.

This modularised approach also means switching from staging to production and back seamlessly. Changes to workflow parameters made within a staging environment can be pushed to production following staging. These capabilities support CI/CD processes by minimising human errors and reducing downtime.

Enterprise-grade ADC capabilities
Finally, any application delivery solution must combine ease of use with advanced application delivery capabilities, such as optimising Layer 7 load balancing deploying and managing application security policies. This further enhances the capabilities of any DevOps orchestration tool.

The latest Continuous Integration Software market report estimates the opportunities and current market scenario, providing insights and updates about the corresponding segments involved in the global Continuous Integration Software market for the forecast period of 2021-2026. The report provides detailed assessment of key market dynamics and comprehensive information about the structure of the Continuous Integration Software industry. This market study contains exclusive insights into how the global Continuous Integration Software market is predicted to grow during the forecast period.

The Continuous Integration Software market research report presents a thorough examination of the key trends and factors influencing the growth and slowdown of this industry vertical, so as to assist stakeholders in better understanding this domain. Moreover, it offers insights about the future growth matrix of this domain by evaluating the past and present business setup. Besides, the research literature provides in-depth information on the size and shares of the market and its segments, while unveiling the opportunities that ensure high returns in the approaching years.

As per expert opinions, the Continuous Integration Software market is projected to accrue notable returns during 20XX-20XX, registering a CAGR of XX% throughout.

Proceeding further, the document discusses the impact of COVID-19 on the industry, taking into consideration the challenges tackled by businesses, like expenditure management, digitizing operations, and supply-demand disarray. In this context, it suggests solutions that will help businesses sustain their profitability in the coming years.

Importantpointers from the Continuous Integration Software market report:

After-effects of COVID-19 on industry remuneration.
Predicted growth rate of the market and sub-markets.
Key market trends.
Opportunity windows.
Merits and demerits of indirect and direct sales channel.
Leading traders, suppliers, and dealers.
Continuous Integration Software market segments covered in the report:

Regional bifurcation: North America, Europe, Asia-Pacific, South America, Middle East & Africa

Scrutiny of each regional market at country-level.
Total revenue of each region.
Market share of each geography.
Estimations regarding the growth rate of every regional market over the predicted timeframe.
Product types:

Cloud Based and Web Based
Sales, market share, and revenue of each product segment.
Pricing pattern of each product type.
Application spectrum:

Large Enterprises and SMEs
Overall sales and revenue accumulated by each application segment.
Product pricing in terms of application scope.
Competitive dashboard:

CircleCI
Jenkins
Codeship
Travis CI
Semaphore
Bitrise
TeamCity
Bamboo
Puppet Pipelines
AWS
Hudson and Chef
Product and services offered by top market players.
Manufacturing facilities of leading industry players across the serviced regions.
New and emerging players in the marketplace.
Total market share, revenue, pricing patterns, gross margins, and overall sales of the listed companies.
SWOT analysis of the major companies.
A detailed briefing of the market concentration ratio, commercialization rate, and popular business strategies.
Key Highlights in Connected Worker Market Report:

North America, Europe, Asia Pacific, Middle East & Africa, Latin America market size (sales, revenue and growth rate) of Continuous Integration Software industry.
Global major manufacturers’ operating situation (sales, revenue, growth rate and gross margin) of Continuous Integration Software industry.
Global major countries (United States, Canada, Germany, France, UK, Italy, Russia, Spain, China, Japan, Korea, India, Australia, New Zealand, Southeast Asia, Middle East, Africa, Mexico, Brazil, C. America) market size (sales, revenue and growth rate) of Continuous Integration Software industry.
Different types and applications of Continuous Integration Software industry, market share of each type and application by revenue.
Global market size (sales, revenue) forecast by regions and countries from 2015 to 2020 of Continuous Integration Software industry.
Upstream raw materials and manufacturing equipment, industry chain analysis of Continuous Integration Software industry.
SWOT analysis of Continuous Integration Software industry.
New Project Investment Feasibility Analysis of Continuous Integration Software industry.

Microsoft this week described a few security products that have reached “general availability” (GA) or commercial-release status, while also touting its overall security-market position.

Reaching GA are some Azure Security Center capabilities, Azure Defender for IoT and Application Guard for Office. These releases were announced on Wednesday. On Tuesday, Microsoft’s security-business prowess was highlighted in the company’s fiscal-year 2021 Q2 earning report given by Satya Nadella, Microsoft’s CEO. He noted that Microsoft’s security solutions revenue recently surpassed $10 billion.
A transcript was needed since a near-eight-minute gap occurred during the Tuesday presentation.

Microsoft’s $10 billion security revenue figure was enough for researchers at analyst and consulting firm Forrester to declare that “Microsoft is now a cybersecurity behemoth.”
Security Stats
Microsoft security stats were touted in a Wednesday announcement by Vasu Jakkal, Microsoft’s corporate vice president for security, compliance and identity. She offered the following security highlights:

Microsoft Defender blocked “almost six billion malware threats” in 2020.
Microsoft Defender for Office 365 blocked “more than 30 billion email threats” in 2020.
Azure Active Directory processes “more than 30 billion authentications” per day.
Azure Sentinel “analyzes over 4 petabytes of data each month.”
Microsoft solutions are protecting “more than 400,000 customers across 120 countries.”
Jakkal suggested that no other software company was handing “security, compliance, identity, and management as an interdependent whole.”

“Microsoft’s security organization is an intense, massive collaboration that drives services, intelligence, technologies, and people — all coming together as one humming machine with a singular mission,” she added.

Application Guard for Office GA
Application Guard for Office is Microsoft’s more improved approach for dealing with malicious files found on Web sites and in e-mail attachments. The product reached GA status, Microsoft announced on Wednesday. It had been at the preview stage back in August.

Microsoft has long had a Protected View security mechanism that mainly just acts as a precaution when users attempt to open documents attached in e-mails. Protected View permits end users to turn on editing in the documents, which can also enable attacks. With Application Guard for Office, these files get opened in a virtual machine “sandbox” environment, namely a “Hyper-V-enabled container,” which is isolated and prevents any malware from spreading into systems.

Despite the product’s name, Application Guard for Office is just for subscribers to the Office 365 service. Additionally, organizations can only get Application Guard for Office when they subscribe to E5-type plans, a top pricing option. Microsoft’s announcement also noted that “Application Guard works in conjunction with Microsoft Defender for Office 365,” a security solution that’s part of the newly renamed Microsoft Defender product line. Other security components in Microsoft Defender for Office 365 include “Safe Attachments, Safe Links, and Safe Documents,” the announcement explained.

Microsoft’s announcement affirmed that Application Guard for Office won’t be turned on by default for licensees:

Azure Security Center Enhancements
The Azure Security Center portal now has multicloud management capabilities, with the ability to work with Amazon Web Services (AWS) and Google Cloud Platform (GCP) reaching GA status, Microsoft announced on Wednesday.

It seems that just some capabilities are at GA in Azure Security Center, though. Microsoft specifically pointed to the ability to show AWS and GCP misconfigurations in its “Secure Score Model and Regulatory Compliance” features as being available.

Microsoft additionally turned on “Azure Security Benchmark as the default security policy for Azure Security Center,” which is conceived as bolstering its recommended policy settings.

Also at GA is the ability to use Azure Defender for Servers with Microsoft’s Azure Arc product to “simplify the on-boarding and security of virtual machines running in AWS, GCP and hybrid clouds.” Azure Arc is Microsoft’s multicloud management portal that also supports on-premises implementations, per a Microsoft “Overview” document. Azure Defender for Servers appears to be a component of the Microsoft Defender for Endpoint security solution. It’s tersely described in this Microsoft document as adding “threat detection and advanced defenses for your Windows and Linux machines.”

In response to customer feedback, Microsoft now lets organizations “exempt resources” from Secure Score “at a subscription level and now at a management group level.” Secure Score is Microsoft’s security assessment service. Some organizations apparently requested this exemption because they are using “third-party technology” (non-Microsoft solutions) for their security-posture assessments.

Azure Defender for IoT GA
Microsoft also announced on Wednesday that Azure Defender for IoT, its agentless security solution for unmanaged “Internet of things” devices and so-called “operational technology endpoints,” has reached GA status. It had been at the public preview stage back in October. The solution is designed to work with devices that use “specialized industrial protocols such as Modbus, DNP3, and BACnet.”

Azure Defender for IoT works with Microsoft recently acquired CyberX technologies to discover devices, find vulnerabilities and perform continuous device monitoring. Governance details are handled, too, when the service is used with a security information and event management solution, such as Microsoft’s Azure Sentinel. It also works with “Splunk, IBM QRadar and ServiceNow” solutions.

Azure Defender for IoT can be used on a customer’s site, or it can be tapped as an Azure service. The latter approach lets organizations connect Azure Defender for IoT with Microsoft’s Azure Defender security services. Alternatively, there’s a “hybrid” deployment possibility, “where security monitoring is performed on-premises but selected alerts are forwarded to a cloud-based SIEM like Azure Sentinel,” the announcement explained.

A Digital Life Erased in Minutes: The Mat Honan Incident

In August 2012, Mat Honan — then a senior writer at Wired magazine — had his entire digital life wiped out in a single afternoon. While he was at home with his young daughter, his iPhone suddenly went blank. When he tried to restore it, every screen led back to a factory-reset welcome prompt. His MacBook followed. His Gmail and Twitter accounts were taken over in quick succession.

