Cloud Cost Optimization Tools 2026: Cut Your AWS, GCP & Azure Bills

Cloud bills don’t grow slowly. They erupt. An unnoticed autoscaler, a forgotten staging environment left running over a holiday weekend, a developer who pulled a production-sized database snapshot into dev—and suddenly the AWS invoice is three times what finance budgeted. According to Flexera’s 2025 State of the Cloud Report, organizations estimate they waste roughly 30% of their cloud spend, yet most teams still rely on spreadsheets and occasional billing dashboard check-ins to manage costs.

The FinOps tooling ecosystem has matured dramatically. In 2026, there are purpose-built tools for every layer of the problem: Terraform cost estimation before resources are provisioned, Kubernetes pod-level cost allocation, automated Spot instance orchestration, and AI-driven rightsizing. The hard part is no longer “can we see the costs?"—it’s choosing the right tool for your team’s scale, cloud provider mix, and technical maturity.

This guide covers eight of the most effective cloud cost optimization tools available in 2026, with honest pros/cons, pricing context, and a recommendation matrix to help you pick without second-guessing.

If you’re building the broader platform that generates these costs, see our guides on CI/CD pipeline tools and container registry platforms for where costs are first created.

TL;DR — Cloud Cost Tool Comparison 2026

1. AWS Cost Explorer — The Baseline Everyone Has

What it does: AWS Cost Explorer is the built-in cost analytics tool inside every AWS account. It provides time-series cost and usage graphs, breakdowns by service/tag/account, 12-month historical data, and a rightsizing recommendation engine for EC2 and RDS instances.

Why it matters: It’s already available—zero setup. The rightsizing recommendations alone can surface 10–20% savings opportunities in accounts that have been running for six months or more.

Pros:

• Zero-cost to access the console UI; API calls are $0.01 per request (as of early 2026)
• Native integration with AWS Organizations for multi-account consolidated billing
• Savings Plans and Reserved Instance coverage reports built in
• Rightsizing recommendations backed by 14 days of CloudWatch metrics

Cons:

• AWS-only; useless for multi-cloud shops
• Tag-based allocation requires disciplined tagging hygiene upfront
• Rightsizing recommendations are conservative—they won’t catch over-provisioned containers
• No CI/CD integration; there’s no “stop this before it deploys” capability

Pricing (as of early 2026): Free UI access. API access billed per request. The Compute Optimizer service, which gives deeper rightsizing data, is free for EC2 and adds a charge for enhanced infrastructure metrics via CloudWatch.

Best for: Any AWS customer as a starting point. Combine it with a purpose-built tool once you need container-level visibility or proactive controls.

2. Infracost — “FinOps Left” for Terraform

What it does: Infracost adds cloud cost estimates directly into your pull requests. When a developer changes a Terraform file—bumping an RDS instance class, adding a new ECS service—Infracost computes the monthly cost delta and posts it as a PR comment before anyone clicks “Apply.”

This “shift FinOps left” approach is fundamentally different from retroactive billing analysis. Instead of asking “why is this month $50K over?”, you stop the expensive change before it reaches production.

Pros:

• Open-source CLI with a permissive Apache 2.0 license; installable in any CI/CD pipeline
• Supports AWS, GCP, and Azure resource types across Terraform and Terragrunt
• Infracost Cloud SaaS layer adds policy enforcement (via OPA/Conftest), team cost dashboards, and alerts when a PR would breach a cost threshold
• Integrates with GitHub Actions, GitLab CI, Atlantis, and Azure DevOps in under 30 minutes
• Can enforce tagging standards as part of the cost policy check

Cons:

• Only covers infrastructure-as-code resources—won’t catch cost waste in already-deployed resources
• Kubernetes workload costs are estimated from node costs, not pod-level allocation
• SaaS pricing for Infracost Cloud is per-seat and can add up for large engineering teams
• Accuracy depends on how completely your Terraform describes resources; modules with dynamic provisioning are harder to estimate

Pricing (as of early 2026): The CLI is free and open source. Infracost Cloud (the SaaS dashboard, team features, policy guardrails) is a paid product—check infracost.io/pricing for current per-seat rates, as they update frequently.

Best for: Platform teams who manage Terraform and want to prevent expensive infrastructure mistakes from reaching production. Pairs well with a CI/CD pipeline investment.

