7 concepts you need to master cache.

Cache Hit Ratios

This is the answer to how effective your cache strategy is. A high hit ratio indicates that the cache frequently contains the requested data.

A high hit ratio minimizes fetching it from slower layers.

Eviction Policies

They determine which data stays in the cache and which gets removed; it's about efficiency.

Common policies include:

Cache Coherence

Of course, it gets more complex In distributed systems.

Maintaining data consistency across these caches is critical.

Cache coherence ensures that all copies of a data item reflect the most recent version.

Cache Granularity

This is about the size of the data units stored in the cache.

Granularity decisions impact the cache's efficiency and hit ratio.

How much data do you need to store in each operation?

Cache Warm-up

Preloading the cache with data expected to be in high demand will improve performance.

Especially in systems where cache hits are critical for speed.

Cache Partitioning

In a well-organized toolbox, you'd have separate compartments or trays for different tools.

Cache partitioning is the same. It's about dividing the cache into different sections, each tailored for a specific data type or request.

This organization improves the cache since retrieving the data is easier and faster.

Cache Compression

When space is at a premium, compressing cached data allows you to store more information.

But, this comes with the trade-off of processing overhead during compression and decompression.

Caching isn't just dumping data somewhere and forgetting about it.

It's also about what, how, and when you store data to make your system faster.