Rate limiting lab
Run the rate limiting baseline
One clean transaction through **POST /v1/rag/answer** must match the oracle: StormCo at 200 RPM gets 429 after burst; Globex at 40 RPM unaffected.
1Learn the idea
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Order the successful transaction
Code the narrow path that serves platform SRE stopping noisy neighbor tenant StormCo: accept → authorize/normalize → call dependency → validate → record. Keep stages named so a trace can show which boundary passed. Success must emit evidence useful to 429_ratio_by_tenant and provider_429_ratio ≤ 0.01, not only a 200 with prose. Predict the observable for POST /v1/rag/answer before running: StormCo at 200 RPM gets 429 after burst; Globex at 40 RPM unaffected.
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Run with fakes first
Drive the path with recording fakes or local stubs. Assert call order and arguments. Idempotency keys or stable ids should keep retries from duplicating costly work where the product requires it. Product under test remains layered token-bucket limiter for multi-tenant RAG API — resist adding unrelated features mid-path.
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Implementation artifact
d = limiter.check(tenant="globex", cost=1)
assert d.allow and d.remaining >= 0
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Compare prediction to result
For Rate limiting lab, paste the CLI/HTTP transcript beside your prediction for POST /v1/rag/answer. If the oracle is unmet (StormCo at 200 RPM gets 429 after burst; Globex at 40 RPM unaffected), stop and debug this page; do not compensate with prompt folktales. Re-run once after a clean process start to catch hidden global state that would invalidate RL-FAILOPEN-61.
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Stage depth
Performance sketch: measure local p95 for the fake-backed path so later regressions are obvious. Keep concurrency modest until failure-handling proves limits. Log a single structured event per success with request id, revision, and the evidence field behind 429_ratio_by_tenant and provider_429_ratio ≤ 0.01. Avoid hidden global caches in the happy path unless the lab is about caching — and even then key by tenant. If the path calls a model, pin model id in config and echo it in the response for auditability. Remember platform SRE stopping noisy neighbor tenant StormCo experiences wall-clock time, not your debugger’s single-step comfort.
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Field notes for `rate-limiting-lab` / `happy-path`
Prefer explicit function names over a single god-object handleRequest. Thread a correlation id from ingress to the last log line. When streaming, define what partial failure means before coding. Snapshot one successful response body in fixtures after redaction. If the path writes to a queue, assert message attributes in the fake. Stop adding retries on this page; that is the next concern. In this chapter the product is layered token-bucket limiter for multi-tenant RAG API, the human stakeholder is platform SRE stopping noisy neighbor tenant StormCo, and the incident id you design against is RL-FAILOPEN-61. Re-state the oracle in your notes — StormCo at 200 RPM gets 429 after burst; Globex at 40 RPM unaffected — and keep the invariant visible: tenant RPM soft=60 hard=100; global 5k RPM; 429 includes Retry-After. Track 429_ratio_by_tenant and provider_429_ratio ≤ 0.01 as the scoreboard. Surface under change control: POST /v1/rag/answer. If you only have forty minutes, finish the fixture for Redis down → fail-open floods provider → shared 429s before polishing UI. Promotion language stays ternary: promote, hold, or roll back based on evidence, not hope.
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Before you start
Why this matters
Without calling production, order the steps a single success takes for platform SRE stopping noisy neighbor tenant StormCo. Circle the first irreversible side effect. Your prediction should mention POST /v1/rag/answer and the evidence field that proves StormCo at 200 RPM gets 429 after burst; Globex at 40 RPM unaffected.
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Answer from memory. Completion is saved from this evidence, not from opening the next page.
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