Cache-Aside, Write-Through, and Write-Back
Lesson 25Intermediate56 minAssessment-backed

Cache-Aside, Write-Through, and Write-Back

Design cache-aside, write-through, and write-back using vendor-neutral architecture, real product constraints, and AWS/GCP/Azure implementation mapping.

What you will be able to do

Explain cache-aside, write-through, and write-back from requirements and constraints.
Identify production trade-offs across scale, reliability, cost, and operability.
Map the vendor-neutral design to AWS, GCP, and Azure services.
Prepare an assessment-grade answer with failure modes and alternatives.

Cache-Aside, Write-Through, and Write-Back is part of Mastering System Design. The lesson trains vendor-neutral architecture first, then maps the design to cloud services and production trade-offs.

Core Design Problem

This lesson focuses on the system-design decisions behind cache-aside, write-through, and write-back: what the system must do, how traffic and data grow, what must remain reliable, and where complexity should or should not be introduced.

Real-World Scenario

We will ground the concept in a realistic product case, then walk through read path, write path, storage, caching, asynchronous work, observability, and failure behavior where relevant.

AWS, GCP, and Azure Mapping

NeedAWSGCPAzure
Application cacheElastiCache for Redis/MemcachedMemorystoreAzure Cache for Redis
Edge cacheCloudFrontCloud CDNAzure Front Door/CDN
InvalidationCloudFront invalidationsCloud CDN invalidationAzure CDN purge
ProtectionWAF/ShieldCloud ArmorWAF/DDoS Protection

Trade-Off Matrix

OptionUse whenRisk
Simple single-service designTraffic and team size are smallMay bottleneck under growth.
Managed cloud serviceReliability and speed matter more than custom controlCost, limits, and vendor coupling.
Custom distributed designRequirements exceed managed defaultsHigher operational burden.

Failure patternsCommon Mistakes to Avoid

  • Starting with provider names before requirements.
  • Ignoring write path and operational failure modes.
  • Over-designing for imaginary scale.
  • Skipping latency, cost, security, and observability.
  • Failing to state what data must be consistent.

Execution guardrailQuick-Start Checklist

  • Clarify users and core flows.
  • Estimate reads, writes, storage, and peaks.
  • Choose the simplest architecture that satisfies constraints.
  • Name alternatives and trade-offs.
  • Map to AWS/GCP/Azure only after the architecture is clear.
  • Add failure handling and observability.

Interview signalFrequently Asked Interview Questions

  • How would you design cache-aside, write-through, and write-back for 10x traffic growth?
  • Which parts should be synchronous and which should be asynchronous?
  • What would you monitor, and what failure mode would page the team?

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Cache Invalidation