How do you implement agentic AI for automated deployment canary analysis?
Canary analysis agents evaluate the health of canary deployments by comparing metrics between canary and baseline instances. Configure agents with access to monitoring systems, deployment pipelines, and statistical analysis tools. The agent collects comparable metrics from canary and baseline populations including error rates, latency distributions, and business metrics. Implement statistical comparison using techniques like Mann-Whitney U tests and Kolmogorov-Smirnov tests to detect significant differences. Configure sensitivity thresholds per metric to balance detection accuracy with false positive rates. Generate canary verdict reports with pass or fail decisions and supporting evidence. Support automated promotion of successful canaries and rollback of failed ones. Track canary analysis accuracy over time to calibrate statistical thresholds.