Course overview
Start hereAI for DevOps Engineers
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Ravi's Wednesday, two ways

8 lessons · 25 prompts

A day in the life of a DevOps Engineer: what changes with these prompts.

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Ravi, a DevOps engineer at a growing e-commerce company.

Ravi starts his Wednesday with a red pipeline. A Jenkins job failed overnight because of a bad Docker tag. He opens ChatGPT, pastes the error, and asks for a fixed Jenkinsfile. The AI gives him a corrected snippet and explains the tag change. Ravi tests it and the pipeline goes green before standup.

Next, he reviews a Terraform plan for a new RDS instance. He asks Claude to check for missing tags and security group rules. Claude points out two things he missed. Ravi updates the plan and sends it for approval.

After lunch, an alert fires: a Kubernetes pod keeps restarting. Ravi uses Gemini to turn the logs and events into a troubleshooting plan. The plan suggests checking memory limits and a liveness probe. He finds the limit is too low, fixes the YAML, and the pod stabilizes.

Before he logs off, Ravi asks ChatGPT to scan a cost report for idle EC2 instances. It finds three he can stop. He does, then closes his laptop at 5:30. Instead of staying late, he takes his dog for a long walk and cooks dinner with his family.

Before

  • Firefighting from the first email
  • Manually editing YAML and Terraform
  • Alerts without a clear next step
  • Never enough time for deep work

After this course

  • Pipeline fixed before standup
  • Terraform reviewed in minutes
  • Incident triaged with a clear plan
  • Home on time, dog walked

What you'll learn

  • CI/CD pipelines: Draft, debug, and improve pipeline configuration for platforms like Jenkins, GitHub Actions, or GitLab CI.
  • Infrastructure as code: Generate and review Terraform, CloudFormation, or Ansible code for cloud resources.
  • Kubernetes manifests: Write and troubleshoot YAML for deployments, services, and resource limits.
  • Incident triage: Turn alerts, logs, and symptoms into a structured troubleshooting plan and clear updates.
  • Monitoring and alerts: Draft alert rules, SLOs, and dashboards from your service expectations.
  • Cloud cost and scaling: Estimate costs, draft autoscaling policies, and find waste in resource reports.
  • Security and secrets: Review access policies, explain scan findings, and draft secrets handling guidance.
  • Runbooks and handoffs: Turn system knowledge into runbooks, postmortems, and team handoff notes.

How this course works

  1. 8 lessonsOne task of your job each, from ci/cd pipeline drafts to runbooks and collaboration.
  2. Ready-to-paste promptsCopy, fill in the parts in {{brackets}}, paste into ChatGPT, Claude or Gemini.
  3. Tick and completeTick the prompts you tried and mark each lesson complete.
  4. Get certifiedFinish and keep the prompts as your own library.