We all know slow APIs suck. 😅
In a world where users expect instant responses, any delay is a red flag.
I ran into this issue recently—API latency creeping up, users complaining and me pulling my hair out.
But here’s how I turned it around with a neat trick: server-side caching.
The Problem: Repetitive Requests
We had a Java Spring backend feeding data to a React frontend.
Some of our endpoints, like fetching product details and user preferences, were constantly under load. Profiling showed over 60% of the requests were just repeating the same queries in short intervals.
Slow, repetitive database calls? No thanks.
The Solution: Redis FTW
I implemented Redis, an in-memory key-value store that’s perfect for caching frequently accessed data.
It was smooth to integrate and instantly improved performance.
The Results: 40% Faster APIs
After deploying the caching solution, we saw a 40% drop in latency.
Our database load decreased, and response times went from 800ms to under 500ms on key endpoints.
Key Takeaways:
Cache wisely: Don’t cache everything. Static data is your friend here, not dynamic, user-specific stuff.
Monitor everything: Caching isn’t a one-time fix. Watch your hit rates and cache evictions to stay on top of it.
Handle invalidation: You don’t want stale data in your cache. Use eviction strategies to keep your data fresh.
If you want to see the full breakdown, check out the full article on Medium! Read more here
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