Navigating Node.js Caching: Lessons LearnedAdam C. |
In my journey to optimize website performance, I explored the realm of caching in Node.js. Initially, I relied on Axios for API calls without caching, which resulted in redundant calls upon revisits to pages. To address this, I leveraged the Axios Cache Interceptor, a Node.js module designed for efficient API caching.
At first glance, the Axios Cache Interceptor seemed like a game-changer. However, over time, I noticed intermittent slowdowns, especially after extended periods of application usage. This led me to investigate further, uncovering a memory leak issue associated with the Axios cache.
The cache, set with a 5-minute Time-To-Live (TTL), failed to clear efficiently, resulting in increased memory consumption and occasional performance hiccups. Despite my website's modest traffic, the cache's impact on memory usage was significant enough to affect overall performance.
After disabling the Axios Cache Interceptor, I observed a remarkable improvement in performance consistency, with ample memory allocation consistently available (65+MB). This experience taught me a valuable lesson about the nuances of caching – it's not a one-size-fits-all solution.
For dynamic websites generating a plethora of unique pages, caching can inadvertently consume excessive memory and impede performance. While caching benefits repeat page visits within sessions, in my case, lightweight queries and optimized memory usage proved to be more effective for maintaining smooth application performance.
In conclusion, my foray into caching in Node.js taught me the importance of striking a balance between performance optimization techniques and resource management. Sometimes, solving one problem may uncover unexpected challenges, but each experience contributes to a deeper understanding of system optimization strategies.