Years of personal data — family photographs, work correspondence, notes — were gone. He had backed up his iPhone to iCloud faithfully, but when he tried to log in, his password was rejected. The backups were unreachable.

How the Attacker Did It: Social Engineering, Not Sophisticated Hacking

When Honan contacted Apple support, he discovered that a caller had already rung 30 minutes earlier. At the time, Apple’s account-recovery process required only a mailing address and the last four digits of a credit card number. Honan’s address was publicly available on his personal website. The attacker obtained the last four digits of his credit card by calling Amazon customer support and exploiting a gap in its verification process — Amazon, at the time, would add a new credit card to an account with minimal verification, then reveal the last four digits of cards on file to anyone who called.

Armed with those four digits, the attacker called Apple, passed the security check, and reset the Apple ID password. Because Honan’s iCloud email pointed to his Gmail, and his Gmail recovery pointed back to his Apple ID, the attacker could cascade through every linked account. The lesson is stark: account chaining — where one compromised credential unlocks others — multiplies the blast radius of even a basic breach.

Honan later made contact with the teenager responsible. The motive? The attacker simply wanted Honan’s short, desirable Twitter handle. An entire digital life was destroyed for a username.

What Is Cloud Computing?

In computing, the cloud refers to the practice of storing and processing data on remote servers managed by a third-party hosting provider, rather than on local hardware. Users access their data and applications over the internet.

At a consumer level this means:

• Photos backed up to iCloud, Google Photos, or Amazon Photos
• Email stored on Google’s or Microsoft’s servers
• Documents synced via Dropbox, OneDrive, or Google Drive
• Software delivered as a subscription (SaaS) rather than installed locally

At an enterprise level it means running workloads, databases, and applications on infrastructure provided by Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, or similar providers — paying for capacity as consumed rather than purchasing and maintaining physical servers.

The Core Service Models

• Infrastructure as a Service (IaaS): Raw compute, storage, and networking (e.g., AWS EC2, Azure VMs).
• Platform as a Service (PaaS): Managed runtime environments for deploying applications without managing the underlying OS (e.g., AWS Elastic Beanstalk, Google App Engine).
• Software as a Service (SaaS): Fully managed applications delivered over the web (e.g., Salesforce, Gmail, Microsoft 365). Users rent access rather than purchasing a licence.

Why Organisations Adopt Cloud

The business case for cloud adoption is well established:

• Reduced capital expenditure: No upfront hardware purchase; operational costs scale with usage.
• Elasticity: Resources can be provisioned or released on demand to match workload spikes.
• Geographic reach: Data can be replicated across regions for resilience and low-latency access.
• Managed security baseline: Major providers invest heavily in physical security, certifications (ISO 27001, SOC 2, FedRAMP), and infrastructure-level protections that most organisations could not replicate in-house.

Amazon Web Services, Microsoft Azure, and Google Cloud are the three largest public cloud providers by market share. AWS has been consistently profitable and a major revenue contributor to Amazon’s overall business. Microsoft signalled its commitment to cloud early, shifting a significant portion of its R&D budget toward cloud products in the early 2010s.

The Real Risks: Where Cloud Security Falls Short

Centralising data in cloud environments creates attractive, high-value targets. The shared-responsibility model — where the provider secures the infrastructure and the customer secures what runs on it — is frequently misunderstood, leaving critical gaps.

1. Data Breaches

When cloud accounts or providers are compromised, attackers can exfiltrate email addresses, credit card numbers, passport details, biometric data, and private messages. Several high-profile cases illustrate the scale:

• iCloud celebrity photo leak (2014): Nude photographs of multiple celebrities were posted online. Apple determined that the images were obtained through targeted spear-phishing attacks against individual accounts, not a systemic iCloud infrastructure breach — a distinction that matters because it shifts blame to weak account-recovery practices rather than server security.
• Marriott Starwood (disclosed 2018): Marriott revealed that its Starwood guest reservation database had been compromised. The records of up to approximately 327 million guests were potentially affected, with exposed data including names, addresses, phone numbers, email addresses, passport numbers, and dates of birth.
• Cambridge Analytica / Facebook (2018): Cambridge Analytica, a political consulting firm, harvested data from approximately 87 million Facebook users — data collected via a third-party quiz app that exploited Facebook’s API permissions at the time. This data was used to build political profiles and target advertising. The incident led to a US Congressional investigation and Mark Zuckerberg’s testimony before the Senate.
• Aadhaar data exposure: Reported breaches involving India’s Aadhaar biometric identity system exposed personal information — including unique 12-digit identity numbers, names, and linked service details — for a very large number of Indian citizens. The exact scope and nature of these incidents has been disputed between security researchers and the Unique Identification Authority of India (UIDAI).

2. Business Destruction: The Code Spaces Case

Code Spaces, a code-hosting and project-management service, was put permanently out of business by a single cloud security incident. An attacker gained access to Code Spaces’ AWS control panel and issued a ransom demand. When the company refused to pay, the attacker systematically deleted data, machine images, backups, and configuration snapshots until virtually nothing recoverable remained. The company shut down days later. This case is a canonical example of why cloud accounts themselves must be hardened with multi-factor authentication and why backups must live in a separate account with separate credentials.

3. Availability and Denial-of-Service Risks

Cloud-hosted services depend on internet connectivity and the provider’s infrastructure remaining available. Distributed Denial-of-Service (DDoS) attacks against a provider or its DNS infrastructure can make services temporarily unreachable. Major cloud providers have had outages that took down large portions of the internet-facing web. For businesses that have migrated all operations to the cloud without adequate fallback planning, such outages can halt revenue-generating activity entirely.

4. Insider Threats and Third-Party Data Sharing

Cloud providers employ administrators with privileged access to infrastructure hosting customer data. The risk of a malicious or coerced insider is real. Additionally, most cloud providers’ terms of service include clauses allowing data disclosure to law enforcement or government authorities under specified conditions. Dropbox’s privacy policy, for instance, explicitly states that it may disclose user information to comply with law, prevent serious harm, prevent fraud or abuse, or protect its property rights. Businesses storing sensitive data in the cloud should read these terms carefully and understand what data sovereignty obligations apply under their jurisdiction.

The Account-Chaining Problem

Honan’s case illustrates a structural weakness that remains common today: accounts are linked together in ways users do not fully appreciate.

• A cloud storage account may use the same email address as a banking app.
• A password manager’s master account may share a recovery email with a social media profile.
• A single credit card number on file at two services can be used to social-engineer both.

Attackers map these relationships and exploit the weakest link. A sophisticated password is irrelevant if the account-recovery path bypasses it.

Practical Steps to Reduce Cloud Risk

For Individuals

• Enable multi-factor authentication (MFA) on every account that supports it — especially email, cloud storage, and financial services. Hardware security keys (FIDO2/WebAuthn) provide stronger protection than SMS-based codes.
• Use unique passwords for every service, managed with a reputable password manager.
• Audit account recovery settings. Remove phone numbers used as recovery options if they are not strictly needed. Ensure recovery email addresses are themselves secured with MFA.
• Keep at least one offline or air-gapped backup of irreplaceable data (photos, documents). A cloud backup is not a substitute for a local backup if the cloud account itself can be locked or wiped.
• Be sceptical of phishing. Most high-profile account compromises begin with a convincing phishing email, not a technical infrastructure exploit.

For Organisations

• Apply the principle of least privilege. Cloud IAM roles and policies should grant only the permissions a workload or user actually needs.
• Enable MFA on all cloud console and API access, especially for privileged roles.
• Segregate backups into a separate account with separate credentials, so that a compromised production account cannot destroy backups.
• Enable audit logging (AWS CloudTrail, Azure Monitor, GCP Cloud Audit Logs) and alert on anomalous activity such as large-scale delete operations or unusual login geolocations.
• Understand the shared-responsibility model for your chosen cloud provider. Encryption, access control, and application-layer security remain the customer’s responsibility even when running on managed infrastructure.
• Have and test an incident response plan that includes cloud-specific scenarios: account takeover, data exfiltration, and ransom-driven deletion.
• Use Cloud Security Posture Management (CSPM) tools to continuously audit configurations for drift from security baselines.

Breach Notification: A Legal and Ethical Obligation

When a cloud provider or cloud-hosted service is breached, the people most harmed are often the end users whose data was stolen — not the company itself. Yet terms of service agreements frequently limit the provider’s liability to subscribers. Many jurisdictions have responded with mandatory breach-notification laws. The United States has state-level breach notification requirements (with California’s CCPA among the most stringent), while the European Union’s GDPR mandates notification to supervisory authorities within 72 hours of discovery and notification to affected individuals without undue delay. Organisations operating in multiple jurisdictions need to understand which obligations apply to them.

Conclusion: The Cloud Is a Tool, Not a Safety Net

Cloud computing is not inherently unsafe — for many workloads, a well-configured cloud environment is more secure than an equivalent on-premises setup. The danger lies in misunderstanding what the cloud does and does not protect. Centralising data on remote servers run by a third party creates real efficiencies and real risks in equal measure.

Mat Honan’s experience remains relevant because the attack vector he fell victim to — social engineering of customer service staff, account chaining, weak recovery processes — is still common. Technology evolves; human factors are slower to change.

