When your Go application loads the same data over and over, it can slow down. Caching stores that data in memory so future requests are faster. The samber/hot library gives you nine different ways to decide which data stays and which gets removed.
You can pick an eviction algorithm like LRU, LFU, or W-TinyLFU based on your access pattern. The library also supports TTL (time to live) so data expires automatically. It handles cache misses with a loader pattern that fetches missing keys only once. This reduces pressure on your backend systems.
For monitoring, Prometheus metrics are built in. Use this skill when your project loads the same medium-to-low cardinality resources at high frequency. It helps lower latency and improve performance.
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