DKDamir Karimovinblog.damir-karimov.com·May 19 · 17 min readWhy Good Abstractions Make Debugging Harder in Real-World SystemsGood abstractions help when they reduce the search space and make ownership clear. They make debugging harder when they duplicate state, hide propagation rules, and let several layers stay locally cor10
SMsourabh malviyainsourabhmalviya.hashnode.dev·Mar 31 · 5 min readCache Strategies in distributed systemCaching helps us to serve millions of request but it come with another challenge in our application that is when is right time to remove the data from cache memory? Traffic spike in not constant in ou00
SKshubham kumarinsystem-design-diaries.hashnode.dev·Mar 24 · 5 min readCache Strategies in Distributed SystemsLet’s start with something simple. 🧠 What is Cache? Imagine a cafe ☕ Some coffees are ordered again and again. Instead of preparing them every time (which takes time), the cafe keeps them ready. 👉 W00
RSRakesh Sadhukhaninmerakesh99.hashnode.dev·Mar 22 · 6 min readCache Strategies in Distributed SystemsIntroduction: When caching becomes the bottleneck Caching is usually introduced as a performance optimization. Add Redis, reduce database load, improve latency ~ done. Until one day it stops working. 00
MSManuela Schrittwieserinneuralstackms.tech·Mar 16 · 5 min readCaching & Performance: Building Fast, Predictable Systems in 2026Modern applications live or die by their performance profile. Users expect instant responses, distributed systems introduce unavoidable latency, and cloud costs rise quickly when services scale ineffi10
BSBisworanjan Senapatiinbiswo98.hashnode.dev·Mar 7 · 7 min read Cache & Caching StrategiesModern applications like streaming platforms, e-commerce sites, and social media handle millions of requests per second. If every request directly hits the database, the system quickly becomes slow an00
AKAnuvrat Kumar Singhinanuvratsingh-dev-test.hashnode.dev·Mar 7 · 9 min readCache Strategies in Distributed Systems: Preventing Cache Stampedes and Traffic SpikesIn the previous article we talked about the Thundering Herd Problem — when thousands of requests hit the database at the same time. Caching usually solves this problem. But surprisingly, caching itsel00
ABAniket Binaniketumbcdev.hashnode.dev·Mar 7 · 4 min readCache Strategies in Distributed Systems 🤔 Why Are These Strategies Even Needed? The Core Problem Your system has a cache (like Redis). It stores expensive data — DB query results, ML model outputs, user dashboards. Every cache entry has a 00
BSBisworanjan Senapatiinbiswo98.hashnode.dev·Mar 6 · 5 min readThe Thundering Herd - ProblemModern distributed systems are designed to scale — until suddenly they don’t.One moment everything works perfectly.The next moment, thousands of requests hit your system simultaneously, overwhelming s00
JSjaydip sataniinjaydipsatani.hashnode.dev·Mar 5 · 5 min readCache Strategies in Distributed SystemsCache Strategies in Distributed Systems: How Big Systems Avoid Traffic Spikes One of the most critical methods of ensuring fastness and scalability of systems is caching. Rather than making continuous00