Whether the cloud represents a silver lining or a gathering storm depends almost entirely on the security practices of those who use it. Strong authentication, disciplined access control, segregated backups, and a clear understanding of contractual terms are not optional extras — they are the minimum baseline for anyone entrusting data to the cloud.

Original article sourced from deccanchronicle.com. The Mat Honan incident was covered in detail by Wired magazine.

Like many vendors in the space of software development tools and services, GitLab, which made its name with version control, is looking to automate and consolidate continuous integration/continuous deployment that comes with software development into a single lifecycle, in order to help organizations rapidly develop, fix and update their software stacks.

“Cycle time compression is the key to business success. Almost every improvement you need to make must be done in software,” GitLab CEO  Sid Sijbrandij said during the company’s GitLab Commit Brooklyn event, held Wednesday in New York. And indeed the conference highlighted, reviewed, and predicted many of the ways that a build process, such as one based on GitLab, could be extended and automated to support many additional aspects of IT, such as governance, data operations, and security, as well as to automate as much as possible the building and deployment of applications.

Sijbrandij admitted that the company was not quite there, in terms of offering a complete integrated suite to handle all aspects of software development, though he touted the company’s aggressive schedule to build out features quickly. The range of tools needed would span a lot of different products lines as we now know them: Planning, code management, creation, verification, packaging, security, release management, configuration, and monitoring.

Not all this work will come in-house, though. For instance, the company partnered with HashiCorp to make it easy for operations teams to manage their infrastructure configuration in GitLab, which then can be executed by TerraForm Cloud. GitLab is also bringing HashiCorp’s Vault secrets management tool into the fold as well, giving developers a programmatic way to ensure the security of their distributed applications.

DevSecOps

In one demonstration of upcoming technologies, Mark Pundsack, GitLab vice president of product strategy, showed how GitLab automation could tighten security. One of the biggest issues that organizations face today is that of bugs and security vulnerabilities in third-party packages that have been embedded in their own software (“dependencies”). Once software has been shipped, how do you know which dependencies are being used, much less tell if they are still secure?

This feature now being internally prototyped would automatically check if the dependency packages are vulnerable, and temporarily stop the build, if they are. Better yet, the company is also planning a feature that would automatically initiate a build and merge an updated dependency into an existing program, and roll it back if it did not work as expected. While these automated merges may not work for all cases, Pundsack warned, they could work for the majority of them, allowing developers to manage-by-exception, an approach that is usually a time-saver.

Data operations (“DataOps”) could be another area that would benefit from automation and version control. In an afternoon panel, data practitioners talked about the limits of current DataOps practices, and why data couldn’t be managed in similar CI/CD pipelines. Fishtown Analytics‘ Claire Carroll pointed out at most companies, analysts have so many formatting quirks for the data models they use, and often they’re the only ones in the org who know these rules, that it can be a bottleneck. In the panel, GitLab Analytics Data Engineer Emilie Schario recalled that she was once at a job where she spent 80% of her time reconciling two spreadsheets from two execs reporting on the same sales data. “I spent way too much time trying to figure out what was going on.”

GitLab’s own Data Team uses the standard GitLab CI/CD tools to manage all of its own data, both the data models and the source data itself, Schario explained after the panel. No special tools required. Version control can be immensely handy in tracking data as it moves across the enterprise, when conflicting versions of, say, a PowerPoint Presentation may cause issues, noted another panelist, Danielle Morrill, the general manager for the DataOps-focused GitLab startup Meltano.

“I think there is a lot to be said for version control, not just as a working tool, but as a communication tool,” Morrill said.

Field of Opportunity

No doubt, the field of CI/CD is hot, not the least because it is a necessary precursor to cloud native computing, as The Cloud Native Computing Foundation CEO Dan Kohn discussed in his talk. This week, GitLab announced that it has procured a $268 million Series E round of fundraising, pushing the company’s value to its investors up to $2.75 billion, so investors are clearly seeing a growing use of CI/CD. Certainly, the company has many customers who see the need for expanding their software development automations and governance through tools and services.

During the morning’s keynotes, Jasmine James, who’s the Delta Air Lines IT Manager in the company’s DevOps Center of Excellence, explained how the airline found that cloud native computing would help put the company on a path forward to a more customer-centric approach to its business, promising the agility to offer personalized service, easier check-in, better flight rescheduling and other benefits to flyers. Historically, the biggest bottleneck in providing these sorts of benefits has been the infrastructure, she noted.

Financial investment firm Goldman Sachs is moving from supporting 10 separate software development lifecycles for all of its applications to a central GitLab-based one, a migration it hopes will set the stage for more agile use of the cloud, noted Goldman Sachs Vice President and Technology Fellow George Grant, in another talk. Within two weeks of setting up the internal services, over 1,600 Goldman Sachs developers started using the git-based service, without prompting, he noted.

Pivotal Application Service for Kubernetes: Dropping the VMware Requirement

Pivotal’s alpha release of the Pivotal Application Service (PAS) for Kubernetes shipped with a dependency on VMware infrastructure—a deliberate shortcut to accelerate time-to-market. According to Ian Andrews, Pivotal’s senior vice president of products, that dependency will not survive into the generally available release.

“The only reason the alpha was tied to a number of components was to bring it to market quickly,” Andrews told The Register during the Cloud Foundry Summit in The Hague, Netherlands.

PAS is one of several certified distributions of the open-source Cloud Foundry platform. At the time of the interview (September 2019), no general availability date had been announced for PAS on Kubernetes. Andrews indicated that Pivotal planned at least two more preview releases before year-end: one at the SpringOne Platform conference in October and another toward the end of 2019.

Investor Pressure vs. Real-World Kubernetes Adoption

Pivotal faced significant investor pressure to accelerate its Kubernetes strategy, with critics arguing the company was falling behind the broader ecosystem. Andrews pushed back on the urgency, drawing a distinction between market narrative and actual production adoption.

“The urgency was more around understanding the long-term vision than an immediate need,” he said. “We’re still very early. Everybody is talking about K8s all the time, but if you look at who is actually using it in production, the list is much shorter. Our technology stack works incredibly well—we have customers with over 100,000 containers running on the current platform. If we forecast out three to five years, though, it seems clear that Kubernetes is going to be a de facto component in the architecture.”

Kubernetes as a Universal Infrastructure API

Andrews articulated a longer-term architectural view: Kubernetes will eventually recede into the infrastructure layer itself, replacing the distinct conceptual separation between VMs, storage, networking, and an orchestration tier sitting above them.

“In the future, Kubernetes will exist as an infrastructure API almost universally,” he said. “VMware has introduced Project Pacific. Now you have a consistent way to provision resources and infrastructure, do health management, updates, and scheduling. The operational complexity of the landscape goes way down.”

Project Pacific, announced at VMworld 2019 in San Francisco, integrates Kubernetes directly into vSphere. Andrews framed it as an early signal of a broader trend: “Today we think about VM hosts, storage, networking, and then Kubernetes as a thing that deploys on top of that. Potentially that becomes the only API that you see.”

The VMware Acquisition and the Multicloud Thesis

At the time of the interview, Pivotal was in the process of being acquired by VMware—notable given that both companies were already under common Dell ownership. Andrews used the opportunity to explain how Pivotal’s culture had historically differed from VMware’s, and why the two companies had converged.

“When Pivotal was created in 2012, both EMC and VMware were really trying to figure out their next chapter. VMware had built a franchise inside the data centre, but the public cloud story was very uncertain. For a time they were fighting against it. For the team at Pivotal, it was clear that most of the world would end up with some on-premises, some public cloud, maybe multiple public clouds—but we didn’t have an invested franchise we were attempting to protect.”

He noted that a similar dynamic played out at the container layer: “First VMware was defensive, and this is now a core part of their strategy. Over the last year we’ve aligned on the way we see the world. It’s multi-cloud, it’s container-centric. That opened the opportunity to come back as one company.”

Spring Framework Integration and Reactive Programming

Pivotal is also the steward of the Spring Framework, one of the most widely used Java application frameworks. Andrews acknowledged that PAS includes some Spring-specific integrations—primarily around distributed tracing and metrics collection—but emphasized that the deeper investment has been at the architectural level.

“We’ve been doing a lot of work in Spring to add support for reactive programming, that historically Java was very poor at,” he said. “That’s allowed us to start thinking about real-time stream processing with Kafka. If you compare the number of developers writing for Spring to the number of Pivotal customers, the first far outstrips the second. But if you choose to deploy on our platform, there’s a simplification.”

Competing on Multicloud Portability Against Hyperscaler Lock-In

Removing the VMware dependency from PAS for Kubernetes means the platform will be deployable on any conformant Kubernetes environment—including Amazon EKS, Google GKE, and Microsoft AKS. Each of those hyperscalers also offers its own managed application services, creating an obvious competitive tension.

Andrews argued that Pivotal’s multicloud portability is a differentiator the hyperscalers structurally cannot match. “We have great relationships with Microsoft, we’ve done a lot of engineering work with Google, we have lots of customers running on Amazon—but they also have products that sit in our space. Our ability to give customers a way to migrate between clouds is antithetical to their approach, which is ‘Get the workload on our cloud and lock it in there forever.'”

The Decline of Imperative Automation Tools

Andrews offered a pointed view on the future of traditional configuration management tools such as Chef, Puppet, and OpsWare—the last of which was where he began his career.

