Course Objective & Scope
During production outages, on-call engineers lose precious minutes jumping between dashboards, massive log streams, recent Git deployments and scattered runbooks, driving up Mean Time to Resolution (MTTR). This course teaches how to combine LLMs with observability pipelines to accelerate triage and root-cause analysis safely.
Querying Prometheus/Grafana, OpenTelemetry, ELK/Datadog and Kubernetes events via read-only MCP tools, alert clustering, correlating symptoms with recent PRs and config changes, executing human-approved runbook actions, and generating automated incident timelines and post-mortems are practised on simulated outages.
Who Should Attend?
- Site Reliability Engineers (SREs) and platform engineers
- DevOps, cloud infrastructure and systems engineers
- IT operations (IT Ops), NOC and incident management teams
- Prerequisite: experience with Linux/container infrastructure and observability stacks (logs, metrics, alerts)
Key Takeaways
- Correlate noisy alert storms into concise, high-signal incident briefs for on-call responders
- Link metric spikes and error logs with recent code deploys and infrastructure changes
- Connect internal runbooks and read-only diagnostic commands into Slack/Teams incident channels
- Enforce strict read-only vs. write guardrails so remediation actions always require human approval
- Generate accurate incident timelines and blameless post-mortem drafts automatically
Curriculum
AIOps and LLM Agent Architecture in Incident Management
- Combining statistical anomaly detection with context-aware LLM triage assistants
- The production golden rule: automated read-only diagnostics, human-approved remediation
Correlating Observability Signals (Logs, Metrics, Traces)
- Querying OpenTelemetry traces, log error clusters and Kubernetes/cloud events via MCP
- Scrubbing PII and secrets from telemetry before sending context to models
Change Intelligence and Root-Cause Hypothesis Generation
- Matching incident onset against recent Git PRs, feature-flag flips and Terraform/Helm diffs
- Ranking competing root-cause hypotheses with concrete verification queries
Interactive Runbook Assistants and ChatOps Integration
- Grounding on-call assistants in internal runbooks and historical incident tickets
- Drafting stakeholder status updates and executing gated commands from Slack/Teams war rooms
Post-Mortem Automation and Continuous Reliability Loops
- Synthesising war-room transcripts, metrics and actions into an accurate incident timeline
- Generating blameless post-mortems, identifying alert gaps and updating runbooks
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