Cachey: High-Performance Read-Through Cache for Object Storage
By
pranay01
If you only eat one bagel today, this is the bagel.
Summary
Cachey is a high-performance read-through cache system designed for object storage, specifically for S3-compatible storage systems. It handles HTTP range requests with 16 MiB page-aligned ranges and provides standard HTTP response semantics including 206 Partial Content and 404 Not Found. The system supports configurable headers for bucket specification and S3 request configuration overrides on cache misses.
Key quotes
· 4 pulledHigh-performance read-through cache for object storage
The service maps requests to 16 MiB page-aligned ranges and the response has standard HTTP semantics
C0-Config overrides: Space-separated key-value pairs to override S3 request configuration per page miss
Range: yes - Byte range in format bytes={first}-{last}
You might also wanna read
Why Average LLM Use Is Likely Destroying Value in Software Development
The author argues that, contrary to prevailing hype, the average use of Large Language Models (LLMs) is likely destroying value rather than
How AI Accelerated Prototyping: From Idea to Tangible in Record Time
The author reflects on how AI has transformed their prototyping workflow. Previously, the biggest bottleneck was the time needed to scaffold
GitLab 19.0 launches with Secrets Manager, agentic workflows, and self-hosted AI models
GitLab 19.0 has been released, positioning itself as an intelligent orchestration platform for DevSecOps. The release includes expanded secr
bit.ly·21h agoCentralizing Error Handling in Rust with Custom AppError Enums
This article discusses the importance of centralizing error handling in Rust applications using a custom AppError enum combined with map_err
Zig Devlog: Build System Rework Separates Maker and Configurer Processes
This devlog entry from the Zig programming language project announces a major rework of the build system, separating the maker process from
Study finds most developers refuse to code without AI, raising quality concerns
A February 2026 study by AI research lab METR reveals that most developers now refuse to work without AI coding tools. While these tools hel
