{
  "uid": "cogitave.learn.observability-and-reliability",
  "kind": "module",
  "href": "/modules/observability-and-reliability/",
  "title": "Observability and reliability",
  "summary": "Instrument a service with OpenTelemetry-spec traces, metrics, and logs, understand why agent traces are kept as evidence, and reason about reliability through SLIs, SLOs, error budgets, and the policy that turns a spent budget into a release freeze.",
  "type": null,
  "products": [
    "cogitave-core"
  ],
  "roles": [
    "developer"
  ],
  "levels": [
    "intermediate"
  ],
  "subjects": [
    "software-engineering"
  ],
  "headings": [],
  "source": "By the end of this module, you'll be able to:\n- Describe Cogitave's telemetry model - OpenTelemetry-spec traces, metrics, and logs under one correlation, bound to the Core model and queryable from MCP.\n- Explain what AI/agent observability adds - the agent trace, token and cost, eval drift, and inference records kept as responsible-AI evidence.\n- Define an SLI, an SLO, and an error budget, and compute a budget from an SLO and a window.\n- State the error-budget policy - the rule that converts a spent budget into a per-service feature freeze - and why the SLA is always looser than the SLO.\n- Read the observability and reliability standards as the source of truth and follow them for the detail.\n",
  "units": [
    "cogitave.learn.observability-and-reliability.introduction",
    "cogitave.learn.observability-and-reliability.instrument-for-observability",
    "cogitave.learn.observability-and-reliability.reliability-and-slos",
    "cogitave.learn.observability-and-reliability.knowledge-check",
    "cogitave.learn.observability-and-reliability.summary"
  ],
  "durationInMinutes": 26,
  "badge": "cogitave.learn.observability-and-reliability.badge",
  "partOf": "cogitave.learn.paths.engineering-standards"
}