Most AI for DevOps content stops at asking a model to write YAML. This course goes further. You work against a real broken system with actual faults, tickets, and grading scripts, building agents that triage, remediate, and report, plus the boundaries that make them safe to point at production.

This Course Offers

• Real operations agents including a Kubernetes triage agent that ranks five simultaneous faults by blast radius and remediates through a separate write identity
• Infrastructure work covering a Terraform module authored test first, plus a release gate that emits a schema validated verdict and holds no deploy authority
• Context engineering as a budget, with scoped instruction files, evidence contracts, and bounded queries that stop a firehose of output
• Agent Skills compiled from runbooks and tested against positive, negative, and ambiguous cases, plus tool surface choices across CLI, wrapper script, Skill, or MCP server
• Enforcement through PreToolUse hooks, scoped RBAC identities, and GitOps, verified to still hold after the hook is removed

Why We Love This Course

1. It runs against a real system called Northstar Commerce with injectable faults and grading scripts, so nothing here is a toy example.
2. The guardrail focus is genuinely important. Role specific subagents with mechanically tested authority is the discipline most teams lack.
3. Claims are measured rather than asserted, including run costs and failures, which is rare in AI course material.
4. At nineteen hours across one hundred and thirty one lessons, it has the depth to cover context, cost, orchestration, and the operational scenarios properly.

Handing an agent production access without boundaries is how incidents happen, and this course treats that as the central problem rather than an afterthought. Do you want an assistant that writes YAML, or an agent you can actually trust with operations work? Enrollment is open, and Claude Code is taught from zero though the DevOps stack is assumed.

• This course is perfect for DevOps and SRE engineers who want agents doing real operations work.
• It suits platform engineers building guardrails their team's agents will run inside.
• Kubernetes, cloud, and DevSecOps engineers wanting AI help with triage without granting production write access will find the boundary design directly useful, though the course is not for engineers new to DevOps.

• Working knowledge of Git and the command line is expected.
• Comfort with Docker, Docker Compose, CI/CD pipelines, Kubernetes basics, Terraform basics, and metrics or logs is assumed.
• A Claude Pro or Max subscription is required, since every command runs on a subscription with no API key needed, plus a machine with Docker and at least 8 GB RAM.

Interested in exploring more lessons? Check out our full course library to continue building your skills and advancing your learning journey.