756 articles on cost optimization — what drives the cost, how it is priced, and where the savings actually are.
Amplify Hosting bills build minutes, stored artifacts, data served, and server-side rendering compute. For a static site it is cheap; SSR and heavy traffic are where cost grows. Here is the breakdown and where to cut.
Elastic Container Registry charges $0.10 per GB-month of image storage, trivial for most teams. The real cost is data transfer: cross-region and internet pulls add up, while pulls to ECS or EKS in the same region are free. Here is the full breakdown.
Route 53 bills $0.50 per hosted zone per month plus $0.40 per million standard queries, and alias queries to AWS resources are free. Latency and geo routing cost more per query, and health checks add up. Here is where the money goes.
KMS charges $1 per month per customer-managed key and $0.03 per 10,000 API requests. AWS-managed keys are free to hold but you still pay for requests. On a busy service, request volume, not key count, is the bill. Here is how to control it.
Gateway endpoints for S3 and DynamoDB are free and remove that traffic from your NAT gateway entirely. Interface endpoints cost per hour per AZ plus per GB, which can still beat NAT on high-volume paths. Here is how to choose.
CloudFront has no fixed fee, you pay for data transfer out to viewers (tiered by region and volume) and per-request charges. Transfer from AWS origins to CloudFront is free, which is why a CDN often lowers your total bill. Here is the breakdown.
Average latency hides the tail that users feel and SLOs measure. Optimizing cost against p95, not the mean, is what keeps a cheaper configuration from quietly breaking. Here is how to reason about the p95-versus-cost frontier.
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.
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.
AWS Config bills ~$0.003 per configuration item (recorded on every resource change) plus rule evaluations. The bill is churn × recording scope. Here's how to scope recording so Config stays cheap.
Commit when utilization clears the break-even (~60-70% for a 1-year term). Here's how to calculate it, when to ladder 1- vs 3-year, how to avoid stranding, and where Spot fits.
Encode cost rules, budget thresholds, per-PR deltas, required tags, banned SKUs, as machine-enforced policies in CI against a cost estimate. Here's the policy set worth having and how to roll it out.
Compute and storage have converged, but data transfer hasn't. Here's the shared structure (ingress free, egress tiered, cross-region charged), where AWS/Azure/GCP diverge, and the universal levers to cut it.
Compute Savings Plans give ~66% off across families and Fargate/Lambda; EC2 Instance Savings Plans give ~72% locked to one family/region. Here's which to pick and how they differ from Reserved Instances.
Azure egress is free for the first 100 GB/month, then tiered ~$0.087/GB; ingress is free. Here's the egress map, the patterns that drive the bill, and how a CDN and region co-location cut it.
Bigtable bills nodes (~$474/month each, minimum one) + storage. The node floor makes it expensive below scale. Here's how to tune nodes, SSD vs HDD, and when a cheaper datastore wins.
Custom metrics are $0.30/metric/month, but each metric-name + dimension-value combination is a separate billable metric, so high cardinality explodes the bill. Here's how to control it.
Delete waste, right-size, commit the baseline, use Spot, tier storage, cut egress, then keep it down with a cost gate. A practical, impact-ordered checklist with links to the details for each step.
Startups need budget alerts, basic tagging, and cost in the PR, not a FinOps team. Here's the starter kit, when to buy commitments, the common traps, and why not to over-engineer it.
FSx has four file system types, each billing storage plus throughput. Here's what Lustre, Windows File Server, NetApp ONTAP, and OpenZFS cost, which to use, and how to avoid over-provisioning throughput.
Load Balancer (L4) is ~$25-40/month; Application Gateway (L7) starts ~$180/month plus capacity units. Here's what the gap buys, when you need L7, and how to avoid defaulting to the pricier option.
GCP load balancers bill forwarding rules (~$18/month each for the first five) plus data processed. Here's why sprawl drives the bill and how URL maps and a CDN cut it.