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Caching & Background Work

Redis, cache consistency, task ownership, retries, job idempotency, worker lifecycles, and stale work.

24 drillsPractice one at a timeOrdered pathConcept questionComparison questionArchitecture scenarioDebugging scenario

Recommended start

Queue vs Request

Explains when backend work belongs in a queue instead of slow or unreliable inline request handling.

Easy~5 minStep 1 of 24

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1Queue vs RequestRecommended startExplains when backend work belongs in a queue instead of slow or unreliable inline request handling.Concept questionEasy~5 min.NETAmazon SQSAzure Service BusPractice 2

Practice order

24 drillsOne at a time

1Queue vs RequestUp next / Easy / ~5 min
2FastAPI background-task limitsMedium / ~10 min
3Celery acknowledgement and redeliveryHard / ~15 min

FastAPI background-task limitsChooses between small in-process follow-up work and durable, independently operated background execution.Comparison questionMedium~10 minFastAPIPython

Practice

3Celery acknowledgement and redeliveryExplains early and late acknowledgement without promising exactly-once task execution.Concept questionHard~15 minPythonPractice

4At-least-once DeliveryExplains why message handlers must tolerate duplicate delivery and how idempotency protects side effects.Concept questionHard~9 min.NETAmazon SQSAzure Service BusPractice

5Safe Celery retriesCombines selective Celery retries with bounded backoff, idempotent effects, and a terminal failure path.Architecture scenarioHard~15 minPythonPractice

6Retry PolicyExplains retry strategy for transient failures and poison-message handling for permanent failures.Concept questionMedium~7 min.NETAmazon SQSAzure Service BusPractice

7DLQ RecoveryExplains how to inspect, fix, replay, skip, or archive dead-letter messages without repeating bad side effects.Debugging scenarioHard~12 min.NETAmazon SQSAzure Service BusPractice

8Celery task payloads and versioningKeeps Celery messages small, safe to deserialize, and compatible across rolling deployments.Architecture scenarioHard~15 minPythonPractice

9Competing ConsumersExplains how multiple worker instances share queue work and what limits safe scaling.Architecture scenarioMedium~10 min.NETAmazon SQSAzure Service BusPractice

10Celery concurrency and prefetchTunes worker pools and reservation behavior to task shape instead of maximizing a single concurrency number.Architecture scenarioHard~15 minPythonPractice

11Message OrderingPreserves order only within the business key that requires it, while handling hot keys, gaps, stale events, replay, and poison messages explicitly.Architecture scenarioHard~12 min.NETAmazon SQSAzure Service BusPractice

12Safe Celery periodic tasksSeparates single scheduler ownership from task-level overlap and idempotency controls.Architecture scenarioHard~15 minPythonPractice

13Queue LagExplains operational signals for queue-backed systems and how to respond when consumers fall behind.Debugging scenarioMedium~10 min.NETAmazon SQSAzure Service BusPractice

14Cache-aside ReadsExplains the cache-aside pattern for read-heavy endpoints and how misses, TTLs, and source-of-truth reads fit together.Concept questionEasy~5 min.NETASP.NET CoreRedisPractice

15Django cache key configurationUses Django cache configuration to control freshness, namespace sharing, and safe cache migrations.Concept questionMedium~10 minDjangoPythonPractice

16TTL StrategyExplains how TTL choices balance freshness, load reduction, user expectations, and operational safety.Concept questionEasy~5 min.NETASP.NET CoreRedisPractice

17InvalidationExplains delete-on-write, versioned keys, event-driven invalidation, and the race conditions around cache freshness.Concept questionMedium~7 min.NETASP.NET CoreRedisPractice

18Scoped Cache KeysExplains cache-key scope for tenant, user, role, locale, filters, response version, and security-sensitive reads.Concept questionMedium~7 min.NETASP.NET CoreRedisPractice

19redis-py client and pool lifecycleReuses bounded redis-py pools for the application lifetime and closes async resources deliberately.Architecture scenarioHard~15 minPythonPractice

20Redis batching and atomicityDistinguishes fewer network round trips from atomic execution and chooses the smallest correct Redis primitive.Comparison questionHard~15 minPythonPractice

21StampedeExplains what happens when a hot key expires and how request coalescing, TTL jitter, background refresh, and stale serving help.Concept questionMedium~7 min.NETASP.NET CoreRedisPractice

22Rejecting stale background workUses expected versions and conditional writes so delayed or retried Python tasks cannot commit stale decisions.Architecture scenarioHard~15 minPythonPractice

23Redis OutageExplains how an API behaves when Redis is unavailable and which cache usages can safely fall back.Concept questionMedium~7 min.NETASP.NET CoreAzurePractice

24Locks and LeasesExplains the risks of Redis-based distributed locks and when database constraints, queues, or idempotency are safer.Concept questionHard~9 min.NETASP.NET CoreRedisPractice

4

At-least-once Delivery

Hard / ~9 min

5Safe Celery retriesHard / ~15 min

6Retry PolicyMedium / ~7 min

7DLQ RecoveryHard / ~12 min

8Celery task payloads and versioningHard / ~15 min

+16 more drills in this section

Caching & Background Work - Python Backend | Aporeon