29 articles on cost vs performance — what drives the cost, how it is priced, and where the savings actually are.
Every cache hit is a database query, a Lambda invocation, or an origin fetch you did not pay for. Caching is one of the few levers that cuts cost and improves latency at once. Here is where to add it and how the math works.
Requests, not usage, decide how many nodes you pay for, the scheduler packs pods by requests. Set them too high and you buy idle nodes; too low and you risk throttling and OOM kills. Here is how to size them for cost and stability.
Rightsizing on cost alone can push tail latency past your SLO. Simulating cost and p95 response time together finds the configuration that's cheap enough and fast enough, before anything is provisioned. Here's how to reason about the tradeoff.
Naive rightsizing trims CPU and memory until latency spikes and you roll it back. The safe method holds a performance budget (p95, error rate, headroom) while cutting cost. Here's the method and the traps.
Autoscaling trades spend for headroom. Target utilization, min/max, and cooldowns decide whether you overpay for idle capacity or miss your latency target under load. Here's how each knob moves cost and p95.