Kubernetes is a popular container orchestration platform that provides developers with a powerful toolset to manage containerized applications at scale. One of the key features of Kubernetes is its ability to perform automated deployment rollouts and rollbacks.

In this blog post, we will explore how Kubernetes performs these operations and how they can be used to improve the reliability and availability of your applications.

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Rollouts and Rollbacks

Before we dive into how Kubernetes performs a rollout and rollback, let's first define what they are.

In the context of Kubernetes, a rollout is the process of updating a running application by deploying a new version of the application. The new version is typically deployed in a phased manner, so that if any issues are discovered, they can be addressed before the entire application is updated.

A rollback, on the other hand, is the process of undoing a rollout and reverting back to a previous version of the application. Rollbacks are important because they allow developers to quickly and easily undo changes that have caused issues in production.

Performing a Deployment Rollout

Kubernetes performs deployment rollouts using a feature called Deployments. Deployments are a higher-level construct that provide a declarative way to manage a set of ReplicaSets. A ReplicaSet is a Kubernetes object that ensures that a specified number of replicas of a Pod are running at any given time. Deployments provide a way to define a desired state for an application and manage the rollout process.

To perform a deployment rollout, a developer first creates a new version of the application and packages it into a container image. They then update the Deployment object to point to the new container image. When the updated Deployment is applied to the Kubernetes cluster, Kubernetes performs the following steps:

  1. Kubernetes creates a new ReplicaSet for the updated version of the application. This ReplicaSet specifies the number of replicas that should be running and the container image that should be used.
  2. Kubernetes gradually scales up the new ReplicaSet and scales down the old ReplicaSet. This is done to ensure that there is no downtime during the rollout process.
  3. Kubernetes monitors the health of the new ReplicaSet by checking the status of the Pods that it manages. If any Pods fail, Kubernetes will automatically restart them.
  4. Once the new ReplicaSet is fully scaled up, Kubernetes will scale down and eventually delete the old ReplicaSet.

This process ensures that the new version of the application is gradually rolled out to the Kubernetes cluster, without causing any downtime or disruption to users. If any issues are discovered during the rollout process, the developer can quickly roll back to the previous version of the application.

Performing a Deployment Rollback

Kubernetes also provides a way to perform automated deployment rollbacks. If an issue is discovered during a deployment rollout, a developer can use the kubectl command-line tool to perform a rollback to the previous version of the application. When a rollback is initiated, Kubernetes performs the following steps:

  1. Kubernetes creates a new ReplicaSet for the previous version of the application.
  2. Kubernetes scales up the new ReplicaSet and scales down the current ReplicaSet.
  3. Kubernetes monitors the health of the new ReplicaSet by checking the status of the Pods that it manages. If any Pods fail, Kubernetes will automatically restart them.
  4. Once the new ReplicaSet is fully scaled up, Kubernetes will scale down and eventually delete the current ReplicaSet.

This process ensures that the previous version of the application is rolled back to the Kubernetes cluster, without causing any downtime or disruption to users. If any issues are discovered with the previous version of the application, the developer can quickly roll forward to the new version.

Managing Rollouts and Rollbacks

Kubernetes provides several features that can be used to manage rollouts and rollbacks. One of the most important features is the ability to define rollout strategies. Rollout strategies allow developers to define how Kubernetes should perform a deployment rollout. There are several rollout strategies available, including:

  • RollingUpdate: This is the default rollout strategy in Kubernetes. With this strategy, Kubernetes gradually replaces the old ReplicaSet with the new ReplicaSet, as described above.
  • Recreate: With this strategy, Kubernetes first scales down the old ReplicaSet to zero replicas, and then scales up the new ReplicaSet to the desired number of replicas. This strategy is less common than RollingUpdate, as it can cause downtime during the rollout process.
  • Blue/Green: With this strategy, a new version of the application is deployed to a separate set of servers, known as the "blue" environment. Once the new version has been fully tested, traffic is routed to the new environment, and the old environment is taken down. This strategy can be useful for applications that require zero downtime during deployment.

Kubernetes also provides several tools that can be used to monitor and manage rollouts and rollbacks.

One of the most useful tools is kubectl, the command-line interface for Kubernetes. With kubectl, developers can view the status of Deployments, view logs for individual Pods, and initiate rollbacks. Kubernetes also provides a Dashboard web interface that can be used to monitor the health of the Kubernetes cluster and manage deployments.

Conclusion

In this blog post, we have explored how Kubernetes performs deployment rollouts and rollbacks. Deployments are a powerful tool for managing the rollout of containerized applications in a Kubernetes cluster. By using a phased rollout process, Kubernetes ensures that the new version of the application is deployed without causing any downtime or disruption to users.

If any issues are discovered during the rollout process, Kubernetes provides a simple way to perform a rollback to the previous version of the application. By using these features, developers can ensure the reliability and availability of their applications in production.