Blue-green deployment vs rolling deployment: Choosing a deployment strategy

Blue-green deployment

Blue-green deployment is a strategy that involves maintaining two identical production environments, referred to as “blue” and “green”. At any given time, only one of these environments is live, serving all production traffic. When deploying a new version of an application, the update is installed on the non-live environment. After thorough testing, traffic is switched from the currently live environment to the updated one, typically by changing the routing configuration.

This approach offers minimal downtime and a quick rollback capability if issues are discovered after deployment. Since the transition between environments is instantaneous, users experience no disruption in service. Additionally, the idle environment can serve as a staging area for the next release, allowing comprehensive testing in an environment identical to production before going live.

Rolling deployment

Rolling deployment is a strategy where a new version of an application gradually replaces the old version. This is typically achieved by incrementally updating instances of the application within the same environment. For example, in a environment with multiple servers, a subset of servers is taken offline, updated, and brought back into service before moving on to the next subset.

This approach reduces risk by allowing observation of how the new version performs with a portion of production traffic before committing to a full deployment. If issues are detected, the deployment can be halted, limiting the impact. While rolling deployments may take longer to complete than other strategies, they often require less infrastructure overhead since separate environments are not needed.

Comparison: Blue-green vs. Rolling deployment

Downtime

• Blue-Green: Virtually zero downtime as traffic is instantly redirected to the new environment.

• Rolling: Minimal downtime, but individual instances experience downtime as they’re updated.

Resource requirements

• Blue-Green: Higher resource requirements as two complete environments must be maintained simultaneously.

• Rolling: Lower resource overhead as only the existing production environment is needed.

Rollback capability

• Blue-Green: Immediate rollback by redirecting traffic back to the original environment.

• Rolling: Rollback is more complex, requiring reverse deployment of the previous version.

Testing

• Blue-Green: Complete testing possible in the new environment before traffic redirection.

• Rolling: Limited ability to test in production before full deployment, as changes are incremental.

Complexity

• Blue-Green: Conceptually simple but requires robust traffic routing mechanisms.

• Rolling: More complex orchestration needed to manage the gradual replacement of instances.

Database compatibility

• Blue-Green: Requires careful handling of database schema changes and backward compatibility.

• Rolling: Better suited for applications where database changes can be made incrementally.

Feature flags with blue-green deployment

Feature flags pair exceptionally well with blue-green deployments to create advanced, risk-mitigated deployment strategies. With blue-green deployment, all code is deployed to the green environment but can remain dormant behind feature flags. Once traffic is routed to the green environment, features can be selectively enabled for specific user segments or gradually rolled out to the entire user base. This creates a separation between deployment and release, allowing teams to deploy code without immediately exposing functionality.

If issues arise after enabling a feature flag in the green environment, teams can quickly disable the problematic feature without needing to roll back the entire deployment. This approach provides fine-grained control over what functionality is exposed to users, while still maintaining the primary benefit of blue-green deployment: the ability to quickly revert to the blue environment if catastrophic issues arise that cannot be mitigated through feature flags alone.

Feature flags with rolling deployment

Feature flags complement rolling deployments by adding an additional layer of risk management to the gradual release process. With rolling deployments, new code is incrementally deployed to production servers, and feature flags allow teams to deploy code in a dormant state across the entire fleet before enabling functionality. This means that even as servers are being updated in waves, the application behavior remains consistent because new features are kept behind flags.

Once the rolling deployment is complete and all servers are running the new code version, teams can begin enabling features gradually using the feature flag system. This creates a two-phase deployment approach: first rolling out code changes safely, then independently controlling feature exposure. If issues are detected after enabling a feature, teams can instantly disable it without needing to perform another rolling deployment, significantly reducing the time to mitigate problems and minimizing user impact.

Blue-green deployment and rolling deployment are two popular strategies for deploying software updates with minimal downtime. Blue-green deployment involves maintaining two identical production environments (blue and green), with only one active at a time. When deploying, the new version is installed on the inactive environment, tested, and then traffic is switched over all at once. This approach offers several advantages: it enables instant rollback by simply reverting traffic to the previous environment, provides a clean separation between versions, and allows thorough testing in a production-identical environment before going live. However, blue-green deployment requires double the infrastructure resources, which increases costs. It also requires a sophisticated load balancing mechanism to handle the traffic switch and may create complications with database migrations or stateful applications.

Rolling deployment, on the other hand, gradually replaces instances of the old version with the new version, typically one server or subset of servers at a time. This approach requires less infrastructure since you don’t need to maintain two complete environments. It also distributes the deployment risk over time, allowing issues to be caught before the entire system is updated. Rolling deployments are generally easier to implement with most orchestration platforms like Kubernetes. However, during the deployment window, two versions of the application run simultaneously, which can create compatibility issues, especially with APIs or database schemas. Choose blue-green deployment when you need the safety of immediate rollbacks, when your application can handle the complete environment switch, and when you can afford the additional infrastructure costs. Opt for rolling deployments when resources are constrained, when you need to gradually introduce changes to monitor performance impacts, or when your application has been designed to handle multiple versions running concurrently.

Frequently asked questions

What is the difference between blue-green deployment and canary deployment?

Blue-green deployment maintains two identical production environments (blue and green), with only one serving traffic at a time. When deploying a new version, you install it on the inactive environment, test it thoroughly, and then switch all traffic from the active to the updated environment instantly. Canary deployment (though not explicitly covered in the article) is a different approach where you gradually roll out a new version to a small subset of users before deploying to the entire user base, allowing you to test with real user traffic while limiting risk.

Can you provide an example of a blue-green deployment?

In a blue-green deployment, you would have two identical production environments. If the “blue” environment is currently serving all user traffic, you would deploy your new application version to the “green” environment. After testing the new version thoroughly in the green environment, you would switch all traffic from blue to green by changing the routing configuration (typically through a load balancer or DNS change). The switch is instantaneous, resulting in no downtime for users. If any issues are discovered after deployment, you can immediately roll back by redirecting traffic back to the blue environment.

How does blue-green deployment work in AWS?

While not specifically addressed in the article, blue-green deployment in AWS typically leverages services like Elastic Load Balancing (ELB) to redirect traffic between environments. You can create two separate environments using services like EC2, ECS, or EKS, deploy your new version to the inactive environment, and then update the load balancer routing rules to direct traffic to the new environment. AWS CodeDeploy also offers built-in support for blue-green deployments, automating much of this process for you.

What are the best strategies for implementing blue-green deployment?

The best strategies for implementing blue-green deployment include:

• Maintaining truly identical blue and green environments to ensure consistent behavior

• Implementing robust testing in the new environment before switching traffic

• Using feature flags in conjunction with blue-green deployment to create an additional safety layer (allowing you to deploy code but keep new features disabled until ready)

• Ensuring you have sophisticated traffic routing mechanisms to handle the instantaneous switch

• Planning for database compatibility and schema changes, which can be challenging in blue-green scenarios

• Being prepared for quick rollbacks by keeping the previous environment ready to receive traffic again

How is blue-green deployment applied to databases?

Blue-green deployment with databases requires careful handling of schema changes and backward compatibility. Since you can’t simply switch between two database instances as easily as application servers, you need strategies to ensure data consistency. This often involves designing database changes to be backward compatible, using strategies like expand/contract patterns (adding new fields/tables before removing old ones), and ensuring both application versions can work with the database schema. In some cases, you might need to synchronize data between environments or maintain separate database versions with data replication, though this adds complexity to the deployment process.