Prompt index

All prompts

A single index for every routeable design exercise. Canonical prompt pages live under the classic or ML system design tracks.

classic system designL5 backend interview

Design a distributed rate limiter

Enforce tenant and user quotas across API gateways without turning Redis into the only thing that matters.

quota modelingRedis countershot-key mitigationidempotency
classic system designL5 backend interview

Design a durable job scheduler

Run delayed and recurring work with retries, backoff, leases, and a clean story for duplicate execution.

leasesretry queuescron semanticsidempotency
classic system designL5 backend interview

Design a distributed cache

Protect a database from hot reads while staying honest about invalidation and stale data.

cache keysTTL designinvalidationconsistent hashing
classic system designL4 to L5 backend interview

Design a URL shortener

Generate short links, redirect at high read volume, and handle abuse without losing the simple core.

id generationread-heavy storageanalytics pipelineabuse controls
classic system designL5 backend interview

Design a message queue

Move work between producers and consumers with leases, ordering boundaries, and backpressure.

delivery semanticspartitioningbackpressuredead-letter queues
classic system designL5 product infrastructure interview

Design a notification system

Send email, push, and in-app notifications while respecting preferences, dedupe, and provider failures.

fanouttemplate versioningpreferencesprovider failover
classic system designL5 search infrastructure interview

Design a search indexing system

Keep a searchable index fresh while writes, deletes, and ranking signals arrive from different services.

inverted indexeschange data capturebackfillsfreshness SLIs
classic system designL5 infrastructure interview

Design an observability pipeline

Collect logs, metrics, and traces without making every outage an ingestion-cost problem.

telemetry ingestionsamplingcardinality controlretention tiers
ML system designSenior MLE / ML system design interview

Design a RAG system

Build retrieval, generation, citation, and evaluation loops that do not collapse into a demo prompt.

chunkingembedding retrievalrerankingevaluation
ML system designSenior MLE / ML platform interview

Design a model serving platform

Serve models with versioning, autoscaling, canaries, and rollback paths that operators can trust.

online inferenceautoscalingcanary rolloutmodel registry
ML system designSenior MLE / data platform interview

Design a feature store

Keep online and offline features aligned enough that model scores mean what training said they meant.

point-in-time correctnessonline/offline parityfeature lineagefreshness
ML system designSenior MLE / ML infrastructure interview

Design an ML evaluation platform

Run offline, online, and regression evaluations with lineage strong enough to stop bad releases.

eval datasetsmetricsexperiment trackingrelease gates
ML system designSenior MLE / search infrastructure interview

Design a vector search service

Serve nearest-neighbor retrieval with filtering, index refresh, recall measurement, and cost controls.

nearest neighborsmetadata filteringindex refreshrecall evaluation
ML system designSenior MLE / ML platform interview

Design a distributed training pipeline

Coordinate data, checkpoints, accelerators, and recovery for large training jobs.

distributed trainingcheckpointingdata loadingcluster scheduling