cost optimization
798 articles on cost optimization — what drives the cost, how it is priced, and where the savings actually are.
Azure VM Scale Sets cost: you pay for the VMs, autoscaling sets how many
Scale Sets add no charge of their own; you pay for the underlying VMs, disks, and load balancer. Autoscaling rules, instance size, and Spot instances decide the bill. Here is how to tune them for cost without hurting performance.
GCP Cloud Run jobs cost: pay for the work, nothing when idle
Cloud Run jobs bill per vCPU-second and memory-GiB-second while the job runs, with no idle cost since jobs run to completion and stop. It suits batch and scheduled work. Here is how the model works and how it differs from Cloud Run services.
GCP Filestore cost: you pay for provisioned capacity by tier
Filestore bills per GB-month of provisioned capacity by tier (Basic HDD, Basic SSD, Zonal, Enterprise), with tier minimums. You pay for the capacity you allocate, not what you use, so tier and size choice drive the bill. Here is how to pick.
GCP Cloud DNS cost: per managed zone plus per query
Cloud DNS bills about $0.20 per managed zone per month plus about $0.40 per million queries, similar to Route 53. For most domains it is a few dollars. Here is the breakdown and where cost hides for high-query or many-zone setups.
GPU instance cost optimization: the most expensive hour to waste
GPU instances cost many times a CPU instance per hour, so idle GPUs, oversized accelerators, and full-price on-demand are expensive mistakes. Spot, right-sizing, and sharing are the big levers. Here is how to keep GPU cost under control.
Cloud cost anomaly detection: catching spend spikes early
Cost anomaly detection flags unexpected spend increases, a misconfigured resource, a runaway job, a leak, before they become large bills. Automated detection plus fast response is the FinOps safety net. Here is how it works.
Cloud unit economics: cost per unit of business value
Unit economics ties cloud cost to business metrics, cost per customer, per transaction, per request, so you measure efficiency, not just total spend. Rising total cost can be healthy if unit cost falls. Here is how to think in units.
Cloud cost per customer: the metric behind gross margin
Cost per customer, cloud spend divided by customers served, drives gross margin in any cloud-hosted product. Knowing it, and reducing it as you scale, is essential to healthy unit economics. Here is how to measure and improve it.
Engineering cost awareness: making cost a first-class concern
The biggest FinOps lever is engineers who see and consider the cost of what they build. Giving developers cost visibility at design and PR time, and making cost a normal engineering concern, prevents waste at the source. Here is how.
Cloud waste elimination: finding and cutting what you do not use
A large share of cloud spend is waste, idle resources, over-provisioned capacity, orphaned volumes, forgotten environments. Systematically finding and eliminating it is the fastest cost win. Here is a complete waste-hunting playbook.
Cloud cost KPIs: the metrics that keep spend accountable
The right cloud cost KPIs, unit cost, coverage and utilization of commitments, waste percentage, forecast accuracy, turn cost from a monthly surprise into a managed metric. Here are the KPIs that matter and how to use them.
Cloud cost allocation with tags: knowing who spends what
Cost allocation tags attribute cloud spend to teams, projects, environments, and customers, making cost accountable and enabling showback, unit economics, and optimization. A consistent tagging strategy is the foundation of FinOps. Here is how to build one.
FinOps team structure: who owns cloud cost
FinOps works as a collaboration between engineering, finance, and a central FinOps function, not a single cost-cutting team. Clear roles, shared ownership, and a central enabling team make cost a managed discipline. Here is how to structure it.
Cost optimization ROI: knowing which savings are worth pursuing
Not every optimization is worth the effort. Weighing the savings against the engineering time and risk, ROI, focuses effort on the high-value wins and avoids over-optimizing trivial costs. Here is how to prioritize.
CDN cache hit ratio: the number that drives your CDN bill
A CDN's cost hinges on cache hit ratio: cache hits serve from the edge cheaply, while misses hit your origin, incurring origin egress and compute. Raising the hit ratio cuts both CDN and origin cost. Here is how.
Edge computing cost: running logic close to users
Edge compute (Cloudflare Workers, Lambda@Edge, and others) runs code at CDN edge locations, priced by requests and compute time, often cheaply. It cuts origin load and latency but has constraints. Here is the cost model.
DNS cost compared: Route 53 vs Azure DNS vs Cloud DNS
Managed DNS (Route 53, Azure DNS, Cloud DNS) prices by hosted zones plus queries, all inexpensive, with health checks and traffic policies adding cost. The cheapest is usually the one native to your cloud. This compares them.
NAT gateway cost optimization: a sneaky networking bill
NAT gateways bill an hourly fee plus per-GB data processing, so high-traffic private subnets accessing the internet or AWS services rack up processing charges. VPC endpoints, consolidation, and architecture cut it. Here is how.
PrivateLink cost: private connectivity to services
PrivateLink (and Private Endpoints) provide private connectivity to services without traversing the internet, billing per endpoint-hour plus data processed. It improves security and can reduce egress, but endpoints add up. Here is the model.
Service mesh cost: the price of sidecars and control plane
A service mesh (Istio, Linkerd, and others) adds a control plane plus per-pod sidecar proxies that consume CPU and memory, so the cost is that overhead across your fleet. Lightweight meshes and sidecar-less modes cut it. Here is the model.
Cross-cloud networking cost: the price of multi-cloud connectivity
Connecting workloads across clouds means egress on both sides plus interconnect or VPN cost, so data moving between clouds is billed twice and adds latency. Minimizing cross-cloud data movement is the main lever. Here is how.
Bandwidth cost optimization: paying less to move data
Bandwidth (data transfer) cost spans egress, cross-region, cross-AZ, and CDN transfer, and it hides across many services. Compression, caching, CDNs, in-region traffic, and committed transfer pricing cut it. Here is a complete playbook.
VPC cost optimization: the networking pieces that bill
A VPC itself is free, but its components, NAT gateways, VPC endpoints, data transfer, and traffic mirroring, carry cost. Knowing which pieces bill, and optimizing them, keeps VPC networking cheap. Here is the breakdown.
Network topology cost: how architecture shapes the bill
Network topology, hub-and-spoke, mesh, flat, or segmented, determines data transfer paths and connectivity cost. A well-designed topology keeps traffic cheap and manageable; a poor one multiplies transfer and complexity. Here is how to design for cost.