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Level 8 / Project 09 - Graceful Degradation Engine

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— This project — — Flashcards — —

Focus

  • Circuit breaker pattern: closed, open, half-open state machine
  • Sliding window error-rate calculation with collections.deque
  • Service tier degradation: full, reduced, minimal, offline
  • Feature flags tied to degradation tiers
  • Recovery testing with half-open state and request limits

Why this project exists

Production systems must degrade gracefully rather than fail completely. When a database slows down, the right response is not a 500 error page: it is disabling non-essential features (search, recommendations, exports) while keeping core functionality alive. This project implements a circuit-breaker-style degradation engine that monitors error rates and progressively reduces service quality, the same pattern used by Netflix, AWS, and every major cloud platform to maintain availability during partial outages.

Run (copy/paste)

cd <repo-root>/projects/level-8/09-graceful-degradation-engine
python project.py --window 20
pytest -q

Expected terminal output

{
  "final_status": {"circuit_state": "closed", "service_tier": "full", ...},
  "timeline": [
    {"step": 0, "circuit_state": "closed", "service_tier": "full", ...},
    ...
  ]
}
7 passed

Expected artifacts

  • Console JSON output with degradation timeline
  • Passing tests
  • Updated notes.md

Alter it (required)

  1. Add a HALF_OPEN state to the circuit breaker that lets a single request through to test recovery.
  2. Add a recovery_time_seconds parameter that controls how long the circuit stays open before testing.
  3. Add per-tier feature lists (e.g. tier DEGRADED disables search but keeps core reads).

Break it (required)

  1. Set failure_threshold=0: does the engine immediately open the circuit?
  2. Record successes rapidly after failures: does the sliding window correctly age out old entries?
  3. Set window_size=0 on SlidingWindowTracker: what happens to error rate calculation?

Fix it (required)

  1. Validate that failure_threshold > 0 and window_size > 0 in __init__.
  2. Add a guard for division by zero in error rate calculation when the window is empty.
  3. Add a test for the HALF_OPEN to CLOSED recovery transition.

Explain it (teach-back)

  1. What is the circuit breaker pattern and how does it differ from simple retry logic?
  2. How does the sliding window tracker calculate error rate and why is it time-based?
  3. What are service tiers (FULL, DEGRADED, MINIMAL) and how do real systems use them?
  4. Why is graceful degradation preferable to a complete outage?

Mastery check

You can move on when you can: - draw the state machine for CLOSED to OPEN to HALF_OPEN to CLOSED, - explain why sliding windows are better than cumulative counters for error rates, - describe a real-world degradation scenario (e.g. Netflix disabling recommendations), - add a new tier with specific feature restrictions without modifying existing tiers.

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