“The model we took [at OpsWare] was: whatever the human had been doing before, we’re going to put that in a script, they’ll be an agent, and we can execute those tasks,” he explained. “If you look at the state of the art today, there is no human building little command scripts that say, ‘When the container fails, respawn another container on a different host.’ It’s built into the system.”

The shift, in his view, is from imperative scripting to declarative intent: operators specify the desired state—for example, “always run three replicas of this container on separate hosts”—and the platform enforces it continuously, without human intervention for routine operations.

“It’s a different model of automation that is necessary for the current scale of operation. We’re now at a scale that is too massive for humans to touch. The paradigm that Puppet, Chef, or OpsWare represents is just completely ineffective,” said Andrews.

Key Takeaways for DevOps Engineers

• PAS for Kubernetes was in alpha at the time of this interview, with the VMware dependency flagged as a temporary shortcut—not an architectural requirement.
• Kubernetes as infrastructure API: The longer-term vision is that Kubernetes (or its successor) becomes the single control plane for compute, storage, and networking, reducing operational complexity.
• Multicloud portability remains Pivotal’s/Cloud Foundry’s core competitive differentiator against hyperscaler-native platforms.
• Reactive Spring and Kafka integration reflects a shift toward event-driven, stream-processing architectures in enterprise Java.
• Declarative over imperative automation: At cloud-native scale, desired-state systems supplant script-based configuration management tools.

This article is based on an interview originally published by The Register in September 2019. It reflects the state of Pivotal, VMware, and the Kubernetes ecosystem at that time. Significant changes have occurred since, including the completion of the VMware acquisition of Pivotal and subsequent portfolio changes.

What Is Application Hosting?

Application hosting refers to the infrastructure, platforms, and managed services that allow organizations to deploy, run, and scale software applications without owning or operating the underlying physical hardware. It spans a wide spectrum — from traditional shared hosting and dedicated servers to fully managed cloud platforms, containers-as-a-service, and serverless compute environments.

For DevOps and platform engineering teams, the choice of application hosting provider directly affects deployment velocity, availability SLAs, cost efficiency, and the operational burden carried by internal teams.

Major Players in the Application Hosting Market

The market is dominated by a handful of hyperscale cloud providers, alongside established managed hosting specialists. Key vendors commonly cited in industry analyses include:

• Amazon Web Services (AWS) — The largest public cloud provider by market share, offering EC2, Elastic Beanstalk, ECS, EKS, Lambda, and a broad suite of managed database and API services.
• Microsoft Azure — A strong enterprise choice with deep integration into Active Directory, Office 365, and hybrid environments; offers App Service, AKS, and Azure Functions.
• Google Cloud Platform (GCP) — Known for Kubernetes (which Google originally developed), BigQuery, and Cloud Run; competitive in data-heavy and AI/ML workloads.
• IBM Cloud — Focused on regulated industries, hybrid cloud (via Red Hat OpenShift), and enterprise middleware workloads.
• Rackspace Technology — A managed hosting and multi-cloud services provider; differentiates on professional services and managed operations layered on top of AWS, Azure, and GCP.
• Liquid Web — Targets SMB and mid-market customers with managed WordPress, WooCommerce, and VPS hosting.

Competition among these vendors is intensifying through continuous feature releases, pricing reductions, and strategic acquisitions — making provider evaluation an ongoing activity for engineering and procurement teams.

Key Service Segments

Application hosting is not a monolithic category. Market analyses typically break it into functional segments:

API Management

API management platforms — such as AWS API Gateway, Azure API Management, Google Apigee, and Kong — handle traffic routing, authentication, rate limiting, versioning, and developer portal functionality. As microservices architectures proliferate, API management has become a core part of the hosting stack rather than an optional add-on.

Database Administration

Managed database services (Amazon RDS, Aurora, Azure SQL Database, Cloud SQL, IBM Db2 on Cloud) remove the operational burden of patching, failover, and backup management from application teams. This segment is growing rapidly as organizations move away from self-managed database servers.

Backup and Recovery

Integrated backup, snapshot, and disaster recovery services are increasingly bundled with hosting offerings. Tools like AWS Backup, Azure Site Recovery, and Veeam on cloud infrastructure allow teams to meet RPO/RTO targets without maintaining separate backup infrastructure.

Enterprise vs. SMB Use Cases

Market demand for application hosting breaks along organizational size:

• Small and Medium Enterprises (SMEs) — Typically prioritize ease of use, predictable pricing, managed services that reduce the need for specialized DevOps staff, and strong support SLAs. Providers like Rackspace, Liquid Web, and platform-as-a-service offerings from the hyperscalers serve this segment well.
• Large Enterprises — Require advanced networking controls (VPCs, private interconnects), compliance certifications (SOC 2, ISO 27001, FedRAMP, HIPAA), multi-region redundancy, and enterprise support agreements. AWS, Azure, Google Cloud, and IBM Cloud compete directly in this space.

Regional Market Dynamics

Adoption patterns and provider preferences vary significantly by geography:

• North America (US, Canada, Mexico) — The most mature market; AWS and Azure have the deepest infrastructure footprints. Regulatory frameworks like CCPA in California add compliance requirements that shape hosting decisions.
• Europe (Germany, France, UK, Italy, and others) — GDPR compliance and data residency requirements drive demand for providers with certified EU data centers and robust data processing agreements. Sovereign cloud offerings are gaining traction.
• Asia-Pacific (China, Japan, India, South Korea, Southeast Asia) — One of the fastest-growing regions; local regulations (particularly in China) require localized infrastructure. Alibaba Cloud and Tencent Cloud are significant regional players alongside the global hyperscalers.
• South America and Middle East/Africa — Emerging markets with growing cloud adoption; latency and data sovereignty concerns are driving hyperscalers to build new regional availability zones.

Key Drivers Shaping the Market

Several forces are accelerating growth in application hosting:

• Digital transformation initiatives — Organizations across industries are migrating on-premises workloads to cloud hosting to reduce capital expenditure and improve agility.
• Microservices and containerization — Kubernetes-based hosting (EKS, AKS, GKE) has become a standard deployment pattern, increasing the sophistication of what teams expect from hosting providers.
• Serverless adoption — Functions-as-a-service reduce infrastructure management overhead, attracting organizations that want to focus entirely on application code.
• Edge computing — CDN and edge compute offerings (AWS CloudFront + Lambda@Edge, Cloudflare Workers, Azure CDN) extend hosting closer to end users, reducing latency for global applications.
• Multi-cloud strategies — Risk mitigation and vendor leverage are driving enterprises to distribute workloads across two or more providers, creating demand for abstraction layers and managed multi-cloud services.

Competitive Pressures and Market Challenges

The application hosting market is not without friction:

• Vendor lock-in — Proprietary managed services create switching costs that can limit future flexibility. Teams using Aurora, Azure Cosmos DB, or Cloud Spanner face significant re-engineering effort if they change providers.
• Cost management complexity — Cloud pricing models are complex, and egress charges in particular can make real-world costs significantly higher than initial estimates.
• Security and compliance — Shared responsibility models mean that misconfigurations by customer teams remain a leading cause of cloud security incidents.
• Skills gap — Smaller organizations often lack the cloud-native expertise needed to fully leverage managed hosting platforms, creating a market for managed service providers (MSPs) like Rackspace.

What Engineering Teams Should Evaluate

When selecting an application hosting provider or re-evaluating an existing contract, consider the following:

1. Compute and networking options — Does the provider offer the instance types, GPU availability, and networking constructs (VPCs, private peering, transit gateways) your applications require?
2. Managed service breadth — Are the database, message queue, caching, and API gateway services mature enough to replace self-managed equivalents?
3. Compliance certifications — Does the provider hold the certifications relevant to your industry (HIPAA, PCI DSS, FedRAMP, SOC 2 Type II, ISO 27001)?
4. SLA terms — What are the published availability commitments, and what credits are available if they are missed?
5. Support model — Is enterprise support included or an additional cost? What are the response time commitments for critical incidents?
6. Total cost of ownership — Model full costs including compute, storage, data transfer, support tiers, and any third-party tooling required to fill gaps.

Summary

The application hosting market is large, competitive, and technically complex. AWS, Microsoft Azure, Google Cloud, IBM Cloud, Rackspace, and Liquid Web each serve distinct segments with different priorities around price, managed services, compliance, and support. For DevOps and platform teams, understanding the segmentation — across API management, database administration, backup and recovery, and compute — is essential for making informed infrastructure decisions that align with both technical requirements and business constraints.

As organizations continue migrating workloads and adopting cloud-native architectures, the selection and ongoing governance of application hosting providers will remain a high-stakes engineering and business decision.

Effective collaboration between team members has always been a critical factor in developing a productive environment for any organization. In the past few years, with the boom in work-from-home culture and innovative concepts of remote working teams, need for having a smooth communication and collaboration among the team members has become a necessity for an organization to carry over its operations efficiently. And this becomes all the more important when people from different domains are working together, like the members from the development and operations team. Any organization having such team structures need to ensure quick and effective communication between team members while ensuring strict monitoring of the project progress and quality to meet the client expectations. Fortunately, such effective coordination and management have been made possible with the help of technology. There are a large number of tools available that can help you establish better coordination and overcome the difficulties involved in such tasks. Here are a few tools that you can try out to help you enhance the collaboration within your DevOps teams.

