AWS cost optimization tools: what each one does, free vs paid, and when you need a platform.
AWS gives you seven cost tools at no charge: Cost Explorer, Budgets, Compute Optimizer, Cost Anomaly Detection, Trusted Advisor, the Cost and Usage Report, and Cost Optimization Hub. Paid platforms earn their fee in three cases: multi-account or multi-cloud sprawl, deep Kubernetes cost work, and hands-off commitment management. Start with the free stack. And remember that every tool stops at a recommendation; someone still has to do the work.
- AWS gives you seven cost tools at no charge: Cost Explorer, Budgets, Compute Optimizer, Cost Anomaly Detection, Trusted Advisor (the full cost checks need a paid Support plan), the Cost and Usage Report, and Cost Optimization Hub. For a team on one or two accounts and a single cloud, that stack surfaces most of the savings. Start there before you pay anyone.
- Third-party platforms (Vantage, CloudHealth, Cloudability, Kubecost, ProsperOps and others) earn their fee in three situations: multi-account or multi-cloud sprawl that native reporting handles poorly, Kubernetes cost work beyond what AWS split cost allocation gives you, and hands-off management of your Savings Plans and RIs. Below those thresholds a paid platform is often pure cost.
- Tools find savings; they do not implement them. The gap between a recommendation and a lower invoice is engineering work. CloudRoute matches you with a vetted AWS partner who does that work, and CloudRoute is free for startups.
IThe AWS cost tooling landscape in one mental model
Every cost tool, native or third-party, does one of four jobs: see the spend, find the waste, act on the savings, or prevent the next surprise. Map a tool to its job and the buying decision gets simple: you only pay for the jobs the free tools do badly.
Visibility: where the money goes, by service, account, team, environment and time. Recommendation: where the waste is (idle resources, oversized instances, the wrong storage class, missing commitments). Action: actually changing something, such as buying a Savings Plan or resizing an instance. Governance: budgets, anomaly alerts, allocation tags and showback, so teams own the spend they create.
The native tools cover all four jobs to a baseline level. The paid market exists because the baseline has gaps: cross-account and multi-cloud reporting is awkward, Kubernetes allocation needs extra work, and native action is manual. AWS recommends a Savings Plan but never buys or rebalances one for you.
The most expensive mistake is buying for a gap you do not have. A six-engineer startup on one account does not need an enterprise FinOps platform. A 40-account company running Kubernetes on three clouds cannot run on native tools alone. Prices in this market move and are mostly negotiated, so confirm live rates before you commit.
IIThe seven AWS-native tools and what each does
Know what AWS already gives you before you evaluate a paid product. All seven are part of your account; the exceptions are noted.
Cost Explorer: visibility
Interactive charts of spend and usage by service, account, Region, instance type, tag and time, plus rightsizing and Savings Plans recommendations. By default it shows the previous 13 months; you can turn on up to 38 months of monthly history at no charge (AWS docs). AWS Cost Explorer forecasts spend up to 18 months ahead (monthly view). (AWS docs).
Cost: the console is free; the API is $0.01 per paginated request, and hourly or resource-level granularity is a paid option. Limit: it is a reporting tool, not an analytics warehouse. Complex questions are clumsy, which is what the CUR and third-party tools fix. See the Cost Explorer guide.
AWS Budgets: governance
Cost, usage, Savings Plans or RI utilization and coverage budgets, with alerts on actual or forecast spend. Budget Actions can apply an IAM or SCP policy or stop instances when a budget is breached.
Cost: per the AWS Budgets pricing page, monitoring and notifications are free; the first two action-enabled budgets are free each month, then $0.10 a day each. Limit: Budgets is a tripwire, not a diagnosis. Pair it with Anomaly Detection for the "why". See the Budgets guide.
Compute Optimizer: right-sizing
Uses CloudWatch metrics to recommend right-sized EC2 instances, Auto Scaling groups, EBS volumes, Lambda memory and ECS on Fargate tasks, including Graviton options, each with a projected price and performance change.
Cost: free; enhanced infrastructure metrics (a longer lookback of up to three months) cost a small per-resource fee and help with bursty workloads. Limit: it sees metrics, not intent. It will suggest downsizing a warm standby. A human still checks each recommendation.
