The new benchmark brings broad, deep coverage across every layer of cloud AI cost, with tested controls that discover, fix, and prevent waste
ARLINGTON, Va.--(BUSINESS WIRE)--Stacklet today introduced the Cloud AI FinOps Benchmark, a set of tested controls that define what good cloud AI cost governance looks like across Amazon Web Services, Google Cloud, and Microsoft Azure. Teams can assess their environment against the benchmark to see exactly where usage can be optimized, then act on it through Stacklet's control plane, using automated policies and agentic AI to fix and prevent waste. Built on newly expanded coverage of cloud AI and GPU resources, with new controls added continuously, the benchmarks are ready out of the box and adjustable, so teams can tune remediation and notification workflows to their environment.
Cloud AI infrastructure is one of the fastest-growing and least-governed lines in the cloud bill: inference runs around the clock, idle environments linger, jobs and artifacts pile up, and token usage climbs unchecked. Teams can see the spend but struggle to govern it, and without a way to fix and prevent waste automatically, the cost of inaction compounds by the day.
“AI is a real, fast-growing number on the cloud bill now, and most teams are still figuring out how to see it, let alone control it. But watching a dashboard doesn't save anyone money,” said Travis Stanfield, CEO, Stacklet. “You need a standard for what good looks like and a way to act on it, and that's the gap we built the Cloud AI FinOps Benchmark to close."
The Cloud AI FinOps Benchmark is the result of months of research and testing. The Stacklet team studied each provider's AI services at the API level, mapping where cost hides, how it accrues, and which configurations drive waste, then translated those findings into tested controls. As coverage expanded across services such as AWS Bedrock and SageMaker, Google Vertex AI, and Azure AI, each new service added controls, and the benchmark continues to grow as providers ship new capabilities.
Stacklet's Cloud AI FinOps Benchmark provides:
- Coverage across every layer of cloud AI cost, no blind spots. Tested controls spanning GPUs, foundation models, custom models, storage, and token usage thresholds across Amazon Web Services, Google Cloud, and Microsoft Azure.
- Ready-to-run packs that drive rapid value. Delivered as packs of tested policies, built and maintained by the Stacklet team, continuously expanded, and adjustable to each team's workflows.
- Governance that acts, not just measures. The benchmark is wired into Stacklet's control plane, so the same controls that assess a team's posture also remediate it: retiring idle endpoints, pausing stalled training jobs, blocking unapproved models, and alerting when token usage crosses a threshold.
- Runtime and shift-left coverage, waste caught either way. Controls act on live resources as they run or drift, and check Terraform and infrastructure-as-code before deployment.
"AI cost doesn't wait for production; it builds up in experimentation and development long before a workload ships. A benchmark that defines what good cloud AI governance looks like, and can act on it to optimize spend, is exactly what teams scaling AI need,” said Lindbergh Matillano, Director of Cloud & AI Optimization, Avalara. “We're looking forward to trying Stacklet's Cloud AI FinOps Benchmark as we continue to grow our AI footprint."
Product Availability
The Cloud AI FinOps Benchmark is available now. Teams can assess their environment against the benchmark and act on the findings through Stacklet's control plane. To learn more about Stacklet's Cloud AI Infrastructure governance capabilities, visit https://stacklet.ai/cloud-ai-infrastructure/.
About Stacklet
Stacklet is the control plane for autonomous cloud and AI infrastructure, built by the creators of CNCF's Cloud Custodian. Trusted by enterprises managing more than $10 billion in cloud spend, Stacklet autonomously discovers, fixes, and prevents issues across operations, cost, and security, delivering up to 50% reduction in costs and 80% less time spent on governance. For more information, visit stacklet.ai.
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