[{"data":1,"prerenderedAt":79},["ShallowReactive",2],{"term-b\u002Fbin-packing":3,"related-b\u002Fbin-packing":60},{"id":4,"title":5,"acronym":6,"body":7,"category":40,"description":41,"difficulty":42,"extension":43,"letter":44,"meta":45,"navigation":46,"path":47,"related":48,"seo":54,"sitemap":55,"stem":58,"subcategory":6,"__hash__":59},"terms\u002Fterms\u002Fb\u002Fbin-packing.md","Bin Packing",null,{"type":8,"value":9,"toc":33},"minimark",[10,15,19,23,26,30],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 - The Vibe Check",[16,17,18],"p",{},"Bin packing is the scheduler's puzzle of cramming as many workloads as possible onto as few machines as possible without anything running out of memory or CPU. It's the same problem as fitting boxes of different sizes into moving trucks: pack badly and you need extra trucks sitting half-empty, pack well and you save real money. Kubernetes and cloud autoscalers are solving this puzzle constantly, in the background, every time a pod gets scheduled.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"Bin packing is the scheduling problem of placing workloads onto the minimum number of physical or virtual machines given their resource requirements, directly affecting infrastructure utilization and cost. Schedulers like the Kubernetes default scheduler and cluster autoscalers use bin-packing heuristics (such as best-fit or most-allocated) to consolidate pods onto fewer nodes, enabling underutilized nodes to be scaled down, as opposed to spreading strategies that prioritize availability over density.",[11,27,29],{"id":28},"when-youll-hear-this","When You'll Hear This",[16,31,32],{},"\"Switching the scheduler to a bin-packing strategy let us shut down four idle nodes.\" \u002F \"Bad bin packing left us paying for nodes running at 15 percent utilization.\"",{"title":34,"searchDepth":35,"depth":35,"links":36},"",2,[37,38,39],{"id":13,"depth":35,"text":14},{"id":21,"depth":35,"text":22},{"id":28,"depth":35,"text":29},"cloud","Bin packing is the scheduler's puzzle of cramming as many workloads as possible onto as few machines as possible without anything running out of memory or...","intermediate","md","b",{},true,"\u002Fterms\u002Fb\u002Fbin-packing",[49,50,51,52,53],"GPU Scheduling","Auto Scaling","Right-Sizing","Kubernetes","Load Balancer",{"title":5,"description":41},{"changefreq":56,"priority":57},"weekly",0.7,"terms\u002Fb\u002Fbin-packing","rGlx4uBMNJVEUTN9noW2j-8C849Bo2Ut0U8WJXvFVOY",[61,64,68,72,76],{"title":50,"path":62,"acronym":6,"category":40,"difficulty":42,"description":63},"\u002Fterms\u002Fa\u002Fauto-scaling","Auto scaling is when the cloud automatically adds more servers when traffic spikes and removes them when it drops, so you're not paying for idle machines a...",{"title":49,"path":65,"acronym":6,"category":40,"difficulty":66,"description":67},"\u002Fterms\u002Fg\u002Fgpu-scheduling","advanced","GPUs are expensive and scarce, so you can't just let every job grab one whenever it feels like it.",{"title":52,"path":69,"acronym":6,"category":70,"difficulty":66,"description":71},"\u002Fterms\u002Fk\u002Fkubernetes","cicd","Kubernetes is a robot manager for your containers.",{"title":53,"path":73,"acronym":6,"category":74,"difficulty":42,"description":75},"\u002Fterms\u002Fl\u002Fload-balancer","networking","A load balancer is like a traffic cop for servers.",{"title":51,"path":77,"acronym":6,"category":40,"difficulty":42,"description":78},"\u002Fterms\u002Fr\u002Fright-sizing","Right-sizing means matching your cloud resources to what you actually need. Running a t2.xlarge for a blog that gets 10 visitors a day?",1792528065360]