3. OpenCost — CNCF’s Open Standard for Kubernetes Cost

What it does: OpenCost is a CNCF sandbox project that provides real-time Kubernetes cost allocation at the namespace, deployment, label, and pod level. It runs as a Prometheus metrics exporter and can be queried via a simple REST API or UI.

OpenCost acts as the open-source cost data foundation that commercial tools (like Kubecost) are built on. If you want K8s cost visibility without commercial lock-in, this is your starting point.

Pros:

• Completely free and open source (Apache 2.0)
• Native Prometheus integration means cost data flows into your existing observability stack
• Multi-cloud cost pricing integration (uses billing APIs for AWS, GCP, Azure spot and on-demand rates)
• CNCF governance means no vendor lock-in; you own your cost data

Cons:

• Basic UI—functional but not polished for business stakeholders
• No built-in multi-cluster federation in the base project
• Optimization recommendations are minimal; it’s visibility, not action
• Requires Prometheus expertise to get full value; not a “click and go” solution

Pricing: Free. You pay only for the compute resources running OpenCost itself (minimal).

Best for: Kubernetes-heavy teams with existing Prometheus/Grafana stacks who want cost metrics without SaaS costs. Also ideal as a data source if you’re building internal FinOps dashboards. Works alongside the container runtimes your clusters are already running.

4. Kubecost — The K8s Cost Platform

What it does: Kubecost extends OpenCost’s foundation with a polished UI, multi-cluster support, budget alerts, cost allocation by team/environment/product, and actionable rightsizing recommendations. IBM acquired Kubecost and now offers it as part of the Apptio product family.

Pros:

• Free Community edition supports one cluster with 15 days of data retention
• Granular pod-level cost allocation broken down by CPU, memory, GPU, network, and storage
• Cost efficiency scoring helps prioritize which workloads to rightsize first
• Native integration with AWS Cost and Usage Reports for accurate on-demand vs. Savings Plan blended rates
• Budget alerts via Slack, PagerDuty, or webhook
• Supports GCP Marketplace billing integration for accurate GKE costs

Cons:

• The free tier is limited to a single cluster with short data retention—inadequate for most production setups
• Enterprise licensing through IBM/Apptio can be expensive; pricing is not public
• UI can feel slow with very large clusters (hundreds of nodes)
• The IBM acquisition has raised long-term roadmap questions for some users

Pricing (as of early 2026): Community edition is free (1 cluster, 15-day retention). Kubecost Enterprise is priced per cluster and quoted through IBM/Apptio sales.

Best for: Teams running multiple Kubernetes clusters who need charge-back reports for engineering teams and budget governance—without building dashboards from scratch. See our Kubernetes monitoring guide for the complementary observability layer.

5. CAST AI — Automated Kubernetes Rightsizing

What it does: CAST AI goes beyond visibility into autonomous action. It connects to your EKS, GKE, or AKS cluster and continuously rightsizes node types, switches between on-demand and Spot instances, and packs pods more efficiently—all without manual intervention.

The key differentiator: CAST AI doesn’t just show you where to save; it makes the saves automatically (with configurable safety boundaries).

Pros:

• Automated instance type selection across 200+ AWS instance families, not just “recommend a smaller size”
• Spot instance management with automatic fallback to on-demand when Spot capacity is unavailable
• Bin-packing optimization reduces node count while maintaining headroom for burst
• Rebalancing respects pod disruption budgets and gradual rollouts
• Free “monitoring mode” lets you see projected savings before enabling automation

Cons:

• Requires read-write access to your cluster and cloud account—a meaningful trust boundary for security-sensitive teams
• Automation can occasionally conflict with cluster-level autoscalers if not configured carefully
• Savings claims (up to 40–60% cited by users) vary significantly based on current over-provisioning baseline
• Primarily K8s-focused; won’t help with non-containerized workloads

Pricing (as of early 2026): Usage-based pricing tied to compute savings generated or compute consumed. See cast.ai/pricing for current rates—the model has evolved from pure percentage-of-savings to tiered compute-based billing.

Best for: Platform teams running large EKS/GKE/AKS clusters who are comfortable granting automated optimization access and want hands-off rightsizing at scale.