Slack

Slack, the near-universal collaboration platform developed by the U.S. software company Slack Technologies, provides a set of tools like direct messaging, audio/video calls, and document sharing to help enhance the team collaboration. Besides group and individual chats, Slack offers some attractive capabilities like inline replies, mobile versatility, and integration with a large number of third-party services like GitHub, Dropbox, Box, Google Drive, Heroku, IBM Bluemix, Zendesk, Trello, Crashlytics, Runscope, and Zapier. Slack is a freemium product. This means that you can use several of its features for free, while some enhanced features like support for an unlimited number of users and application integrations can be enjoyed at a premium price. For this reason, Slack has gained good popularity among teams of all sizes, be it enterprises, small organizations, or individuals.

Microsoft Teams

Microsoft Teams is the unified communications platform that offers a wide range of collaborative features for teams of all sizes. It is available with the Microsoft Office 365 subscription as well as an independent application for Windows, macOS, iOS, Android, Windows 10 Mobile and Windows Phone 8.1 Web App. Being part of the Office 365 productivity suite, it has native support for all the productivity apps, including Skype voice and video calls. Additional extensions allow integration with other non-Microsoft products as well.

Story of the evolution of this product is as interesting as its features. In 2016, Microsoft’s $8 billion bid to acquire Slack didn’t turn out well, as Bill Gates was in favor of making improvements to Skype for Business. Gradually, Microsoft Teams grew into a unified platform, combining the product lines Office 365 for Education (in May 2017) and then Skype for Business (in September 2017). While Microsoft Teams kept growing by having tighter integration with Microsoft products, its competitor Slack kept making enhancements towards tighter integration with Google’s collaboration product suite. The Microsoft Teams vs. Slack battle will only get hotter this year.

GitHub

GitHub is the largest online open-source code repository, with several collaboration capabilities like task management, bug tracking, and dedicated project wikis, etc. GitHub, the US-based multinational organization, was acquired by Microsoft in 2018 for $7.5 billion. It provides excellent support for different kinds of project collaboration activities. It leverages Git (a distributed version control system) to provide a hosted environment for tracking changes to any set of files, including documents and program codes. In addition to all the core version control functionalities of Git such as distributed version control and source code management (SCM), GitHub also offers its features like access control for added security. GitHub offers its services in three subscription offers: free, professional, and enterprise. While the content of free subscription is shared publicly, private repositories with managed permissions are available with professional and enterprise accounts.

Basecamp

Basecamp is a project management tool that helps teams collaborate and communicate over project milestones. Launched in 2004, the Basecamp tool allows the team leaders to create to-do lists, file sharing, forum-like collaboration with threaded message boards, schedule management, file sharing, and time tracking. It is also supported by a chat capability (formerly known as Campfire, later merged into the core product with version Basecamp 3 onwards). Initially launched as a web-based tool, Basecamp apps are now available for web, iOS, Android, Mac, and PC. It is popular among freelancers, small shops, midsized companies, as well as multinational organizations. It is not available as a freemium product, although you can check it out using the free trial.

Jira

Jira, the project management and tracking tool developed by the Australian Software company Atlassian, can be a good way to keep good coordination between the developers, testers, project managers, and other stakeholders. Teams of all sizes can use Jira to collaborate on various project management tasks like bug tracking, issue tracking, and build management. Jira can be used to develop custom workflows and project matrix tracking. It can be integrated with a variety of source control programs, like Git, Perforce, Clearcase, and Team Foundation Server. Atlassian has made available the full source code of Jira for academic and commercial customers under a developer source license. It also provides a free version to some organizations that meet certain criteria (non-profit, non-political, non-governmental, and non-academic organizations).

Workplace by Facebook

Workplace by Facebook is an enterprise-level collaborative platform developed by the social media titan. It comes with a unique combination of user experience of Facebook (the social media platform) with support for additional enterprise-grade collaboration and management features like project groups and teams, administrative support and dedicated storage space for the projects. Workplace also allows your employees to collaborate with external teams, like clients, partners, and suppliers (having their Workplace accounts) using private chats and secure video calls. It also offers integration with a wide variety of authentication services and platforms, including Active Directory, Windows Azure AS, and Okta.

Besides the usual features like group chats, instant messaging and news feed, it also offers additional attractive features like Live Video broadcast directly using mobile phones and real-time feedback in the form of comments and reactions. It is available in two pricing options, Workplace Standard (free) and Workplace Premium.

Trello

Trello is a to-do list-based collaboration tool that allows DevOps teams to use shared lists, groups, and cards in an easy to use fashion. It offers a single view of the entire project status, including the activities that in-progress, already completed, and yet to start, in the form of a single manageable whiteboard. Each individual task can have attached files or images, and they can also be directly linked to other data sources like BitBucket or Salesforce, along with capabilities to comment and collaborate with all the team members. The Trello boards are also equipped with “power-ups” (application integration and development capability) that allows the team to use code-repository, bug tracking, and time-tracking for Trello projects. It is available in two licensing options, a free version for individuals, and the paid subscription version for enterprises, having advanced teams functions and app integrations.

Besides the above list of tools, there are several additional tools available in the market that you can try, like Yammer (a chat-based collaboration system), Zendesk (a customer support tool), If This Then That (web-based service to create automated chains of simple conditional activities), WebEx (IM and chat service), GoToMeeting (online meetings). Each of these tools serves a specific capability and its own set of advantages and limitations. While keeping these advantages and limitations, you can try out these tools to see how they fit in within your environment. Identifying the right one, or a combination of several right ones can take the DevOps implementation in your organization to the next level.

What Is the Continuous Integration Tools Market?

CI tools automate the process of merging developer code changes into a shared repository, running build pipelines, executing test suites, and surfacing feedback quickly. The market spans on-premises servers, cloud-hosted SaaS platforms, and hybrid deployments. Vendors compete on factors including pipeline-as-code support, native cloud integrations, scalability, plugin ecosystems, and total cost of ownership.

Growth in the market is driven by several converging forces:

• Widespread adoption of microservices and containerised workloads that multiply the number of independent pipelines teams must manage.
• Regulatory and competitive pressure on industries such as finance, healthcare, and retail to deliver software faster without sacrificing quality.
• Expansion of cloud-native development, which favours SaaS CI platforms that scale on demand.
• The rise of DevSecOps, embedding security scanning directly into CI pipelines.

Key Vendors in the CI Tools Space

The competitive landscape includes large enterprise software vendors, cloud hyperscalers, and specialist DevOps companies. Notable players include:

• IBM – Offers CI/CD capabilities through its broader DevOps portfolio and cloud platform.
• Atlassian – Provides Bamboo (on-premises) and Bitbucket Pipelines (cloud), tightly integrated with Jira and the Atlassian ecosystem.
• Red Hat – Delivers OpenShift Pipelines (based on Tekton) for Kubernetes-native CI/CD workflows.
• CA Technologies (now Broadcom) – Focuses on enterprise-grade release automation and value stream management.
• Puppet – Known for configuration management but also provides pipeline and infrastructure-automation tooling relevant to CI workflows.
• CloudBees – Offers an enterprise distribution of Jenkins alongside its CloudBees CI and CD platforms, targeting regulated industries.
• AWS – AWS CodePipeline and AWS CodeBuild provide native CI/CD services tightly coupled with the AWS ecosystem.
• Microsoft – Azure DevOps (formerly VSTS) and GitHub Actions are widely adopted across enterprises and open-source projects.
• Oracle – Provides CI/CD services through Oracle Cloud Infrastructure DevOps.
• Micro Focus – Targets enterprise ALM and CI with tools such as ALM Octane.
• CircleCI – A cloud-first CI platform popular with mid-size engineering teams.
• JetBrains – TeamCity is a mature CI server with strong IDE integration.
• Electric Cloud (now CloudBees CD) – Specialises in release orchestration and pipeline analytics.
• SmartBear – Integrates CI capabilities with API testing and quality tooling.
• AppVeyor – A cloud CI service with strong Windows and .NET build support.
• Drone.io – A container-native CI platform built around a Docker-based pipeline model.
• Bitrise – Specialises in mobile CI/CD for iOS and Android applications.
• Nevercode – Another mobile-focused CI/CD service.
• AutoRABIT – Targets Salesforce DevOps, providing CI/CD for Salesforce orgs.
• Shippable (acquired by JFrog) – Pioneered YAML-based pipeline configuration; capabilities have been absorbed into JFrog Pipelines.
• Rendered Text – The company behind Semaphore CI, a fast cloud-based CI platform.
• Vsoft Technologies – A smaller player offering DevOps consulting and tooling services.

Deployment Models: On-Premises vs. Cloud

CI tools are available in two primary deployment models, each with distinct trade-offs:

On-Premises

Self-hosted CI servers such as Jenkins, TeamCity, and Bamboo run inside an organisation’s own infrastructure. This model gives teams full control over data residency, network topology, and security configurations — critical requirements in heavily regulated sectors. The trade-off is higher operational overhead: teams are responsible for provisioning, scaling, patching, and maintaining the CI infrastructure.

Cloud (SaaS)

Cloud-hosted CI services such as GitHub Actions, CircleCI, Bitrise, and AWS CodeBuild offload infrastructure management entirely. Teams pay on a consumption or seat basis, gain elastic build capacity without upfront investment, and benefit from continuous platform updates. The SaaS model is increasingly the default choice for greenfield projects and cloud-native organisations.

