Rolling deployment vs kill switches: Choosing a deployment strategy

Rolling deployment

Rolling deployment is a gradual release strategy where new application versions are deployed incrementally across servers or instances. Instead of updating all systems simultaneously, the deployment process replaces old versions with new ones in small batches, typically one server or a small group at a time. This approach ensures that some portion of the application remains available throughout the deployment process.

The rolling deployment strategy minimizes downtime and provides a safety net by maintaining operational instances during the update process. If issues arise during deployment, the process can be paused or rolled back before affecting the entire system. This method is particularly effective for applications that require high availability and cannot afford complete service interruptions.

Kill switch

A kill switch deployment strategy involves the ability to instantly disable or revert a feature or entire application deployment with a single action. This approach typically uses feature toggles, load balancer configurations, or traffic routing mechanisms to immediately redirect users away from problematic deployments. The kill switch acts as an emergency brake that can be activated when critical issues are detected in production.

Kill switch strategies are designed for rapid response to production incidents, allowing teams to quickly mitigate damage from faulty deployments. Unlike rollbacks that may take time to propagate through systems, a kill switch provides immediate relief by either disabling problematic features or routing traffic to known-good versions. This strategy is essential for maintaining system stability and user experience when deployments go wrong.

Comparison

Speed of deployment

• Rolling Deployment: Gradual deployment takes longer to complete as updates are applied incrementally

• Kill Switch: Instant activation allows immediate changes to traffic routing or feature availability

Risk management

• Rolling Deployment: Lower risk due to gradual rollout that can catch issues before full deployment

• Kill Switch: High-speed risk mitigation but doesn’t prevent initial exposure to problematic code

System availability

• Rolling Deployment: Maintains partial availability throughout the deployment process

• Kill Switch: Can provide immediate availability restoration when issues occur

Complexity

• Rolling Deployment: Requires orchestration tools and careful coordination of instance updates

• Kill Switch: Simpler implementation focused on traffic routing and feature toggling mechanisms

Recovery time

• Rolling Deployment: Slower recovery requires rolling back through the same gradual process

• Kill Switch: Immediate recovery through instant traffic redirection or feature disabling

Feature flags with rolling deployment

Feature flags complement rolling deployment by providing fine-grained control over feature visibility during the gradual rollout process. As new versions are deployed to each batch of servers, feature flags can selectively enable or disable specific functionality for different user segments or geographical regions. This dual approach allows teams to deploy code infrastructure through rolling updates while controlling feature exposure independently, creating multiple layers of risk mitigation.

The combination enables sophisticated deployment patterns where code can be rolled out to all servers while features remain hidden behind flags until the deployment is verified. Teams can gradually increase feature flag exposure percentages as confidence grows, essentially creating a rolling deployment for both infrastructure and feature adoption simultaneously.

Feature flags with kill switch

Feature flags serve as the primary mechanism for implementing kill switch functionality, providing granular control over individual features rather than entire application deployments. When integrated with monitoring systems, feature flags can automatically trigger kill switch behavior by disabling problematic features instantly without requiring full deployment rollbacks. This approach allows surgical precision in addressing production issues while maintaining overall application availability.

The kill switch strategy becomes more powerful when feature flags are centrally managed and can be toggled in real-time across all application instances. Teams can implement automated kill switches that monitor key performance indicators and automatically disable features when thresholds are breached, while also maintaining manual override capabilities for immediate human intervention during critical incidents.

Rolling Deployment offers the significant advantage of zero-downtime updates by gradually replacing instances of the old version with the new one, maintaining service availability throughout the process. This approach allows for real-time monitoring of the deployment’s impact and provides natural load balancing as traffic shifts between versions. However, rolling deployments can be slower to complete since they update incrementally, and they create temporary inconsistencies where multiple versions run simultaneously. This mixed-version state can complicate debugging and may cause issues with database migrations or API compatibility. Additionally, if problems arise, rollback requires reversing the entire rolling process, which can be time-consuming.

Kill Switch Deployment provides fast, atomic updates where all instances switch simultaneously from old to new version, eliminating version inconsistencies and simplifying system state management. The rollback process is instantaneous—simply flip the switch back—making it ideal for critical fixes or when you need immediate, predictable changes across all users. However, this strategy typically requires brief downtime during the switch, which may be unacceptable for high-availability services. There’s also higher risk since all users experience the new version simultaneously, meaning any critical bugs affect the entire user base at once. Choose rolling deployments for user-facing applications requiring high availability and gradual risk mitigation, while kill switch deployments work best for internal systems, emergency patches, or environments where brief downtime is acceptable in exchange for deployment simplicity and speed.

What is an example of a rolling deployment strategy?

A rolling deployment strategy involves gradually updating application versions across servers in small batches rather than all at once. For example, if you have 10 servers running your application, you might update 2 servers at a time with the new version while the remaining 8 continue serving traffic with the old version. Once the first batch is successfully updated and verified, you move to the next batch of 2 servers, continuing this process until all servers are running the new version. This approach maintains service availability throughout the deployment process since some servers are always operational.

How does rolling deployment compare to canary deployment?

Rolling deployment and canary deployment are both gradual release strategies, but they differ in their approach and scope. Rolling deployment focuses on incrementally updating infrastructure by replacing servers or instances in batches until the entire system runs the new version. Canary deployment, on the other hand, releases the new version to a small subset of users or traffic (typically 5-10%) while the majority continues using the stable version. Rolling deployment is primarily about infrastructure updates, while canary deployment is about controlled user exposure to validate the new version before full release.

What are the differences between rolling deployment and blue-green deployment?

Rolling deployment updates systems gradually in batches while maintaining partial availability throughout the process, creating a mixed-version environment temporarily. Blue-green deployment maintains two identical production environments (blue and green) where you deploy the new version to the inactive environment, test it completely, then switch all traffic instantly from the active to the newly updated environment. Rolling deployments take longer to complete but provide continuous availability, while blue-green deployments offer faster, atomic switches with brief downtime but require double the infrastructure resources.

How do rolling deployment, blue-green deployment, and canary deployment strategies compare?

These three strategies differ primarily in risk management, speed, and resource requirements. Rolling deployment gradually replaces instances while maintaining partial availability, offering moderate risk with slower deployment speed and standard resource usage. Blue-green deployment provides instant switching between two complete environments, offering low risk with fast switching but requiring double the infrastructure. Canary deployment releases to a small user subset first, providing the lowest risk through real user validation but requiring sophisticated traffic routing and monitoring capabilities. Rolling is best for high-availability requirements, blue-green for systems that can tolerate brief downtime, and canary for user-facing applications where real-world validation is critical.

What is the recreate deployment strategy and how does it work?

The recreate deployment strategy involves completely shutting down all instances of the current application version before deploying the new version. This approach first terminates all running instances, then deploys and starts the new version across all servers simultaneously. While this strategy is the simplest to implement and ensures no version conflicts or mixed states, it results in complete service downtime during the deployment process. The recreate strategy is typically used for applications where downtime is acceptable, such as internal tools, batch processing systems, or during scheduled maintenance windows where brief service interruptions won’t impact users significantly.