6. Spot by NetApp (formerly Spot.io) — Spot Instance Automation at Scale

What it does: Spot by NetApp manages your entire compute fleet to maximize Spot and preemptible instance usage across EC2, GCE, and Azure. Its core product, Elastigroup, treats a pool of different instance types as fungible—when one is reclaimed, another takes its place automatically within seconds.

Pros:

• Sophisticated Spot interruption prediction reduces workload disruptions compared to using Spot directly
• Supports both Kubernetes (Ocean product) and non-containerized workloads (Elastigroup)
• Multi-cloud scope: handles AWS, GCP, and Azure in a unified control plane
• Reserved Instance and Savings Plans management through the Eco product
• Proven at large scale; NetApp enterprise support backing

Cons:

• Pricing is not publicly listed; requires a sales conversation
• The product surface is large and complex—takes time to configure well
• Less community documentation than pure open-source alternatives
• The NetApp acquisition has introduced some organizational complexity

Pricing (as of early 2026): Custom enterprise pricing, typically structured as a percentage of cloud savings generated. Contact sales for current rates.

Best for: Mid-to-large organizations running significant non-Kubernetes compute workloads on AWS, or enterprises wanting a single vendor for Spot management across cloud providers.

7. CloudHealth by VMware (Now Broadcom) — Multi-Cloud Governance

What it does: CloudHealth is one of the original FinOps platforms, providing cost visibility, governance policies, and chargeback/showback reporting across AWS, GCP, and Azure. After Broadcom’s VMware acquisition, it’s now positioned as part of the enterprise infrastructure management suite.

Pros:

• Battle-tested multi-cloud cost management with deep AWS integration
• Perspective engine allows extremely flexible cost allocation hierarchies
• Policy-based governance with automated rightsizing recommendations
• Strong reporting for finance teams and executives
• Integrates with ITSM tools like ServiceNow

Cons:

• Enterprise-only pricing; no self-serve or free tier
• The Broadcom acquisition has created uncertainty for some customers about roadmap and support
• UI can feel dated compared to newer FinOps platforms
• Steeper learning curve for initial setup and perspective configuration

Pricing (as of early 2026): Enterprise pricing via Broadcom sales. Has historically been cloud spend percentage-based.

Best for: Large enterprises with complex multi-cloud environments, dedicated FinOps teams, and the need for executive-level chargeback reporting across business units.

8. ProsperOps — Automated AWS Commitment Management

What it does: ProsperOps automates AWS Reserved Instance and Savings Plans purchasing on your behalf. Instead of manually analyzing your usage patterns and guessing how many 1-year or 3-year commitments to buy, ProsperOps runs a continuous algorithm that manages your commitment portfolio to maximize coverage at minimal risk.

Pros:

• Fully automated—set it and forget it for commitment management
• Handles the complex tradeoffs between Convertible vs. Standard RIs, Compute vs. EC2 Savings Plans
• Transparent savings reporting with clear ROI metrics
• Percentage-of-savings model means you only pay when you save
• No access to your compute infrastructure required, only billing data

Cons:

• AWS-only; no multi-cloud support
• Only addresses commitment discounts, not rightsizing or waste elimination
• Best suited for stable, predictable workloads; less effective for very spiky or new workloads

Pricing (as of early 2026): Percentage of savings generated (typically in the 10–15% range; check prosperops.com for current rates). No savings = no fee.

Best for: AWS-heavy organizations spending $50K+/month on compute, where Savings Plans management is complex enough to justify automation. Pairs excellently with a rightsizing tool like CAST AI or AWS Compute Optimizer.

Quick-Win Tips: Immediate Cloud Cost Reductions

Before buying any tool, these changes can save money this week:

1. Delete idle resources immediately. Run aws ec2 describe-instances --query "Reservations[*].Instances[*].[InstanceId,State.Name,Tags]" and filter for stopped instances older than 30 days. Volumes attached to stopped instances still bill.

2. Set lifecycle policies on S3 buckets. Most teams have multi-terabyte S3 buckets with no lifecycle rules. Transitioning objects older than 90 days to S3-Intelligent-Tiering or Glacier cuts storage costs by 60–80%.

3. Enable VPC Flow Logs selectively. Flow logs sent to CloudWatch Logs generate significant ingest and storage costs. Route to S3 instead, or enable only on subnets you’re actively troubleshooting.

4. Right-size the obvious outliers first. AWS Compute Optimizer (free) flags instances using less than 40% of their allocated CPU. Start there before any paid tooling.

