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Module Quiz

Complete this quiz after finishing all concept and practice pages. Save your answers before opening separate quiz calibration.

Current Module Questions​

Question 1: USE vs RED​

You are handed a new Postgres-backed microservice with zero monitoring. Name one metric you would put on a dashboard from the USE method and one from the RED method, and explain which question each answers.

Question 2: Percentile Reasoning I​

Service X has a latency distribution of [20, 25, 30, 35, 40, 45, 50, 55, 60, 65] ms (sorted). Service Y has [20, 22, 25, 28, 30, 32, 38, 42, 50, 468] ms.

a. Compute the mean latency for each. Are they similar? b. Compute p50 and p99 for each (use the 10th sample as p99 for this approximation). c. If a user page fans out to 10 independent requests, which service will more often produce a slow page?

Question 3: Percentile Reasoning II​

Your monitoring team wants to compute "cluster-wide p99" by taking the average of each instance's p99 and reporting that number. Is this valid? If not, what should they do instead?

Question 4: Amdahl vs USL​

A parallel data-processing job has 5% serial fraction (Amdahl's s). It also exhibits contention with USL parameters α = 0.05, β = 0. At N = 100 workers, which law predicts a higher throughput, and what is the practical takeaway?

Question 5: Stateless Design​

Your web tier uses sticky sessions because "it's faster." List two concrete failure modes this design has and propose a migration path.

Question 6: Caching​

A team caches a product row for 30 minutes using cache-aside. Prices change and the cache is not invalidated. What is the maximum staleness a user can see, and what update pattern would tighten this without killing hit rate?

Question 7: SLI/SLO/Error Budget Scenario​

Your service's SLO is 99.9% availability over 30 days. In the last 15 days of this window, you have observed:

  • total requests: 10,000,000
  • failed requests (5xx or > 1s latency): 11,000

a. What is the observed SLI? b. How much error budget has been consumed so far (as a percentage of the monthly budget)? c. A team wants to ship a risky feature tomorrow. What does the error-budget policy suggest? Justify.

Question 8: Failure Modes​

A single slow backend causes every caller's thread pool to saturate, which causes every upstream of those callers to also saturate. Which failure mode is this, what single pattern would have most contained it, and where in the call graph does the pattern go?

Question 9: Chaos Engineering​

Your team's leadership says "why would we break things in production when we already test in staging?" Give a two-sentence argument for a production chaos experiment, and describe the blast-radius controls that make it safe.

Question 10: Little's Law​

An HTTP server processes an average of 500 req/s with a mean response time of 200 ms. What is the average number of requests in-flight at any moment? Your thread pool is sized at 50. Is that enough?

Question 11: Load Shedding​

A service is receiving 10x its capacity in requests. You can either let all requests slow down to 10x latency, or fast-reject 90% and serve 10% fast. Which do you pick in general and why?

Question 12: Observability Pillars​

You get a bug report: "checkout is slow for some users but not others." You have access to metrics, logs, and traces. In what order do you use them and why?

Question 13: Incident Lifecycle​

You are paged at 3am for a latency SLO breach. You discover a deploy 5 minutes before the alert. What is the correct first action, and why is it not "root-cause the bug"?

Question 14: Blameless Postmortems​

An engineer accidentally dropped a production index during a migration, causing 40 minutes of outage. The easy finding is "Engineer X ran the wrong command." Write the correct root-cause framing.

Question 15: Composition​

A new feature is being designed. It reads from a database, computes a recommendation, and returns it. Combine ideas from three different clusters of this module to make it production-ready: one scaling idea, one reliability idea, and one observability idea.

Interleaved Review Questions​

Prior Module Question 1 (S6 Module 5: Distributed Systems Fundamentals)​

Why is a timeout the only mechanism a node has to distinguish "slow" from "dead," and what does that imply for back-pressure design under overload?

Prior Module Question 2 (S6 Module 3: Replication and Partitioning)​

How does cross-region replication interact with SLO design for write availability?

Prior Module Question 3 (S3 Module 2: Probability)​

Why does the binomial-tail intuition directly apply to tail-at-scale latency, and what does it predict about fan-out width?

Prior Module Question 4 (S5 Module 4: Networking)​

Why does HTTP/2 or HTTP/3 help tail latency, and where does it not?

Prior Module Question 5 (S2 Module 3: Data Structures)​

Why is the latency of a hash-table lookup often described as "amortized O(1)" but showing up as a tail spike in production?

Self-Assessment and Remediation​

Mastery Level (90-100% correct):

  • Ready for the capstone and any system-design interview round on reliability.
  • Your instinct should now be: when you see a production issue, map it to a specific cluster's vocabulary within a minute.

Proficient Level (75-89% correct):

  • Review missed concepts. Most gaps are in the percentile-reasoning and error-budget questions (2, 3, 7) - those reward fluency, not memorization.
  • Redo Practice 3 (Reliability and SLO Clinic) and one Kata from Practice 4.

Developing Level (60-74% correct):

  • Rework Cluster 1 (Performance Reasoning) and Cluster 3 (Reliability Engineering) end to end.
  • Redo Practice 1 (Performance Profiling Lab) and Practice 3 (Reliability and SLO Clinic).
  • Re-read the Google SRE Book chapters on SLIs/SLOs and on Managing Incidents; they will re-anchor your intuition.

Insufficient Level (<60% correct):

  • The module has not landed. Restart from the module index.md diagnostic questions. Identify which three concepts you cannot state in one sentence, and read the concept page plus its first "Read This Only If Stuck" link for each. Do not proceed to the capstone until you can pass this quiz above 75%.

Progression boundary​

Quiz performance calibrates retrieval and reasoning. It does not replace runnable work, changed-case transfer, the module assessment or required semester evidence. Consult practice calibration for the additional independent cases.