Cost Anomaly Detection: catch the spike
Machine-learning monitors learn your normal spend per service, account, cost category or tag and alert on unusual jumps: a runaway NAT Gateway, a forgotten GPU instance, a misconfigured pipeline. Free.
Limit: it reacts after the anomaly starts and needs a few weeks of history to learn "normal". It is still the highest-return free tool to turn on first. See the Anomaly Detection guide.
Trusted Advisor: the breadth check
Checks across cost, security, performance, resilience and limits. The cost checks flag idle load balancers, underused EBS volumes, idle RDS instances, low-utilization EC2 and unattached Elastic IPs.
Cost: a limited free set; the full cost checks need a Business, Enterprise On-Ramp or Enterprise Support plan. Limit: breadth over depth. Good for a sweep, not a savings model.
Cost and Usage Report (CUR) and Data Exports: the raw truth
The most detailed billing data AWS produces: every line item, hourly or by resource, with every tag, delivered to S3. It powers Athena and QuickSight dashboards and almost every third-party platform. CUR 2.0 through Data Exports is the current format.
Cost: the report is free; you pay for S3 storage and for queries. Limit: it is raw. Turning it into answers takes SQL and BI work, which is exactly the labor paid platforms package.
Cost Optimization Hub: one ranked list
Collects and de-duplicates cost recommendations (rightsizing, idle deletion, Graviton, Savings Plans, RIs) across accounts and Regions, estimates the monthly saving of each, and ranks them. Free.
It closes the oldest gap in the native stack, where advice used to be scattered across four tools. It is the right native place to start "what do we do first".
Turn on, in this order: Cost Anomaly Detection, AWS Budgets (one cost budget and one Savings Plans coverage budget), Data Exports / CUR so the raw data starts piling up, then work Cost Optimization Hub top-down with Compute Optimizer for the sizing detail. Activate cost allocation tags early: every tool, native or paid, is only as good as your tags.
IIIThird-party platforms and the gap each one sells against
Every viable third-party tool exists because it does something native AWS does badly, not at all, or not automatically. Match a tool to a gap you actually have.
Pricing is mostly a share of the cloud spend managed or a platform fee, and it is usually negotiated. The test is simple: does the gap cost you more than the tool does?
Visibility and FinOps platforms: Vantage, CloudHealth, Cloudability, nOps, Finout
The gap: clean cross-account and multi-cloud reporting, virtual tagging to fix allocation gaps, and showback or chargeback that finance can read. These platforms ingest your CUR (and often Azure and GCP data) and package it.
When it pays off: several AWS accounts or real multi-cloud, many teams to hold accountable, and a finance team asking for chargeback. When it does not: one or two accounts on one cloud, where Cost Explorer plus a CUR dashboard does the job.
Kubernetes cost: AWS split cost allocation, Kubecost and OpenCost
What AWS now does: split cost allocation data for Amazon EKS puts pod-level cost and usage into the CUR, with namespace and deployment tags, and can import Kubernetes labels as cost allocation tags (AWS docs). Turn it on first if you run EKS.
What Kubecost and OpenCost add: live in-cluster dashboards, request and limit right-sizing, idle-capacity detection and multi-cluster views. OpenCost is the open-source CNCF project; Kubecost adds paid multi-cluster and governance features. Worth it when several teams share clusters and need day-to-day answers, not just a monthly CUR view.
Commitment and Spot automation: ProsperOps, Spot (now part of Flexera), Zesty
The gap: AWS recommends Savings Plans and RIs but never buys, blends or rebalances them. ProsperOps manages the commitment portfolio continuously (laddering terms, mixing Compute and EC2 Instance Savings Plans and RIs) and typically charges a share of the savings it produces.
Spot (sold by NetApp to Flexera in March 2025, per NetApp) and Zesty automate the compute side: running interruptible Spot capacity safely and optimizing commitments. They pay off when compute spend is large enough that a few extra points of savings beat the fee, and when your team would otherwise let commitments go stale.
Shift-left and open source: Infracost and the CUR dashboards
Infracost estimates the cost change of a Terraform change inside the pull request, so engineers see the delta before they merge. Prevention is the cheapest saving.
