Scalability and Rollback Efficiency of Kubernetes Deployment Patterns: A Study of Blue-Green vs. Canary Approaches

In cloud-native software development, continuous deployment strategies significantly influence application availability, reliability, and maintainability. This study presents a comparative analysis of two widely adopted Kubernetes deployment patterns—Blue-Green and Canary—focusing on their scalability, rollback efficiency, and resource utilization in microservices-based web applications. Using a controlled Kubernetes environment, traffic simulations were executed via K6 to replicate real-world load scenarios, including linear ramp-ups, burst loads, and sustained user concurrency. Key performance metrics such as pod startup time, request latency (P50, P90, P99), CPU/memory utilization, and rollback duration were collected and analyzed using Prometheus and Grafana dashboards. Results show that while Blue-Green deployments offer faster rollback and simpler version control, Canary deployments provide finer traffic control and greater fault isolation during incremental releases. The findings highlight critical trade-offs in deployment strategy selection and provide operational insights for DevOps teams seeking to optimize reliability and service continuity in Kubernetes clusters. The study contributes to deployment automation best practices and supports informed decision-making for scalable, resilient microservice delivery pipelines.