Industry Verticals Driving CI Adoption

CI tooling is no longer confined to software-first companies. The following verticals represent significant and growing adoption:

• Banking, Financial Services, and Insurance (BFSI) – Regulatory requirements and the pace of fintech competition push banks and insurers to automate testing and deployment while maintaining strict audit trails.
• Retail and E-commerce – High-frequency feature releases, seasonal traffic spikes, and the need for zero-downtime deployments make CI essential.
• Telecommunications – Network function virtualisation and 5G software stacks require automated build and test pipelines at scale.
• Education – EdTech platforms rely on rapid iteration to improve learning experiences and fix issues affecting students.
• Media and Entertainment – Streaming platforms and digital content delivery require continuous releases to stay competitive.
• Healthcare – Software in clinical and administrative systems demands rigorous automated testing before each release to meet compliance requirements.
• Manufacturing – Industrial IoT and embedded software teams increasingly apply CI practices to firmware and control-system development.

Key Market Dynamics

Growth Drivers

• Enterprise digital transformation initiatives accelerating investment in DevOps toolchains.
• Proliferation of containerisation (Docker, Kubernetes) increasing the need for pipeline automation.
• Shift-left testing strategies requiring CI tools with rich quality-gate integrations.
• Open-source CI ecosystems (Jenkins, Tekton, Argo Workflows) lowering entry barriers for adoption.

Challenges

• Pipeline maintenance complexity grows as organisations scale to hundreds or thousands of repositories.
• Security concerns around supply chain attacks targeting CI systems (e.g., secrets exposure, dependency tampering).
• Skills gaps in configuring and optimising CI pipelines remain a barrier for smaller teams.
• Vendor lock-in risk when pipelines are tightly coupled to a specific SaaS platform’s proprietary syntax.

Emerging Trends

• AI-assisted pipelines: Vendors are introducing ML-driven features for flaky test detection, build-time prediction, and intelligent caching.
• Unified CI/CD platforms: The boundary between CI and CD is blurring, with platforms providing end-to-end pipeline orchestration from commit to production.
• Value stream management (VSM): Organisations are instrumenting CI pipelines to measure flow metrics such as lead time and change failure rate.
• Supply chain security: SBOM generation, SLSA provenance, and signed build artefacts are becoming standard CI pipeline outputs.

Regional Landscape

CI tooling adoption varies by region, shaped by the maturity of local technology ecosystems, regulatory environments, and cloud infrastructure availability:

• North America – The most mature market, with deep enterprise adoption and a strong open-source contributor base.
• Europe – Growing adoption, with data sovereignty regulations (GDPR) influencing preference for on-premises or regional cloud deployments.
• Asia-Pacific (APAC) – Rapid growth driven by large developer populations in India and China, expanding fintech and e-commerce sectors, and cloud-first startups.
• Middle East and Africa (MEA) – Earlier-stage adoption, with government digital transformation programmes creating new demand.
• South America – Growing SaaS CI adoption among technology companies in Brazil, Colombia, and Argentina.

Evaluating CI Tools: What Teams Should Consider

When assessing CI platforms for your organisation, consider the following criteria:

1. Pipeline-as-code support: Can pipelines be version-controlled alongside application code using YAML or a DSL?
2. Integration ecosystem: Does the platform integrate natively with your source control, container registry, test frameworks, and deployment targets?
3. Scalability: Can the platform handle your build concurrency requirements without prohibitive cost?
4. Security features: How are secrets managed? Does the platform support OIDC-based authentication to cloud providers to avoid long-lived credentials?
5. Observability: Does the platform surface build analytics, failure trends, and pipeline performance metrics?
6. Compliance: Does the platform provide audit logs, role-based access control, and support for data residency requirements relevant to your industry?
7. Total cost of ownership: Account for licensing or consumption costs, infrastructure overhead (for self-hosted), and the engineering time required to maintain pipelines.

The CI tools market continues to consolidate and evolve rapidly. Understanding the vendor landscape, deployment trade-offs, and industry-specific requirements positions engineering and platform teams to make informed toolchain decisions that support long-term DevOps maturity.

What Is Application Release Orchestration?

Application Release Orchestration (ARO) software gives DevOps and release engineering teams a structured, automated way to manage the end-to-end lifecycle of software releases. Rather than relying on ad-hoc scripts or manual handoffs between development, QA, and operations, ARO platforms coordinate every step—from build promotion and environment provisioning to approval gates, deployment execution, and post-release verification.

Core capabilities typically include:

• Deployment automation — scripted, repeatable pushes to target environments with rollback support.
• Pipeline orchestration — sequencing and parallelising stages across heterogeneous toolchains.
• Release governance — audit trails, approval workflows, and policy enforcement to meet compliance requirements.
• Environment modelling — tracking which version of which component is running where across dev, staging, and production.
• Reporting and analytics — release velocity metrics, failure rates, and change-risk scoring.

Market Drivers and Restraints

The 2018 Bigmarketresearch.com report identified several forces shaping ARO adoption:

Growth Drivers

• Enterprise digital transformation — organisations across industries are increasing release frequency to stay competitive, creating demand for tooling that maintains quality at speed.
• DevOps maturity — as teams move beyond basic CI/CD pipelines, they need orchestration layers that handle complex, multi-service releases across hybrid and multi-cloud environments.
• Regulatory compliance pressure — industries such as financial services and healthcare require documented, auditable change processes that ARO platforms provide natively.
• Convergence of deployment automation and release management — vendors are consolidating previously separate tooling, reducing integration overhead for buyers.

Market Restraints

• Awareness and skills gaps — many organisations, particularly in emerging markets, lack internal expertise to evaluate, implement, and operate ARO platforms effectively.
• Licensing and implementation costs — enterprise ARO suites can carry significant licence fees and require professional services engagements, making ROI justification challenging for smaller organisations.
• Toolchain fragmentation — heterogeneous technology stacks increase integration complexity, extending time-to-value.

Deployment Models

ARO software is typically offered in two deployment models:

• On-premises — the platform runs inside the customer’s own data centre or private cloud. Preferred by organisations with strict data-residency or air-gap requirements.
• Cloud-based (SaaS) — the vendor hosts and operates the platform. Lower operational overhead and faster onboarding, but requires network connectivity to production environments and acceptance of shared-infrastructure models.

Target Segments

The market serves two primary organisational segments:

• Small and medium-sized enterprises (SMEs) — typically prioritise ease of use, quick setup, and cost-effective SaaS pricing. They often adopt open-source or freemium tiers before migrating to commercial plans.
• Large enterprises — require enterprise-grade scalability, role-based access control, audit logging, integration with ITSM platforms (ServiceNow, Jira Service Management), and support for complex multi-team governance models.

Regional Analysis

The 2018 report segmented the global market across the following regions:

North America

The United States, Canada, and Mexico. North America has historically been the largest revenue contributor, driven by early DevOps adoption, concentration of technology vendors, and mature enterprise software buying cycles.

Europe

UK, Germany, France, Spain, Italy, and the rest of Europe. Growth is supported by digital transformation initiatives and compliance-driven demand, particularly in financial services and manufacturing sectors.

Asia-Pacific

China, India, Japan, South Korea, Australia, and the rest of Asia-Pacific. The report identified this region as having the highest growth momentum, fuelled by rapid technology adoption in India and China and expanding IT services industries across the region.

LAMEA (Latin America, Middle East, and Africa)

Chile, Israel, South Africa, and the rest of LAMEA. An emerging opportunity region where ARO adoption is at an earlier stage, with growth tied to broader cloud infrastructure investment and enterprise modernisation programmes.

Key Vendors in the ARO Market

The report named the following companies as significant participants in the Application Release Orchestration software market at the time of publication:

• XebiaLabs (now Digital.ai) — known for XL Release and XL Deploy, widely used in regulated enterprises.
• Electric Cloud (later acquired by CloudBees) — offered ElectricFlow, targeting large-scale continuous delivery.
• GitLab — integrated CI/CD and release management within a single DevOps platform.
• IBM — provided UrbanCode Deploy and UrbanCode Release for enterprise release automation.
• Red Hat — Ansible Automation Platform covers deployment automation with strong infrastructure-as-code integration.
• Octopus Deploy — focused on .NET and multi-cloud deployment pipelines, with strong Windows ecosystem support.
• CA Technologies (now Broadcom) — offered CA Release Automation targeting mainframe and hybrid environments.
• Microsoft — Azure DevOps (including Azure Pipelines and Release Management) covers the full CI/CD and release orchestration workflow.
• Puppet — infrastructure automation with release pipeline capabilities through Puppet Enterprise and Relay.
• Micro Focus — offered deployment and release management capabilities targeting large enterprises with legacy estates.
• VMware — provided release automation capabilities within its application platform portfolio.
• ARCAD Software — specialised in IBM i (AS/400) and mainframe DevOps and release automation.
• Inedo — offered BuildMaster for application release management, targeting mid-market teams.
• Clarive Software — provided a unified DevOps platform with pipeline orchestration and release management features.

Note: Several of the above vendors have since been acquired, rebranded, or significantly restructured. Verify current product names and ownership before making purchasing decisions.

