Measuring Cache Effectiveness
Learn the key metrics that reveal whether a cache is actually helping: hit ratio, miss penalty, latency improvement, and how to interpret them to tune cache size and TTL.
Why Measure a Cache?
A cache only helps if it serves enough requests to beat its cost. Without measurement, you cannot tell a useful cache from wasted memory.
Hits and Misses
A hit is served from the cache; a miss requires fetching from the slow source. Counting both is the foundation of every cache metric.
hits = 0
misses = 0
store = {'a': 1}
for key in ['a', 'b', 'a']:
if key in store:
hits += 1
else:
misses += 1
print('hits', hits, 'misses', misses)All lessons in this course
- Introduction to Caching
- Benefits of Caching
- Caching Levels & Hierarchy
- Measuring Cache Effectiveness