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Interactive roadmap

DevOps / SRE + AI

Reliable operation of AI workloads

Serving, autoscaling, observability, cost control, security, and incident response for AI systems.

10–16 weeksDevOps engineersSREPlatform engineers
Open as course →Every node has an evidence route
3stages
8nodes
1projects and milestones
01 · Shared AI core02 · AI runtime and serving03 · Observability and incidents
  1. 01

    Shared AI core

    Probabilistic failure modes and verifiable model behavior.

    Stage outcomeSRE understands the operational risks and limits of AI systems.
    Materials ready
    Article →
    Materials ready
    Prerequisites: AI literacy and model limits
    Article →
    Materials ready
    Prerequisites: Prompt and context engineering
    Article →Article →
  2. 02

    AI runtime and serving

    Inference, batching, queues, and scaling for production workloads.

    Stage outcomeA controlled inference service with explicit capacity and health signals.
    Materials readyAssessment available
    Open practicum →Assessment rubric →Article →
    Materials readyAssessment available
    Open practicum →Assessment rubric →Article →
  3. 03

    Observability and incidents

    Tracing, costs, alerts, rollback, and operational drills.

    Stage outcomeAn AI platform with measurable SLOs and a tested recovery path.
    Materials readyAssessment available
    Open practicum →Assessment rubric →Article →
    Materials readyAssessment available
    Open practicum →Assessment rubric →
    Materials readyAssessment available
    Open practicum →Assessment rubric →Article →