Automating the Experimentation Lifecycle with Kiro, AWS DevOps Agent, and LaunchDarkly

This article describes a reference solution that automates the experimentation lifecycle by combining AWS DevOps Agent for orchestration, Kiro CLI for code generation, and LaunchDarkly for feature flag governance and guarded rollouts.

• AWS DevOps Agent runs as a Custom Agent on a schedule to orchestrate the full experimentation workflow autonomously
• Kiro CLI implements code changes behind feature flags in headless mode without human IDE interaction
• LaunchDarkly manages feature flags, runs A/B experiments on fixed traffic slices, and executes guarded rollouts with automatic rollback on metric regressions
• The workflow follows a Plan-Prove-Iterate cycle: define goals, generate hypotheses, implement behind flags, validate through release review, deploy, measure impact, and iterate
• Guarded Releases monitor operational guardrails (error rate, latency) and automatically revert flag state at runtime if thresholds are breached, eliminating redeployment delays
• Integration uses MCP servers: LaunchDarkly's hosted MCP server for flag management and the custom Experiment MCP Server for code implementation and deployment
• Safety boundaries include mandatory release readiness review, feature flags before code changes, fixed-percentage experiments before rollouts, and automatic rollback on guardrail breaches

This architecture reduces experimentation overhead by automating planning, connecting measurement to action through real-time monitoring, and enabling continuous iteration informed by recorded outcomes.