Cloud & Devops

Cloud & Devops

DevOps is an increasingly common approach to software delivery where development and operations teams collaborate to build, test, deploy and monitor applications with speed, quality and control.

DevOps is relevant to any kind of software project regardless of architecture, platform or purpose. Common use cases include: cloud-native and mobile applications, application integration, and modernization and multicloud management.

Successful DevOps implementations generally rely on an integrated set of solutions or a “toolchain” to remove manual steps, reduce errors and scale beyond small, isolated teams.

Continuous integration (CI) and continuous delivery (CD) embody a culture, set of operating principles, and collection of practices that enable application development teams to deliver code changes more frequently and reliably. The implementation is also known as the CI/CD pipeline and is one of the best practices for Devops teams to implement.

CI/CD defined

Continuous integration is a coding philosophy and set of practices that drive development teams to implement small changes and check in code to version control repositories frequently. Because most modern applications require developing code in different platforms and tools, the team needs a mechanism to integrate and validate its changes.

The technical goal of CI is to establish a consistent and automated way to build, package, and test applications. With consistency in the integration process in place, teams are more likely to commit code changes more frequently, which leads to better collaboration and software quality.

Continuous delivery picks up where continuous integration ends. CD automates the delivery of applications to selected infrastructure environments. Most teams work with multiple environments other than the production, such as development and testing environments, and CD ensures there is an automated way to push code changes to them.  CD automation then performs any necessary service calls to web servers, databases, and other services that may need to be restarted or follow other procedures when applications are deployed.

Continuous integration and delivery require continuous testing because the objective is to deliver quality applications and code to users. Continuous testing is often implemented as a set of automated regression, performance, and other tests that are executed in the CI/CD pipeline.

A mature CI/CD practice has the option of implementing continuous deployment where application changes run through the CI/CD pipeline and passing builds are deployed directly to production environments. Teams practicing continuous delivery elect to deploy to production on daily or even hourly schedule, though continuous delivery isn’t always the optimal for every business application.

How continuous integration improves collaboration and quality

Continuous integration is a development philosophy backed by process mechanics and some automation. When practicing CI, developers commit their code into the version control repository frequently and most teams have a minimal standard of committing code at least daily. The rationale behind this is that it’s easier to identify defects and other software quality issues on smaller code differentials rather than larger ones developed over extensive period of times. In addition, when developers work on shorter commit cycles, it is less likely for multiple developers to be editing the same code and requiring a merge when committing.

Teams implementing continuous integration often start with version control configuration and practice definitions. Even though checking in code is done frequently, features and fixes are implemented on both short and longer time frames. Development teams practicing continuous integration use different techniques to control what features and code is ready for production.

One technique is to use version-control branching. A branching strategy such as Gitflow is selected to define protocols over how new code is merged into standard branches for development, testing and production. Additional feature branches are created for ones that will take longer development cycles. When the feature is complete, the developers can then merge the changes from feature branches into the primary development branch. This approach works well, but it can become difficult to manage if there are many features being developed concurrently.

There are other techniques for managing features. Some teams also use feature flags, a configuration mechanism to turn on or off features and code at run time. Features that are still under development are wrapped with feature flags in the code, deployed with the master branch to production, and turned off until they are ready to be used.

The build process itself is then automated by packaging all the software, database, and other components. For example, if you were developing a Java application, CI would package all the static web server files such as HTML, CSS, and JavaScript along with the Java application and any database scripts. CI not only packages all the software and database components, but the automation will also execute unit tests and other testing. This testing provides feedback to developers that their code changes didn’t break any existing unit tests.

Most CI/CD tools let developers kick off builds on demand, triggered by code commits in the version control repository, or on a defined schedule. Teams need to discuss the build schedule that works best for the size of the team, the number of daily commits expected, and other application considerations. A best practice to ensure that commits and builds are fast, otherwise, it may impede the progress of teams trying to code fast and commit frequently.

Continuous testing goes beyond test automation

Automated testing frameworks help quality assurance engineers define, execute, and automate various types of tests that can help development teams know whether a software build passes or fails. They include functionality tests that are developed at the end of every sprint and aggregated into a regression test for the entire application. These regression tests then inform the team whether a code change failed one or more of the tests developed across all functional areas of the application where there is test coverage.

A best practice is to enable and require developers to run all or a subset of regressions tests in their local environments. This step ensures that developers only commit code to version control after regression tests pass on the code changes. Regression tests are just the start. Performance testing, API testing, static code analysis, security testing, and other testing forms can also be automated. The key is to be able to trigger these tests either through command line, webhook, or web service and that they respond with success or fail status codes.

Once testing is automated, continuous testing implies that the automation is integrated into the CI/CD pipeline. Some unit and functionality tests can be integrated into CI that flags issues before or during the integration process. Test that require a full delivery environment such as performance and security testing are often integrated into CD and performed after builds are delivered to target environments.

The Continuous Delivery pipeline automates changes to multiple environments

Continuous delivery is the automation that pushes applications to delivery environments. Most development teams typically have one or more development and testing environments where application changes are staged for testing and review. A CI/CD tool such as Jenkins or Travis CI is used to automate the steps and provide reporting.

A typical CD pipeline includes many of these steps:

  • Pulling code from version control and executing a build.
  • Executing any required infrastructure steps that are automated as code to stand up or tear down cloud infrastructure.
  • Moving code to the target compute environment.
  • Managing the environment variables and configuring them for the target environment.
  • Pushing application components to their appropriate services, such as web servers, API services, and database services.
  • Executing any steps required to restarts services or call service endpoints that are needed for new code pushes.
  • Executing continuous tests and rollback environments if tests fail.
  • Providing log data and alerts on the state of the delivery.

More sophisticated CD may have other steps such as performing data synchronizations, archiving information resources, or performing some application and library patching. Once a CI/CD tool is selected, development teams must make sure that all environment variables are configured outside the application. CI/CD tools allow setting these variables, masking variables such as passwords and account keys, and configuring them at time of deployment for the target environment.

Many teams implementing CI/CD pipelines on cloud environments also use containers such as Docker and Kubernetes. Containers allow packaging and shipping applications in standard, portable ways. The containers can then be used to scale up or tear down environments that have variable workloads. CD tools also provide dashboard and reporting functions. If builds or deliveries fail, they alert developers with information on the failed builds. They integrate with version control and agile tools, so they can be used to look up what code changes and user stories made up a build.  

  • Optimize your technical environment for agility, efficiency & performance, reducing friction and costs.
  • Create a space to store huge volumes of data.
  • Increase mobility and wireless operations for users round the globe.
  • Increase efficiency with backend systems that can handle a Huge volume of traffic.
  • Save time and money by allowing automation operations in the cloud.

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