Continuous deployment (CD) is a software release method that automates the entire process from code commit through to testing and deployment. Once a commit passes all tests, it is automatically released into production, and updates become visible to software users. This is considered an evolution of Continuous Integration / Continuous Delivery (CI/CD).
Continuous deployment replaces the manual safeguards that traditionally prevented unproven code from reaching the live production environment. When implementing this approach, it is essential to ensure that all IT and development teams adhere to rigorous testing requirements and development practices for production-ready code. It also requires monitoring production in real time to quickly identify and resolve problems with each new release.
In the past, continuous deployment was considered a hard-core practice that could only be implemented by “unicorns” or technology giants like Amazon and Facebook. Today, new development practices like GitOps and improved infrastructure, powered by Kubernetes, is making continuous deployment accessible to everyone
Continuous Delivery vs. Continuous Deployment
Continuous delivery builds on continuous integration (CI), extending automation beyond the build stage to deploy all code changes to the testing and production environments. In addition to automated tests, the release process is also automated, making it easy to deploy applications with the click of a button.
Continuous delivery enables scheduled releases daily, weekly, or however often the business demands. However, the benefits of continuous delivery are greater when releases occur in small batches as soon as possible. This approach enables early troubleshooting to identify issues before they become costly to repair.
Continuous deployment extends the CI/CD approach even further than continuous delivery. It automates the release of each change that has passed the other stages of the production pipeline. Continuous deployment eliminates human intervention in the deployment process, with all changes deployed to production unless they fail a test.
Continuous deployment helps speed up the customer feedback loop with shorter development cycles and no stressful deadline (i.e., release day). It lets developers focus on creating software, enabling code changes to go live within minutes of a build.
Advantages and Disadvantages of Continuous Deployment
Continuous deployment provides several important advantages for software developers and organizations, including:
Higher productivity—developers can spend more time on the actual build, relying on automation to handle deployment.
Adaptability—organizations can quickly respond to changing customer demands, with new features more easily tested, deployed, and validated.
Fast feedback—development teams receive frequent user feedback, responding quickly to special requests or bug reports. Customers can use the updated product immediately when developers push the code.
However, a continuous deployment pipeline can also present some challenges:
Initial cost—despite the high return on investment, the initial engineering costs of setting up a continuous deployment pipeline may be high.
Maintenance—ongoing maintenance efforts are necessary to ensure a smooth, fast pipeline.
What Tools are Necessary to Practice Continuous Deployment?
Continuous deployment demands a significant upfront engineering investment. Some of the tools required to establish a CD pipeline include:
Automated tests—test automation is the main capability required for continuous deployment. The whole CI/CD chain depends on automation. Development teams can use automated tests to prevent regressions when introducing new code without relying on manual testers to review every code change.
Containerization—containerization allows developers to create and deploy applications faster and more securely. It is easier to deploy an application as a container, bundled with all relevant configuration files, libraries, and dependencies needed to run application code. This single software package or “container” is abstracted from the host operating system, portable, and able to run on any platform or cloud.
Deployment automation—the main difference between continuous delivery and continuous deployment is the added step of automating code deployment in a live production environment.
Progressive deployment—continuous deployment pipelines require tools to upgrade software to a new version and automatically roll back a deployment when it introduces a bug or undesirable change. An example of a progressive deployment strategy is a green/blue or canary deployment.
GitOps tools—GitOps gives developers greater control over their application deployment pipelines by unifying many important tasks such as deploying, managing, and monitoring environments. GitOps gives you full control over the deployment of both infrastructure and applications. DevOps teams create a declarative configuration saying what they need to run, and GitOps tools deploy it automatically and make sure deployments are consistent and reliable.
Monitoring and alerting tools—continuous deployment pipelines must have continuous, real-time monitoring. Teams should automatically receive alerts to significant issues. Monitoring tools offer crucial health visibility across the development system for the entire deployment lifecycle. It is also possible to configure alerts to trigger automated rollbacks of flawed deployments.
