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Level 5 / Project 11 - Retry Backoff Runner

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— This project — — Flashcards — Browser

Estimated time: 80 minutes

Focus

  • exponential backoff strategy practice

Why this project exists

This project gives you level-appropriate practice in a realistic operations context. Goal: run the baseline, alter behavior, break one assumption, recover safely, and explain the fix.

Run (copy/paste)

Use <repo-root> as the folder containing this repository's README.md.

cd <repo-root>/projects/level-5/11-retry-backoff-runner
python project.py --max-retries 5 --base-delay 0.1 --output data/retry_report.json
pytest -q

Expected terminal output

Success after 3 retries (total delay: 0.7s)
5 passed

Expected artifacts

  • data/retry_report.json
  • Passing tests
  • Updated notes.md

Checkpoint: Baseline code runs and all tests pass. Commit your work before continuing.

Alter it (required) — Extension

  1. Add jitter to the backoff delay (random variation) to prevent thundering-herd behavior.
  2. Add a --max-retries flag that overrides the default retry count from the command line.
  3. Log each retry attempt with the delay duration and the error that triggered it.
  4. Re-run script and tests.

Break it (required) — Core

  1. Set --max-retries 0 so no retries are allowed and the flaky function always fails.
  2. Set --base-delay to a negative number.
  3. Capture the first failing test or visible bad output.

Fix it (required) — Core

  1. Validate that max_retries >= 1 and base_delay > 0.
  2. Return a clear error report when all retries are exhausted.
  3. Add tests for zero retries and negative delay.
  4. Re-run until output and tests are deterministic.

Checkpoint: All modifications done, tests still pass. Good time to review your changes.

Explain it (teach-back)

  1. How does exponential backoff calculate the delay for each retry attempt?
  2. Why does create_flaky_function use a counter to simulate intermittent failures?
  3. What is jitter and why does it prevent thundering-herd problems?
  4. Where do you see retry with backoff in production (AWS SDK, HTTP clients, message queues)?

Mastery check

You can move on when you can: - run baseline without docs, - explain one core function line-by-line, - break and recover in one session, - keep tests passing after your change.

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