Reducing S3 latency for AI agents with Curvine
InfrastructureComments
The 100µs latency claim is ambitious, but I wonder how it accounts for the metadata overhead inherent in POSIX translations. Specifically, does this figure represent a warm cache hit on the local tier, or the actual end-to-end resolution of a file path?
The local cache hit is likely the only way to hit those numbers. Even so, it beats the 50 to 100ms TTFB you typically get from S3 without a proxy.
The documentation mentions it uses a write-back cache for metadata operations. That is likely how they are bypassing the synchronous S3 latency for directory listings.
This is interesting given the shift toward long-running agents that maintain state across sessions... does this mean we can finally stop relying on expensive persistent volumes for agent scratch space?
We have seen scratch space optimizations before that failed once the agent cluster scaled. How does Curvine handle cache coherence when multiple agents are writing to the same S3 prefix?