Moving from Continuous Delivery to Continuous Deployment
There are several steps that organizations can take to implement continuous deployment.
Encouraging a CI/CD Culture
Successful continuous deployment depends on teams embracing a continuous integration and delivery culture. Test quality determines the risk level of each release. Automated testing should be a priority throughout the development lifecycle, with developers taking care to implement tests for each new feature. Regressions identified after the software release may require additional tests.
Another priority should be repairing broken builds for the main development branch. Continuous deployment helps mitigate risks such as accumulated changes sitting in development, with developers unsure whether their code has passed acceptance tests. Every developer must be involved in the CI/CD process to ensure everyone stays up to date with the project’s progress.
Have an Effective Test Suite
Unit, integration, and functional tests aim to improve an organization’s confidence in new releases. Theoretically, more tests guarantee that new features are free of regressions. The CI/CD solution must fully manage and automate these tests to enable a comprehensive test suite, ensuring testing throughout the deployment lifecycle.
The platform must run the whole test suite in one step to achieve the required level of automation. Some organizations continue to build tests the old way, with engineers executing various tests manually. This approach creates bottlenecks and slows down deployment.
The CI/CD platform should handle most tests automatically – test engineers can write tests but shouldn’t waste time executing them. Testing teams can perform smoke tests manually in some cases, but this should be an exception.
Fast test execution is essential for enabling frequent releases. Developers must be confident their commits don’t have regressions and are ready for deployment. Testing time should be fast, between five and ten minutes on average, to enable developers to push features to production quickly. It is advisable to refactor or redesign larger tests that take hours to complete.
Testing typically involves several steps within the CI/CD pipeline. It is a continuous process throughout the development pipeline. It should include various types of tests, such as stress/load tests, short unit tests, complex integration tests, limited smoke tests, and user-driven UI tests.
The specific test types will depend on the project and organization. Developers should have a choice of tests to incorporate into their pipelines. A unified, standard test suite may be inefficient and encourage developers to cut corners, while multiple test suites offer greater flexibility and save time.
Using Trunk-Based Development
The best way to branch source code is a major bone of contention. Opinions differ on whether developers should use branches per release, feature, component, or team.
Organizations with regular release cycles (i.e., quarterly or monthly) often choose to have separate branches for each release. This approach allows them to create patches for their released codebase while keeping them separate from the development changes in-process.
However, release branches are unnecessary for continuous deployment because this approach breaks down deployments into smaller, more manageable sections. There are no large, monolithic deployments. With continuous deployment, organizations face a different challenge—for every current deployment that requires a patch, another deployment is already waiting in the pipeline. This makes a strong case for trunk-based development.
Another reason that many organizations opt for a branching approach is to provide separate branches for each feature. This approach may be useful for smaller features, but it can become expensive to merge the long-lived branches for larger features. Developing features in the trunk is a better option—the feature can remain disabled with a feature toggle, reserving the branches for experimental features that might be rolled back. This helps keep the trunk code base decluttered.
Feature toggles allow developers to use the configuration to turn features on and off. Feature toggling controls when and how each functionality becomes available in an application.
People generally associate feature toggling with a business-driven approach that allows business users to decide whether to deactivate or modify a feature. Toggles are a simple way to modify app functionality. However, a release-driven feature toggling approach is more significant for continuous deployment. In this context, developers hide a new feature (from all or some users) until they are ready to deploy it.
The objective here is to minimize the code branching. To this end, developers must be willing to introduce changes gradually to the code repository trunk while hiding changes before they can go live. Developers can thus fully build features and leverage business users to review them interactively in an internal system. They enable the features only when these users are satisfied with them. The rest of the codebase can go to production with other approved fixes while avoiding the anti-pattern of long-lived branches for those features.
When an organization decides to introduce a new feature, it is useful to have a library of feature toggles to help manage the gradual introduction of changes to a subset of users. This canary deployment model enables developers to test out their changes with a limited set of users before making them available to everyone else.