AWS publishes the Cloud Intelligence Dashboards (CUDOS) framework for free: CUR on Athena and QuickSight, giving platform-grade visibility for the cost of the BI work to stand it up.
IVWhen AWS-native is enough and when a platform pays off
The buying decision comes down to a few thresholds. Cross one and a paid tool can earn its fee; stay under all of them and the free stack is the answer.
- Stay native if you run one or two accounts on one cloud: Cost Explorer, Cost Optimization Hub, Compute Optimizer, Anomaly Detection and a Savings Plan capture most of the savings. A platform here mostly buys convenience.
- Consider a platform for multi-account sprawl or multi-cloud: With five or more linked accounts, several teams and a finance team asking for chargeback, native cross-account reporting gets painful. A visibility platform earns its fee in analyst hours and cleaner allocation.
- For shared Kubernetes clusters, start with AWS split cost allocation: Turn on split cost allocation data for EKS first. Add OpenCost or Kubecost when teams need live in-cluster views and request right-sizing.
- Consider commitment automation when compute spend is large: If a few extra points of effective savings rate beat the tool's cut, and your team would otherwise buy one Savings Plan and forget it, autonomous commitment management usually nets positive.
- Shift left regardless: Cost estimates in the pull request are cheap or free and catch the oversized Terraform module at review time.
- The real bottleneck is rarely the tool: Every tool ends at a recommendation. Savings land only when someone re-architects the NAT topology, migrates to Graviton, rewrites lifecycle policies and buys the right commitments.
VTools find the savings. Someone still has to do the work.
A dashboard that says "you could save 38%" is not savings. It is a backlog. On most teams that backlog never gets worked, because the people who could do it are shipping product.
Walk the chain. Cost Optimization Hub hands you a ranked list: right-size 14 instances, move 9 workloads to Graviton, buy a Compute Savings Plan, delete 240 unattached volumes, replace two NAT Gateways with gateway endpoints, tier 40 TB of S3. Every line is an engineering ticket with testing, rollout risk and an owner. Some of them (Graviton rebuilds, commitment laddering, data-transfer changes) need real expertise.
A vetted AWS partner can bring the tooling and do that rework, so the savings reach the invoice. CloudRoute matches you with one. CloudRoute is free for startups; partners pay CloudRoute a monthly membership plus 10% of AWS-approved funding.
Who pays for the partner's work. It is an engagement you agree with the partner before it starts, and the savings usually pay for it. AWS funding that only partners can file attaches to qualifying work, not to cost work on its own: MAP if you are moving more workloads onto AWS, POC if you are testing a new setup, or incremental workload (IW) funding if you are launching new work on AWS. For startups this is typically $50K to $150K. Depends on the workload; AWS approves.
VIBuyer's guide: the right stack for your situation
Match your profile to a row. Each is the right-sized stack a FinOps practitioner would stand up, not the maximal one.
| Your situation | Visibility | Recommendation | Commitments / Kubernetes | Worth paying for? |
|---|---|---|---|---|
| Seed startup, 1 account | Cost Explorer + Budgets | Cost Optimization Hub + Compute Optimizer | One Compute Savings Plan (DIY) | No: the free stack is plenty |
| Series A, 1 to 3 accounts | Cost Explorer + CUR dashboard | Cost Optimization Hub + Anomaly Detection | Savings Plan ladder (DIY or automated) | Maybe: a partner audit may beat a platform seat |
| Running EKS, shared clusters | Cost Explorer + EKS split cost allocation | Compute Optimizer + OpenCost or Kubecost | Spot for batch; requests right-sized | Often: for live in-cluster views |
| Multi-account, 5+ teams | Vantage, CloudHealth or Cloudability | Platform recommendations + Cost Optimization Hub | Autonomous commitment management | Yes: sprawl and chargeback justify it |
| Multi-cloud (AWS + Azure or GCP) | CloudHealth, Cloudability or Finout | Cross-cloud platform recommendations | Platform + commitment automation | Yes: native tools are single-cloud |
| Any size, nobody to do the rework | Whatever you have | Cost Optimization Hub | Partner plans it | A partner-led audit and rework |
VIIA first month that needs no new tools
You can bank the first wave of savings with the free stack in about a month, before spending anything on tooling.
