golang-samber-hot

To implement an in-memory cache in Go with custom eviction, use a framework supporting algorithms like TinyLFU, ARC, and FIFO. This allows you to tailor cache performance to specific workload patterns and optimize memory usage.

The best way to handle high concurrency in a Golang cache is by using sharding. Sharding divides the cache into independent segments, reducing lock contention and ensuring high throughput for concurrent read and write operations.

A loader chain in a Go caching framework sequentially attempts to fetch missing data from multiple sources. It populates the cache automatically during cache misses, preventing thundering herd problems and streamlining data retrieval.

Yes, you can use TTL and background cleanup for a Go in-memory cache. Setting a TTL ensures data expires after a duration, while a Janitor process handles background eviction to maintain memory limits without manual intervention.

You need an advanced cache eviction algorithm like W-TinyLFU when dealing with scan pollution or skewed access patterns. It tracks frequency to retain hot items, improving cache hit rates significantly compared to basic LRU.

Yes, this Go caching framework supports collecting performance metrics. Built-in metrics monitoring tracks cache hits, misses, and evictions, enabling you to analyze production behavior and optimize throughput and latency.