[{"data":1,"prerenderedAt":22},["ShallowReactive",2],{"tag-list-en-resilience":3},[4,15],{"title":5,"description":6,"tags":7,"path":12,"date":13,"img":14},"Load Balancing Algorithms: Each One Fixes the Last One's Flaw","Spreading requests across N servers sounds like a one-liner: pick a server, send the request. Then one backend is slower, or bigger, or holds a session, and the naive choice falls apart. This walks the classic algorithms as a chain where each one exists to fix the previous one's blind spot: round robin, weighted, least connections, power of two choices, and consistent hashing, in Go, ending with the failure every tutorial forgets.",[8,9,10,11],"Load-Balancing","Go","Distributed-Systems","Resilience","\u002Fbackend\u002Fload-balancing\u002Fload-balancing-algorithms","2026-07-20",null,{"title":16,"description":17,"tags":18,"path":20,"date":21,"img":14},"Retry Storms: How Good Clients Take Down Healthy Servers","A retry looks harmless: the request failed, so try again. Multiply that by every client, add one slow dependency, and retries turn into a self-inflicted DDoS. This walks from the naive retry loop to exponential backoff, jitter, retry budgets and circuit breakers, the caller-side half of resilience that pairs with rate limiting on the server.",[11,10,9,19],"Retries","\u002Fbackend\u002Fapi-design\u002Fretry-storms","2026-07-11",1786887556345]