Canary release vs rolling deployment: Choosing a deployment strategy
Canary release
A canary release is a deployment strategy that gradually introduces a new version of an application to a small subset of users before rolling it out to the entire user base. This approach gets its name from the historical practice of using canary birds in coal mines to detect dangerous gases. In software deployment, the “canary” serves as an early warning system for potential issues with the new release.
The canary release strategy typically involves routing a small percentage of traffic (usually 5-10%) to the new version while the majority of users continue using the stable version. This allows teams to monitor key metrics, gather user feedback, and identify any performance issues or bugs before committing to a full deployment. If problems are detected, the canary can be quickly rolled back with minimal impact to users.
Rolling deployment
Rolling deployment is a strategy where the new version of an application is gradually deployed across multiple instances or servers, replacing the old version incrementally. This approach ensures zero-downtime deployment by maintaining service availability throughout the update process. Instead of updating all instances simultaneously, the deployment occurs in phases, with each phase updating a portion of the infrastructure.
During a rolling deployment, the load balancer or orchestration system systematically takes instances offline, updates them to the new version, and brings them back online before proceeding to the next batch. This method provides a safety net as the deployment can be paused or rolled back if issues arise during any phase. The strategy is particularly effective in containerized environments and microservices architectures where multiple instances of the same service run simultaneously.
Comparison
Traffic distribution
- Canary: Routes small percentage of traffic to new version while majority stays on old version
- Rolling: Gradually shifts all traffic as instances are updated one by one
Risk level
- Canary: Lower risk due to limited user exposure during testing phase
- Rolling: Moderate risk as all users eventually receive the update during deployment process
Rollback speed
- Canary: Immediate rollback by redirecting traffic away from canary instances
- Rolling: Slower rollback requiring reverse deployment process across all updated instances
Resource requirements
- Canary: Requires additional infrastructure to run both versions simultaneously
- Rolling: Uses existing infrastructure more efficiently by updating in place
Monitoring complexity
- Canary: Requires sophisticated monitoring to compare metrics between versions
- Rolling: Simpler monitoring focused on deployment progress and system health
User experience
- Canary: Inconsistent experience as different users see different versions
- Rolling: Consistent experience once deployment completes for each instance
Feature flags with canary releases
Feature flags work exceptionally well with canary releases by providing fine-grained control over which users experience new functionality. Instead of relying solely on traffic routing, teams can use feature flags to enable new features for specific user segments within the canary group, allowing for even more targeted testing and gradual rollouts. This combination enables A/B testing scenarios where different variations of features can be tested simultaneously within the canary population.
The integration of feature flags with canary releases also provides an additional safety mechanism for rollbacks. If issues are detected, teams can instantly disable problematic features through feature flags without needing to redeploy or redirect traffic, providing faster incident response times and more granular control over the user experience during the testing phase.
Feature flags with rolling deployments
Feature flags complement rolling deployments by decoupling feature releases from code deployments, allowing new code to be deployed safely with features initially disabled. As the rolling deployment progresses across instances, feature flags ensure that new functionality remains hidden until the deployment is complete and the team is ready to activate features. This approach prevents partial feature exposure that could occur if some instances have the new code while others are still being updated.
Using feature flags with rolling deployments also enables teams to perform staged feature activations after the deployment is complete. Rather than enabling all new features immediately once the rolling deployment finishes, teams can gradually activate features using the same progressive approach, effectively creating a two-phase rollout strategy that further reduces risk and allows for careful monitoring of each feature’s impact on system performance and user behavior.
Canary releases offer excellent risk mitigation by exposing new versions to only a small subset of users initially, allowing teams to detect issues early with minimal impact. This approach provides granular control over rollout speed and enables detailed monitoring of key metrics before full deployment. The ability to quickly rollback affects only the small canary group, making it ideal for critical applications where stability is paramount. However, canary releases require sophisticated traffic routing infrastructure, more complex monitoring systems, and longer deployment cycles. The infrastructure overhead includes maintaining multiple environments simultaneously and implementing feature flags or load balancer rules to manage traffic distribution.
Rolling deployments excel in simplicity and resource efficiency, gradually replacing instances without requiring additional infrastructure or complex traffic management. This approach maintains consistent capacity throughout the deployment process and works well with standard orchestration tools like Kubernetes. Rolling deployments are faster to implement and require less operational overhead, making them suitable for applications with predictable behavior and lower risk tolerance requirements. The main drawbacks include the potential for wider blast radius if issues occur, as problems may affect more users before detection. Additionally, rolling deployments offer less granular control over the rollout process and may struggle with database schema changes or stateful applications. Choose canary releases for critical user-facing applications, new feature launches, or when you need precise control over risk exposure. Opt for rolling deployments when you need simple, fast deployments for stable applications with well-tested changes, or when infrastructure complexity must be minimized.
Frequently asked questions
What are the different types of deployment strategy?
There are several deployment strategies used in software development, with two main approaches being canary releases and rolling deployments. Canary releases gradually introduce a new version to a small subset of users (typically 5-10% of traffic) before rolling out to the entire user base, serving as an early warning system for potential issues. Rolling deployments gradually deploy the new version across multiple instances or servers, replacing the old version incrementally while maintaining zero-downtime. Both strategies can be enhanced with feature flags, which provide fine-grained control over feature activation and allow teams to decouple feature releases from code deployments.
What are the pros and cons of rolling deployment?
Rolling deployments offer several advantages including simplicity and resource efficiency, as they gradually replace instances without requiring additional infrastructure or complex traffic management. They maintain consistent capacity throughout the deployment process, work well with standard orchestration tools like Kubernetes, and are faster to implement with less operational overhead. However, rolling deployments have some drawbacks including a potentially wider blast radius if issues occur, as problems may affect more users before detection. They also offer less granular control over the rollout process and may struggle with database schema changes or stateful applications. The rollback process is slower since it requires reverse deployment across all updated instances, compared to the immediate rollback capabilities of canary releases.
