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Capstone — Python for DevOps

The capstone ties the whole course together into one project. You don't need every piece — even one clean, working, end-to-end flow is enough to be interview-ready.

The story these modules tell

Every module in this course builds one capability. The capstone assembles them:

   log analysis          ->  03-file-handling-and-logs  +  04-object-oriented-python
        |
   run it as a CLI        ->  05-cli-tools-argparse
        |
   pull in cloud data     ->  06-aws-automation-boto3
        |
   expose it as an API    ->  07-apis-with-fastapi
        |
   add an AI layer         ->  08-ai-agents-for-devops   (optional, impressive)

What to build

Pick a scope and make it clean, commented, and runnable:

  • Minimum: the log analyzer as a CLI tool (05-cli-tools-argparse) that writes a JSON summary.
  • Solid: wrap the log analyzer + system metrics in a FastAPI service (07-apis-with-fastapi) with /health, /logs, /metrics.
  • Impressive: add the AWS report endpoint and/or the local AI log agent.

The reference implementation of the "Solid + AWS" tier already lives in ../07-apis-with-fastapi/devops-utilities-api. Use it as your starting point, or build your own.

Deliverables

  1. A working project (one clean flow is enough).
  2. A project-level README.md explaining what it does and how to run it.
  3. A STAR explanation (see below) you can use in interviews.

Explain it with the S.T.A.R method

Fill in STAR.md:

  • Situation — what was the problem? (e.g. "logs grew daily; manual checks were slow")
  • Task — what were you responsible for? (e.g. "automate log analysis in Python")
  • Action — what did you actually do? (parse logs, CLI, API, AI summary)
  • Result — what was the outcome? (faster visibility, less manual effort)

Checklist before you call it done

  • Code runs without errors from a clean venv
  • README.md explains setup + run steps
  • Functions are named clearly and commented where needed
  • Errors are handled (missing file, bad input, failed API call)
  • STAR.md written and rehearsed

What comes next

CI/CD, Kubernetes, monitoring, cloud architecture — Python for DevOps was your foundation. Keep going: DevOps – Zero To Hero.