How do you monitor performance during automated deployments?

Automated deployment enables efficient releases through tools like Jenkins or CI/CD pipelines. Performance monitoring identifies application health issues during this process to ensure deployment quality. Its importance lies in reducing downtime risks and enhancing release reliability, typically applied in DevOps and cloud-native environments.

Core components include integrated monitoring platforms such as Prometheus and Grafana, featuring real-time metric collection (e.g., CPU load, response time) and automatic alerts. In practical applications, by defining baseline thresholds and embedding detection points in the deployment phase, performance bottlenecks are exposed in advance, improving system stability and reducing rollback frequency.

Implementation steps: First, configure monitoring agents and dashboards in the CI/CD pipeline. Second, define key metrics (e.g., latency, error rate) and set up automated alerts. Then, perform post-deployment health checks (e.g., through synthetic tests), pausing the process if anomalies are triggered. Business values include accelerating release cycles, reducing repair costs, and enhancing user trust.