How to Evaluate an ARO Platform

When selecting an Application Release Orchestration tool, DevOps teams should assess the following criteria:

1. Integration breadth — Does the platform connect to your existing CI tools, artifact repositories, ITSM systems, and cloud providers without heavy custom scripting?
2. Environment modelling fidelity — Can it accurately represent your infrastructure topology across on-premises, cloud, and hybrid targets?
3. Governance and audit capabilities — Are approval workflows, change records, and deployment logs comprehensive enough for your compliance obligations?
4. Scalability — Can it handle your release volume today and over the next two to three years as teams and services grow?
5. Self-service for development teams — Does it empower developers to trigger and monitor releases without requiring platform-team intervention for every deployment?
6. Total cost of ownership — Account for licensing, infrastructure, training, and ongoing maintenance, not just the headline licence price.

Summary

Application Release Orchestration software sits at the intersection of deployment automation and release governance—bridging the gap between fast-moving development pipelines and the control requirements of production operations. As organisations mature their DevOps practices, the discipline of coordinating complex, multi-service releases across diverse environments becomes increasingly important. The vendor landscape has consolidated since 2018, but the core requirements—automation, visibility, governance, and integration—remain consistent selection criteria for engineering and platform teams evaluating these tools.

Global Continuous Delivery Market: An Overview

The Continuous Delivery (CD) market has attracted significant attention from analysts, enterprises, and software vendors as DevOps adoption accelerates globally. An industry research report published around 2019 examined the global CD market in depth, covering production metrics, growth rates, consumption trends, market share, pricing, gross margin, and revenue projections. The report drew on expert opinions and historical data to characterize market behavior and forecast near-term trajectories.

Understanding the CD market is valuable for DevOps practitioners, software architects, and business decision-makers who need to justify toolchain investments, evaluate vendor stability, or benchmark their organizations against industry trends.

What the Report Covers

The research was structured across thirteen chapters, each addressing a specific dimension of the market. Here is a summary of the key areas covered:

• Market Overview & Dynamics: Product definitions, market segmentation, regional overviews, growth drivers, limitations, opportunities, and relevant industry policies.
• Industry Chain Analysis: Upstream suppliers, major players, production processes, cost analysis, distribution channels, and downstream buyers.
• Type-Based Analysis: Value, production volume, growth rate, and pricing broken down by deployment type (on-premises vs. cloud).
• Application-Based Analysis: Downstream market characteristics, consumption patterns, and market share by industry vertical.
• Regional Production & Revenue (2014–2019): Historical data on production volume, pricing, gross margin, and revenue by region.
• Trade Flows (2014–2019): Regional production, consumption, export, and import data for the historical period.
• SWOT Analysis by Region: Strengths, weaknesses, opportunities, and threats assessed on a regional basis.
• Competitive Landscape: Company profiles, product introductions, and market distribution status for leading players.
• Market Outlook by Type & Application (2019–2024): Forward-looking analysis segmented by deployment model and vertical.
• Regional Outlook (2019–2024): Projected market evolution across key geographies.
• Investment Feasibility: Key factors, new entrant SWOT analysis, and feasibility assessment for market entry.
• Conclusion & Appendix: Summary of findings, research methodology, and data sources.

Leading Vendors in the Continuous Delivery Market

The report identified the following companies as major players in the global Continuous Delivery market at the time of publication:

• Atlassian
• IBM
• XebiaLabs
• CA Technologies (now Broadcom)
• Electric Cloud (now CloudBees)
• Puppet Enterprise
• Chef Software (now Progress Chef)
• CloudBees
• Microsoft
• Flexagon
• Micro Focus
• Clarive

Note: Several of these vendors have undergone acquisitions or rebranding since 2019. Always verify current vendor status before making procurement decisions.

Deployment Models

The research segmented the market by two primary deployment types:

• On-Premises: CD tooling hosted and managed within an organization’s own infrastructure. Preferred in regulated industries with strict data residency requirements.
• Cloud: CD platforms delivered as SaaS or hosted services. Increasingly dominant due to lower operational overhead and faster provisioning.

Industry Verticals (Application Segments)

The report broke down CD market demand by the following application sectors:

• Banking, Financial Services, and Insurance (BFSI) — High regulatory pressure drives both demand for automation and on-premises deployment preferences.
• Telecommunications — Large, complex software estates benefit significantly from continuous delivery pipelines.
• Media and Entertainment — Rapid content delivery cycles make CD a natural fit.
• Retail and eCommerce — Frequent feature releases and A/B testing make CD tooling essential.
• Healthcare — Growing software adoption in clinical and administrative systems, balanced against compliance constraints.
• Manufacturing — Industrial software and IoT integrations increasingly leverage CD practices.
• Education — EdTech platform growth is driving CD adoption in this vertical.
• Others: Government, transport and logistics, energy and utilities.

Regional Market Breakdown

The global CD market was analyzed across the following key regions:

• North America: United States, Canada
• Europe: Spain, UK, Italy, France, Germany, Rest of Europe
• Asia-Pacific: China, Australia, India, Japan, Rest of Asia-Pacific
• Middle East & Africa: GCC countries, South Africa, Rest of Middle East & Africa
• Central & South America: Brazil, Mexico, Argentina, Rest of Central & South America

North America and Europe were historically the largest markets for CD tooling, driven by early DevOps adoption among technology-forward enterprises. Asia-Pacific has been growing rapidly, with India and China showing strong demand as digital transformation initiatives accelerate.

Why Continuous Delivery Market Growth Matters to DevOps Teams

Market growth data for CD tools is more than a business metric — it signals toolchain maturity, vendor viability, and where enterprise investment is flowing. DevOps engineers and architects can use this kind of market analysis to:

• Assess whether a chosen CD vendor has the commercial traction to remain viable long-term.
• Understand which verticals are driving feature investment, which can influence product roadmaps.
• Justify budget requests for CD tooling by referencing industry-wide adoption trends.
• Benchmark their own organizations against regional and sector-specific adoption patterns.

As software delivery cycles compress and competitive pressure to ship reliably intensifies, Continuous Delivery is no longer a niche practice — it is a mainstream expectation across most software-intensive industries.

This article is based on a market research report originally published via melodyreports.com and referenced in August 2019. Specific market size figures and growth rate projections from the original report were not available in the source material and have not been reproduced here.

What Is VMware HCX?

VMware HCX is an application mobility platform designed to simplify workload migration, rebalancing, and disaster recovery across on-premises datacenters and cloud environments. It acts as a connective layer that lets enterprises move virtual machines between different infrastructure stacks — including across hypervisors and cloud providers — without redesigning networking or storage configurations from scratch.

HCX has been tightly integrated with VMware Cloud on AWS and VMware NSX since its initial release, making it a core tool for organizations pursuing hybrid or multi-cloud strategies on VMware infrastructure.

What’s New in This HCX Enterprise Release

VMware announced three significant feature additions in the August 2019 HCX Enterprise update, each targeting a specific enterprise pain point: heterogeneous platform migration, minimizing migration downtime at scale, and strengthening disaster recovery posture.

1. Non-vSphere to vSphere Migration (KVM and Hyper-V Support)

One of the most significant barriers to consolidating on VMware infrastructure has been the presence of workloads running on alternative hypervisors. With this release, VMware HCX Enterprise adds support for migrating VMs from KVM and Microsoft Hyper-V directly to vSphere — without requiring manual re-platforming steps.

This matters for organizations running mixed environments, including OpenStack-based private clouds (which typically use KVM as the underlying hypervisor) or Windows-centric infrastructure built on Hyper-V. The ability to migrate these workloads into a vSphere environment under a single orchestration tool reduces both migration complexity and project duration.

John Antonio, Chief Strategy Officer at IDX | IDX Labs, commented that KVM-to-vSphere migration is particularly valuable for telco cloud and NFV use cases, where OpenStack and VIO adoption is common and the need to connect IT, B2B, and NFV cloud environments is critical.

2. Large-Scale Bulk Migration with vMotion

This release combines VMware’s established vMotion live migration technology with the parallelism and scheduling capabilities of bulk migration. The result is the ability to migrate hundreds of live workloads simultaneously with no downtime.

The workflow works as follows:

1. VMs are replicated in bulk to the target environment while still running at the source.
2. Cutover is scheduled for a defined maintenance window or business-appropriate time.
3. At the scheduled time, live vMotion completes the migration with no service interruption.

This approach gives operations teams precise control over application cutover timing, which is critical for minimizing business risk during large-scale datacenter evacuations or cloud-first migrations.

3. Advanced Disaster Recovery with Site Recovery Manager (SRM) Readiness

VMware HCX Enterprise now integrates more deeply with VMware Site Recovery Manager (SRM), combining HCX’s hybrid interconnect capabilities with SRM’s orchestrated failover and recovery workflows.

Key benefits of the joint solution include:

• Optimized bandwidth and connectivity: The HCX hybrid interconnect handles WAN optimization and compression between sites.
• Secure VM transport: VMs in transit are encrypted through the interconnect.
• Stretched networking: Layer 2 network extension simplifies IP address management for recovered VMs, avoiding the need to re-IP workloads after failover.
• Reduced replication friction: HCX eliminates compatibility issues that often arise from mismatched network and storage configurations across sites.

CenturyLink’s vice president of product management for IT Solutions, David Shacochis, noted that HCX enables their customers to perform secure, seamless migrations of mission-critical applications with no downtime across CenturyLink’s VMware Cloud-Verified managed environment.