Week 1, instrument. Turn on Cost Anomaly Detection, create a cost budget and a Savings Plans coverage budget, enable Data Exports to S3, and tag your top spend by team and environment.
Week 2, find the waste. Read Cost Optimization Hub's ranked list, check sizing detail in Compute Optimizer, and run a Trusted Advisor cost sweep for idle and unattached resources.
Week 3, bank the quick wins. Delete unattached volumes and old snapshots, release unused Elastic IPs, remove idle load balancers and instances, move gp2 to gp3, and turn on S3 Intelligent-Tiering where access is unpredictable.
Week 4, the structural levers. Buy a one-year Compute Savings Plan sized to your steady baseline, plan the Graviton moves Compute Optimizer flagged, and scope data-transfer fixes such as gateway endpoints in place of NAT data processing.
Then decide. You will know what the free stack got you and how much structural work is left that you do not have time for. That is when a partner-led engagement makes sense.
AWS-native tools vs third-party platforms, head to head
The core buying question in one table. Native tools cost nothing to use and cover the fundamentals; third-party platforms cost money and earn it on scale, multi-cloud, Kubernetes depth and automation.
| Capability | AWS-native | Third-party platform |
|---|---|---|
| Single-account visibility | Cost Explorer: strong, free | Cleaner UI; small gain at small scale |
| Multi-account and multi-cloud | Awkward across accounts; AWS only | Core strength of visibility platforms |
| Right-sizing recommendations | Compute Optimizer and Cost Optimization Hub, free | Similar engines, packaged with workflow |
| Kubernetes cost allocation | EKS split cost allocation in the CUR | Kubecost or OpenCost: live in-cluster views and request right-sizing |
| Anomaly detection | Cost Anomaly Detection, free | Comparable, often with richer alerting |
| Commitment automation | Recommends only; never buys or rebalances | ProsperOps, Spot, Zesty: continuous management |
| Chargeback and showback | Basic, via tags and the CUR | Finance-ready reports |
| Cost in pull requests | Not native | Infracost |
| Price of the tool | Free to use; CUR costs only S3 and queries | Share of managed spend or a platform fee |
| Implements the savings for you | No | No |
How a match works (example)
- You tell us about the work
You fill in a short form: what you run today, what you want to move, test or build, your stage and your region.
- We pick one partner
We read your answers and pick one vetted AWS consulting partner that fits the work, the stack and the region. We reply within 24 hours; your matched partner reaches out within 5 business days.
- The partner checks which funding fits
Your matched partner scopes the work with you. Then it checks which partner-filed funding fits: MAP if you are moving to AWS, POC if you want to test something, or incremental workload (IW) funding if you are already on AWS and launching new work.
- The partner files, AWS decides
If the work qualifies, the partner files the funding request with AWS. AWS reviews it and decides. The amount depends on the workload.
- You pay nothing
CloudRoute is free for startups. Partners pay CloudRoute a monthly membership plus 10% of AWS-approved funding.
AWS Activate credits are separate, and you apply for them yourself. Use Activate Founders if no investor backs you. Use Activate Portfolio with the Org ID or invite from your VC, accelerator, incubator or angel group if it is an Activate Provider. A consulting partner cannot apply for Activate on your behalf.
Common questions
What are the main AWS cost optimization tools?
Are the AWS-native cost tools really free?
When is AWS-native enough, and when do I need a paid platform?
How do I allocate Amazon EKS costs to teams?
What does ProsperOps do that AWS does not?
Do these tools reduce my bill, or just show me the savings?
How does CloudRoute fit in, and who pays?
Stop reading dashboards. Start cutting the bill.
The tools surfaced the savings. CloudRoute matches you with a vetted AWS partner who implements them: right-sizing, Graviton, commitments, data transfer. CloudRoute is free for startups. If the follow-on work includes a migration (MAP), a test (POC) or new work on AWS (IW), the partner can file funding for it: typically $50K to $150K for startups. Depends on the workload; AWS approves.