MuseOps

MuseOps: Autonomous SRE Incident Remediation Engine MuseOps is an autonomous SRE incident remediation pipeline designed to eliminate high MTTR during production outages. When runtime infrastructure failures (e.g., container OOMKilled events) occur, MuseOps ingests noisy log streams from CloudWatch/Kubernetes, filters high-signal error context via parser.py, and passes structured failure data to Baseten’s meta-models/muse-spark-open-1026 endpoint. Muse generates a Root Cause Analysis (RCA) alongside dynamic HCL Terraform patch code (remediation_patch.tf). To guarantee safety in production, the pipeline enforces strict local AST static validation (terraform fmt, init, validate) via validator.py and stages binary execution plans (tfplan) under an auto_apply=False policy in remediation_executor.py for deterministic human-in-the-loop oversight. Technical stack: Python 3, Baseten Meta Model API, Muse, HCL Terraform, Pydantic, static code analysis tools.