5. Tag everything before anything else. None of the tools above deliver meaningful team-level allocation without consistent resource tags. Define a tagging standard (team:, env:, service:) and enforce it in Terraform (Infracost can check this in PRs).

6. Kill NAT Gateway data processing waste. NAT Gateway charges per GB processed. Workloads pulling data from S3 should use VPC endpoints instead—free within the same region.

7. Review CloudWatch Metrics and Logs retention. Default log groups retain logs forever. Set a 30-day retention policy on non-compliance-sensitive log groups.

Recommendation by Company Size

Startups (< $10K/month cloud spend)

Start with AWS Cost Explorer (free) and Infracost (free CLI). Get tagging right from day one. Don’t buy enterprise FinOps tooling yet—the ROI isn’t there, and the organizational discipline to act on recommendations matters more than the tool.

Growing Teams ($10K–$100K/month)

Add Kubecost Community (free) if you’re running Kubernetes. Consider ProsperOps or manual Savings Plans once your EC2/Fargate spend is predictable. CAST AI in monitoring mode (free) is a zero-risk way to see your K8s savings opportunity before committing.

Scale-ups ($100K–$500K/month)

This is where CAST AI or Spot by NetApp Ocean delivers serious ROI. Kubecost Enterprise or Infracost Cloud with policy guardrails prevents expensive mistakes from reaching production. Budget alerting and team-level chargeback become essential for accountability.

Enterprise ($500K+/month, multi-cloud)

CloudHealth or a dedicated FinOps platform handles the governance and executive reporting layer. Layer in CAST AI or Spot by NetApp for automated optimization. A dedicated FinOps team—not just tools—is the real multiplier at this scale.

Further Reading

For engineers building the infrastructure these tools monitor, pair this guide with:

• Best Kubernetes Monitoring Tools 2026 — observability alongside cost visibility
• Best CI/CD Pipeline Tools 2026 — where Infracost plugs in
• Best Container Registry Platforms 2026 — don’t forget registry egress costs
• Best Observability Platforms 2026 — metrics, logs, and traces inform rightsizing decisions

For engineers who want to go deeper on cloud architecture fundamentals, Cloud FinOps: Collaborative, Real-Time Cloud Financial Management by J.R. Storment and Mike Fuller is the definitive practitioner book, and The Cloud Architecture Patterns is useful for understanding the design decisions that drive cost.

Frequently Asked Questions

What is the best cloud cost optimization tool in 2026?

There is no single winner—the right tool depends on your cloud provider mix, technical stack, and team size. For AWS-only Kubernetes teams, CAST AI + Kubecost covers automated savings and visibility. For multi-cloud enterprises, CloudHealth handles governance. For IaC-first teams, Infracost prevents mistakes before they deploy. Most mature FinOps programs use 2–3 complementary tools.

What is FinOps and why does it matter for DevOps teams?

FinOps brings financial accountability to variable cloud spending. Unlike traditional IT capex, cloud costs scale directly with engineering decisions. FinOps bridges engineering, finance, and product teams so cost is a first-class engineering metric—not a surprise invoice.

How much can I realistically save with cloud cost optimization?

Savings depend on current waste levels. Organizations doing optimization for the first time commonly find 20–35% in immediate savings. CAST AI reports customers achieving 40–60% Kubernetes cost reductions through automated rightsizing and Spot orchestration.

What is the difference between Kubecost and OpenCost?

OpenCost is the open-source CNCF project—the data collection engine, free and vendor-neutral. Kubecost is built on top of OpenCost and adds a polished UI, multi-cluster aggregation, budget alerts, and chargeback reports. Think of OpenCost as the engine; Kubecost is the full vehicle.

Is Infracost really free?

The CLI is fully open source (Apache 2.0) and free to run in any CI/CD pipeline. Infracost Cloud (the paid SaaS layer) adds policy guardrails, team dashboards, and cross-team visibility for larger organizations.

How do I get started with no tooling today?

Three free steps: (1) Enable AWS Cost Explorer and identify your top-5 cost drivers. (2) Install Infracost CLI in your Terraform CI pipeline (20 minutes). (3) Run AWS Compute Optimizer (free) for rightsizing recommendations. These cost nothing and typically surface 10–20% savings in the first week.