Architecture

Cache-Fronted Object Storage

Placing a cache layer (SSD, Alluxio, CDN, or in-memory cache) in front of S3 to serve frequently accessed objects with lower latency while maintaining S3 as the durable source of truth.

4 connections 2 resources

Summary

What it is

Placing a cache layer (SSD, Alluxio, CDN, or in-memory cache) in front of S3 to serve frequently accessed objects with lower latency while maintaining S3 as the durable source of truth.

Where it fits

Cache-fronted architectures bridge the gap between S3's high durability and the low-latency needs of interactive applications. The cache absorbs hot read traffic, reducing S3 API costs and latency, while S3 provides infinite-scale cold storage.

Misconceptions / Traps
  • Cache invalidation is the hard problem. When S3 objects are updated, the cache must be invalidated or refreshed — otherwise clients see stale data. Event-driven invalidation (S3 notifications) helps but adds complexity.
  • Cache hit ratio determines economic viability. If the working set is too large or access patterns are random, the cache adds cost without reducing S3 traffic.
Key Connections
  • solves Cold Scan Latency — cache hit eliminates S3 round-trip
  • solves Egress Cost — cache at the edge reduces cross-region data transfer
  • scoped_to Separation of Storage and Compute, Object Storage

Definition

What it is

Placing a cache layer (local SSD, distributed cache like Alluxio, or CDN) in front of S3 to absorb hot-path reads, reduce S3 API call volume, and lower access latency for frequently accessed objects.

Why it exists

S3 charges per-request and has network latency per access. A cache layer collapses repeated reads of the same objects, reducing both cost and latency for read-heavy workloads while S3 remains the durable source of truth.

Primary use cases

Read-heavy analytics acceleration, CDN-fronted media delivery from S3, training data caching for repeated ML epochs, Alluxio-backed Spark/Trino acceleration.

Connections 4

Outbound 4

Resources 2