Performance monitoring tells you if your cloud is working. Cost monitoring tells you what it’s costing — and whether that cost makes business sense. Most organizations don’t discover their cloud spend problem until the CFO asks why the AWS bill tripled. By then, the waste is baked into infrastructure decisions that are hard to unwind. Here’s how to set up cost visibility before that conversation happens.
Why cloud cost monitoring is its own discipline
Cloud pricing is designed to be hard to predict: per-hour instances, per-GB storage, per-request APIs, per-million invocations, cross-region transfer fees, tiered volume discounts, reserved vs on-demand vs spot pricing. A performance monitoring tool (Datadog, New Relic) can show you how much infrastructure you’re running. A cost monitoring tool shows you what it costs, who’s spending it, and where it’s wasted.
The overlap with performance monitoring is real — you need utilization data to identify waste, and tools like Datadog now include cloud cost features. But dedicated cost tools go deeper on allocation, budgeting, anomaly detection and FinOps workflows.
The tools
Cloud-native (free or included)
AWS Cost Explorer — Free for all AWS accounts. Shows cost and usage by service, region, account and tag over the last 13 months. AWS Budgets adds threshold alerts. The starting point for any AWS shop, but limited to AWS and dependent on tagging discipline.
Azure Cost Management — Free for Azure customers. Similar capability to AWS Cost Explorer, with forecasting and budget alerts. Good for Azure-only; limited cross-cloud.
Google Cloud Billing — Built-in billing reports and budget alerts. BigQuery export enables custom analysis. The least polished of the three but functional for GCP-only.
Multi-cloud and FinOps platforms
CloudZero — Allocates cost to engineering dimensions (per customer, per feature, per team) without requiring tags. Strong on unit economics — showing cost-per-customer rather than just cost-per-service. Listed in our directory.
Finout — Multi-cloud cost allocation with Kubernetes support and MegaBill (virtual unified bill across providers). Strong on combining cloud and SaaS costs in one view. Listed in our directory.
Flexera One — Enterprise-grade cloud management platform covering cost optimization, governance and migration across AWS, Azure and GCP. Best for large enterprises with complex multi-cloud estates. Listed in our directory.
CloudHealth by VMware — A mature FinOps platform offering multi-cloud cost management, governance, and optimization recommendations. Enterprise-focused with strong policy and reporting features. Listed in our directory.
Kubernetes-specific
Kubecost / OpenCost — Allocates Kubernetes cluster costs to namespaces, deployments, pods and labels. Kubecost’s free tier covers a single cluster; OpenCost is the open-source CNCF project it contributed. Essential if container workloads are a significant portion of your bill.
The three quick wins
Before buying a tool, these actions recover 20–40% of typical cloud spend:
1. Kill idle resources
Unused EC2 instances, orphaned EBS volumes, unattached Elastic IPs, forgotten dev environments left running over weekends. AWS Trusted Advisor and Azure Advisor flag many of these for free. The typical enterprise wastes 25–35% of cloud spend on resources nobody uses.
2. Right-size over-provisioned instances
A t3.xlarge running at 5% CPU should be a t3.small. Utilization data from your infrastructure monitoring feeds directly into right-sizing decisions. AWS Compute Optimizer and third-party tools automate recommendations.
3. Commit to reserved capacity
For steady-state workloads, reserved instances (AWS), savings plans (AWS/Azure) and committed use discounts (GCP) cut per-hour cost 30–60% versus on-demand. The risk: committing to capacity you don’t use. Start with workloads that have been stable for 3+ months.
Unit economics: the metric that matters
Absolute cloud spend (“we spent $47k last month”) is less useful than unit cost:
- Cost per customer — are high-volume customers profitable or subsidized?
- Cost per transaction — is the payment-processing workload cost scaling linearly or superlinearly?
- Cost per environment — is staging costing 60% of production for 0% of revenue?
CloudZero is built around this concept; others can approximate it with good tagging. Either way, unit economics let engineering and finance have the same conversation — which is what FinOps is really about.
How cost monitoring connects to performance monitoring
The overlap:
- Utilization data from infrastructure monitoring drives right-sizing: you can’t identify a 5%-utilized instance without CPU metrics.
- Cost anomaly alerts complement performance anomaly alerts: a sudden cost spike often indicates a runaway process, a scaling event, or a misconfigured service — the same events performance monitoring catches from the other direction.
- Shared tagging — tags that organize resources for monitoring (team, service, environment) are the same tags cost tools need for allocation.
If you’re already running Datadog, its Cloud Cost Management module can surface cost alongside performance data. If you’re on a tighter budget, AWS Cost Explorer + your existing monitoring setup covers the basics.
Bottom line
Start with your cloud provider’s free tools (Cost Explorer, Azure Cost Management) and enforce consistent tagging from day one — retroactive tagging is painful. Add a dedicated cost platform (CloudZero, Finout, Kubecost) when multi-cloud, Kubernetes or FinOps workflow needs outgrow the native tools. The biggest savings come from the simplest actions: killing idle resources, right-sizing instances, and committing to reserved capacity for stable workloads.