"Use a dedicated AI agent gateway to place governance boundaries outside execution systems, preventing agents from directly interacting with sensitive infrastructure. Use policy as code with OPA to authorize every agent-initiated action based on identity, intent, and context instead of embedding authorization logic in application code. Use OpenTelemetry-based observability to verify, debug, and audit agent behavior through traces, metrics, and logs rather than relying on inferred correctness."
"Many engineering teams are experimenting with automation beyond traditional scripts and pipelines. Instead of humans clicking through dashboards or manually approving changes, a practice often referred to as " ClickOps", some organizations are beginning to delegate operational tasks to autonomous or semi-autonomous agents. These agents may generate infrastructure changes, trigger deployments, or respond to operational signals with little or no human intervention. Unlike traditional CI/CD bots, which execute predefined pipelines with static permissions and deterministic inputs, agent-driven systems introduce dynamic decision-making and cross-system actions at runtime."
AI-driven agents perform dynamic, cross-system actions across CI/CD platforms, cloud APIs, infrastructure-as-code tools, and internal services, increasing risk when granted broad or persistent permissions. A dedicated AI agent gateway should place governance boundaries outside execution systems to prevent direct access to sensitive infrastructure. Policy-as-code with OPA should authorize every agent-initiated action based on identity, intent, and context instead of embedding authorization in application code. OpenTelemetry-based observability should verify, debug, and audit agent behavior via traces, metrics, and logs. Short-lived, isolated execution runners and the MCP+OPA+ephemeral runner pattern can contain blast radius and ensure predictable cleanup.
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