AUTOMATED PERFORMANCE BASELINES IN DOCKERIZED ENVIRONMENTS AND GITOPS PRINCIPLES
Keywords:
Automated Performance Baselines, Docker, GitOps, Containerized Environments, Continuous Deployment, Performance Monitoring, Regression Detection, Cloud-Native Systems.Abstract
The fast use of containerization and GitOps in cloud-native environments means that there has to be strong ways to make sure that applications work the same way throughout continuous deployments. This research suggests a theoretical framework for automated performance baselines in Dockerized systems, incorporating GitOps principles to proactively identify deviations and regressions. We kept an eye on performance indicators including response time, CPU usage, memory usage, and container startup latency during several simulated deployment cycles. The results show that automated baselining, along with GitOps-driven validation and rollback procedures, can find performance problems, keep the system stable, and support performance governance that can be repeated and scaled. This method shows that it is possible to make modern DevOps workflows more reliable and consistent in how they work.
