Distributed Systems · advanced
Distributed Infra
Service discovery, orchestration.
Mental model
Distributed systems multiply the ways things can fail. Every network call can be slow, retried, lost, or duplicated. Design for partial failure first — timeouts, idempotency, bounded queues — and worry about speed second.
How to study Distributed Infra
Begin by restating the mental model in your own words, then connect it to a concrete system you have built or operated. Name the mechanism, the constraint it addresses, and the trade-off it introduces. Use System Design Primer, Kubernetes — Cluster components, Consul — Service discovery explained to check details, but close the source before writing your explanation. Retrieval is the learning step; rereading is only preparation.
Next, compare Distributed Infra with the neighboring concepts in its roadmap. Ask what changes in correctness, latency, resource use, operability, and failure recovery. Complete Distributed rate limiter and preserve the command, input, output, and one failed attempt as evidence. Finish by explaining the idea without jargon to someone who has not studied the track.
Proof of understanding
- Explain the mechanism from first principles and identify the state it reads or changes.
- Give one situation where the concept is the right choice and one where it is not.
- Predict a realistic failure mode before running the drill, then compare the prediction with evidence.
- Connect the result to a roadmap or build artifact instead of treating the concept as isolated trivia.
Learn from primary sources
Practice and explain it back
Distributed rate limiter
Design a rate limiter for an API: 1000 req/min per user, deployed across 10 app servers. Compare token bucket vs sliding window, and where the counter lives.
Expected evidence: Algorithm choice + storage backend (Redis?) + how you handle a Redis outage.
Open the interactive drill →Review prompts
- A remote call times out. What do you actually know about whether it executed?
Build evidence
Synthesize: Distributed Systems
Reason about coordination, data placement, logs, durable workflows, consistency, and recovery under partial failure. Produce one working system, benchmark, or evidence-backed design that integrates the path.
- Implements or precisely models the core mechanisms from all three milestones
- Includes at least one injected failure or adversarial case and demonstrates recovery
- Reports quality, latency, resource, reliability, or usability measurements relevant to the domain
- Ships a concise architecture note explaining decisions, trade-offs, and remaining risks
Prerequisites
Related concepts
None assigned yet.