Anonymised under NDA
AI-augmented DevOps for a regulated enterprise
Cross-industry · A regulated enterprise platform team
DevOps AI agent that triages incidents, proposes runbook actions, and augments PR review across a multi-cluster Kubernetes estate.
The problem
- Mean time to detect was driven by alert fatigue, not by tooling capability.
- Runbooks lived in wikis and were rarely consulted under incident pressure.
- Code review was a bottleneck and an inconsistent quality gate.
The architecture
- Incident-triage agent correlating alerts, traces, and recent deployments to produce a first-pass diagnosis.
- Runbook agent grounded in a vector index of internal runbooks, with explicit human approval before any remediation.
- PR-review agent enforcing internal standards, with hosted-model and open-source-model options chosen per repository sensitivity.
KubernetesOpenTelemetryDatadogLangGraphClaudeLlama
The outcome
- First responders entered every incident with a curated diagnosis and a recommended next step.
- Engineering teams shipped faster with a more consistent review baseline; humans retained final authority on every change.
Services drawn on
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