Keeping the features focused and small is important to achieve an effective feature toggling strategy. Suppose an organization deploys early and often with multiple in-process features switched off. In that case, the developers must constantly validate that the disabled features remain self-contained and will not impact other components. Continuous deployment offers a high level of transparency that encourages developers to keep their code clean.
Implementing Zero Downtime Deployment
Eliminating downtime is essential when deployments occur continuously throughout business hours (contrast this with the pain of infrequent deployments). Applications must handle changes without affecting user experience or interrupting traffic. Some applications or websites can afford a few minutes of downtime during off-peak hours, but many apps need to operate smoothly to maintain business continuity.
Organizations typically use multiple web servers to run their applications, sometimes in several web farms behind load balancers. When updating the system, they can pull each server or web farm offline and bring it back after the update. The same goes for application servers, although API versioning is also useful when updating these.
Background processes on an application server must share a data source (i.e., a database) and run simultaneously without conflicting with each other. Avoiding downtime when updating a database may be trickier if it serves as a single source of truth. For instance, there may be several database servers in a cluster, but with only one data instance active at any time.
Using snapshots to update a database is ineffective because the data could change by the time the update is ready. The best way to update the database while keeping the application running is to avoid breaking changes. For example, adding a new field or table is better than modifying or deleting an existing element. This approach may still require significant schema refactoring to ensure support for both old and new versions. Usually, significant changes that require downtime are rarely necessary—it might be acceptable to schedule downtime for these occasions.
How Does GitOps Help Implement Continuous Deployment?
GitOps is a declarative strategy for implementing continuous deployment for cloud native apps. It emphasizes the developer’s role while operating infrastructure, providing developer-friendly tools such as Git to handle operations. GitOps revolves around using a Git repository containing descriptions of the desired production infrastructure. It leverages automation to ensure the production environment matches the desired state described in the repository.
Developers only need to update the Git repository to update an application or deploy a new one. An automated process continues from there. This approach is similar to using cruise control to manage applications in the production environment.
The main unique advantage of GitOps is that development teams don’t have to use different tools to deploy the application. It eliminates the need for an Ops team, with the version control system used to develop the app managing everything.
Argo CD is a declarative GitOps continuous delivery tool for Kubernetes. It lets you adopt a GitOps process where application definitions, configurations, and environments are declarative and versioned.
With Argo, application deployment and lifecycle management become automated, auditable and understandable. Argo CD defines the desired application state, using a Git repository as a single source of truth.
Argo CD enables continuous deployment by automatically deploying the desired application state to a specified target environment. When deploying your application, you can use Git commits to track branch and tag updates, or pin them to a specific version of a manifest.
Argo CD is implemented as a Kubernetes controller that continuously monitors a running application and compares the current active state to the desired target state (specified in the Git repository). A deployed application whose real-time state is different from the target state is considered OutOfSync. Argo CD provides the ability to automatically synchronize the live state to the desired target state – making continuous deployment safe and easy to achieve.
Changes to the desired target state in the Git repository are automatically applied and reflected in the specified target environment, and it is always easy to roll back to a previous stable version.
Codefresh provides delivery pipelines, which greatly simplify the creation and monitoring of development workflows. These pipelines are optimized for DevOps flows such as CI/CD pipelines for checking out code, building and testing artifacts, etc.
Codefresh GitOps provides the application deployment layer. Defining an application is as simple as identifying a source repo and its target. Codefresh GitOps is built on Argo CD and Argo Rollouts to power progressive delivery.
The platform seamlessly integrates with Git, JIRA, and other systems to provide a clear dashboard of all activity in the software supply chain. Bringing all these components into a single flow makes it easy to identify the cause of breaking changes, and keep track of all your running infrastructure and applications as changes flow into them.
With easy remediation, teams have more confidence in deploying more frequently. Today, even high velocity organizations might only deploy frequently on a few applications, Codefresh enables companies to deploy frequently for every application.
This also works at scale. Filtering all changes by deployment time, committer, application, JIRA issue, or several other dimensions brings incredible traceability and clarity. The dashboard can even track all the locations a particular artifact is deployed across the entire organization.
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