Why This Release Matters for Hybrid and Multi-Cloud Strategy

Enterprises adopting hybrid cloud architectures frequently run into a common problem: the cloud infrastructure is ready, but migrating existing workloads to it is slow, risky, and operationally expensive. HCX is VMware’s answer to that last-mile problem.

According to 451 Research’s Voice of the Enterprise: Cloud, Hosting & Managed Services — Workloads & Key Projects 2019 report (cited in VMware’s announcement), the proportion of workloads executing primarily in public cloud environments was expected to double over the following two years. That projection created strong urgency for tools that could accelerate workload migration at enterprise scale.

Allwyn Sequeira, SVP & GM of VMware’s Hybrid Cloud Services BU, described the strategic intent clearly: extending HCX beyond VMware-to-VMware migrations to cover non-VMware source environments, while also hardening disaster recovery capabilities, broadens the platform’s addressable use cases significantly.

HCX in the Broader VMware Ecosystem

HCX is positioned as a platform capability across several VMware product lines:

• VMware Cloud on AWS: HCX has been bundled and deeply integrated since early in that offering’s availability.
• VMware NSX: HCX leverages NSX for network extension and security policy enforcement during migrations.
• VMware Cloud Foundation (VCF): HCX fits into VCF-based deployments for datacenter consolidation and cloud expansion.
• VMware Cloud Provider Partners: HCX is available through VMware’s partner ecosystem for managed private and hybrid cloud services.

VMware refers to the end goal as a “borderless Software-Defined Data Center (SDDC)” — an architecture where workload placement is determined by policy and business need rather than physical location constraints.

Summary

For teams evaluating VMware HCX, the key questions to answer are: how heterogeneous is your source environment, how many VMs need to move, and what are your RTO/RPO requirements for disaster recovery? The August 2019 release meaningfully expands HCX’s answers to all three.

Introduction

Since its release in 2014, Kubernetes has seen remarkable adoption across data centers and cloud environments. As a container orchestration platform, it has proven capable of handling diverse IT workloads — from virtualized network functions to AI/ML pipelines and GPU-accelerated compute. Kubernetes has effectively become the de facto standard for enterprises scaling toward cloud-native architectures.

The next frontier for Kubernetes adoption is edge infrastructure: distributed environments with constrained hardware resources, intermittent connectivity to a central cloud, and thousands of nodes to manage simultaneously. Edge deployments serve as the processing layer closest to IoT sensors and end devices, making low latency, resilience, and centralized policy enforcement critical requirements.

This article explains why Kubernetes is well-suited to edge environments and walks through three architectural patterns the Kubernetes IoT Edge Working Group has proposed for deploying Kubernetes at the edge.

Why Kubernetes for Edge?

Edge nodes introduce a new infrastructure tier between IoT devices and the central cloud or on-premises data center. Operators need to manage workloads at the edge with the same level of automation and dynamism they apply to their cloud environments. Manually managing thousands of geographically distributed edge nodes is not operationally feasible at scale.

Kubernetes is a strong candidate for edge orchestration for several reasons:

• Infrastructure agnosticism: Kubernetes can schedule workloads across heterogeneous hardware — x86 servers, ARM devices, GPUs, and FPGAs — without requiring changes to the application layer.
• Unified operational model: A single control plane and API surface means the same policy definitions, RBAC rules, and deployment manifests can govern workloads across cloud, on-premises, and edge environments.
• Horizontal scalability: Kubernetes is designed to scale out, making it practical to manage a large fleet of edge nodes from a centralized control plane.
• High availability and self-healing: Kubernetes continuously monitors node and pod health, automatically rescheduling failed workloads. This is particularly important at the edge where physical access to nodes for manual intervention is difficult.
• Rapid application delivery: Container images can be pushed to edge nodes with the same CI/CD pipelines used for cloud services, enabling consistent and fast software updates across the fleet.

In a typical edge and IoT architecture, analytics and control plane services reside in the cloud. Data and instructions flow bidirectionally between cloud and edge. Kubernetes provides a common operational paradigm so that policies and rulesets can be applied uniformly across the entire infrastructure, or scoped narrowly to specific edge sites and nodes when needed.

How Can Kubernetes Be Used in Edge Architecture?

In March 2019, a Kubernetes IoT Edge Working Group was formed, comprising engineers from Red Hat, VMware, Futurewei, Google, Edgeworx, and other organizations. The group was established to discuss, design, and document approaches for running Kubernetes in edge and IoT use cases.

At their presentation during KubeCon Europe 2019, the working group outlined three primary architectural approaches for deploying Kubernetes at the edge. Each trade-off differs in where the control plane lives and how much resource overhead is imposed on the edge node itself.

A standard Kubernetes cluster consists of:

• Master (control plane): Exposes the API server, schedules workloads, and manages cluster state via etcd.
• Worker nodes: Run the container runtime (e.g., containerd or Docker), the kubelet agent that communicates with the master, and one or more pods — groups of tightly coupled containers.

The three approaches for edge scenarios build on this foundation in different ways.

Approach 1: Whole Cluster at the Edge

In this model, a complete, self-contained Kubernetes cluster runs directly on the edge node or a small cluster of edge nodes. Both the control plane and workloads are co-located at the edge site, reducing dependency on a persistent cloud connection.

The main challenge with this approach is resource overhead. Standard Kubernetes control plane components (API server, controller manager, scheduler, etcd) consume significant memory and CPU, which is scarce on edge hardware.

K3s (by Rancher) is the reference implementation for this approach. K3s packages Kubernetes into a single binary under 100 MB, removes legacy and non-essential components, replaces etcd with SQLite by default, and reduces minimum memory requirements substantially. This makes it viable to run a production-grade Kubernetes cluster on resource-constrained edge nodes such as ARM-based single-board computers or small industrial servers.

Approach 2: Cloud Control Plane with Edge Nodes (KubeEdge)

In this architecture, the Kubernetes control plane remains in the cloud (public or private), while lightweight edge agents manage containers and local resources on edge nodes. The edge nodes do not run a full control plane; instead, they run a thin agent that communicates with the cloud control plane and can operate autonomously during periods of network disconnection.

KubeEdge is the reference implementation for this model. Originally based on Huawei’s Intelligent Edge Fabric (IEF) IoT platform, KubeEdge extends Kubernetes to the edge by adding:

• An EdgeCore agent running on edge nodes that manages local pods and device communication.
• A CloudCore component running in the cloud that bridges the standard Kubernetes API with EdgeCore agents.
• Offline autonomy — edge nodes can continue running workloads even when the cloud connection is interrupted.

This approach reduces the resource footprint on edge nodes significantly while enabling centralized visibility and policy management. It is well-suited for large-scale deployments with many diverse edge sites.

Approach 3: Hierarchical Cloud Plus Edge Using Virtual Kubelet

In this model, a Virtual Kubelet running in the cloud presents edge nodes and their pods as an abstracted Kubernetes node to the control plane. The Virtual Kubelet intercepts scheduling decisions and delegates actual workload execution to edge infrastructure, without the edge nodes themselves being directly registered as standard Kubernetes nodes.

This approach offers the greatest flexibility in how edge resources are represented and managed. It allows edge infrastructure from different vendors or using different runtimes to be plugged into a standard Kubernetes control plane through a common adapter interface. Virtual Kubelet was originally designed to connect Kubernetes to serverless container platforms (such as Azure Container Instances), but the same abstraction layer is applicable to edge scenarios.

The trade-off is increased architectural complexity and a harder debugging experience when issues span the cloud-to-edge boundary.

Key Challenges Remaining

Despite its strengths, using Kubernetes for edge and IoT environments introduces real challenges that the community is actively working to address:

• Intermittent connectivity: Edge nodes may lose contact with the cloud control plane. Workloads must continue running and state must reconcile cleanly when connectivity is restored.
• Fleet management at scale: Managing thousands of edge nodes — each potentially running different hardware configurations — requires sophisticated tooling for configuration drift detection, automated updates, and rollback.
• Security at the edge: Edge nodes are physically accessible in ways that cloud servers are not, increasing the attack surface. mTLS between components, node attestation, and secrets management at the edge require careful design.
• Observability: Aggregating metrics, logs, and traces from thousands of distributed edge nodes into a coherent monitoring system adds significant data pipeline complexity.
• Resource constraints: Standard Kubernetes tooling and add-ons (Prometheus, Istio, etc.) may be too resource-heavy for constrained edge hardware, requiring lighter-weight alternatives.

Summary

Kubernetes brings a proven, infrastructure-agnostic orchestration model to edge environments, enabling teams to manage distributed edge workloads with the same tools and practices used in the cloud. Three primary architectural approaches exist for deploying Kubernetes at the edge:

1. Whole cluster at the edge — full Kubernetes on lightweight distributions like K3s, suitable for semi-autonomous sites.
2. Cloud control plane with edge agents — projects like KubeEdge keep the control plane centralized while running thin agents on edge nodes with offline autonomy.
3. Virtual Kubelet abstraction — edge resources are presented to a cloud control plane through a virtual node interface, maximizing flexibility.

The right approach depends on the available hardware resources at the edge, acceptable latency for control-plane communication, offline operation requirements, and the scale of the deployment. As the Kubernetes ecosystem continues to mature its edge capabilities — through projects like KubeEdge, K3s, and working groups within the CNCF — the operational model for managing edge infrastructure is converging toward the same Kubernetes-native patterns already established in the cloud.