Rightsizing
Instances and Kubernetes workloads sized to what they actually use, with the monthly saving priced for each change.
Right-size every workload. Approve every fix.
Workload Optimization is one of the four solutions in Finitizer CloudIQ. It finds oversized, idle and always-on compute across AWS and Google Cloud, including EC2, EKS, GKE and Lambda, and prepares each fix for your engineers to review and approve.
What Workload Optimization covers
Off-hours scheduling
Schedules for development and test workloads that sit idle outside working hours, with the saving for each.
Idle and orphaned resources
Idle instances, unattached disks and other resources nobody uses anymore, found and priced.
Spot adoption
Workloads that suit Spot capacity, with the expected saving for each.
The AI behind every fix
AI in Finitizer CloudIQ does the investigating and the paperwork. Your engineers keep the decision.
Fini, the cost analyst
Ask questions about your cloud bill in plain English, such as why BigQuery costs rose yesterday, and get the answer with its root cause and the next step.
MCP server
Connect your own AI tools, such as Claude, to Finitizer's cost data and findings through the open Model Context Protocol.
Anomaly alerts and forecasts
Unusual spend is flagged as it appears, with hourly alerts on AWS, and forecasts show where the month is heading.
Fixes as code
Each finding becomes a Terraform pull request, a runbook with rollback steps or a Jira ticket that your engineers review and apply.
Frequently asked questions
What is workload optimization?
Workload optimization matches cloud resources to what each workload actually uses: right-size what is too big, schedule what idles outside working hours, remove what nobody uses, and move suitable workloads to Spot capacity.
Which services does it cover?
Virtual machines (Amazon EC2 and Compute Engine), Kubernetes (EKS and GKE), and containers and serverless (ECS, Fargate, Lambda and Cloud Run), plus SageMaker, Bedrock and GPU workloads.
Does Finitizer change my workloads?
No. Finitizer prepares each change as Terraform, a runbook or a Jira ticket. Your engineers review it and decide what to apply.
What do the AI agents do?
They investigate each finding, explain its cause, and prepare the fix and its rollback steps. They do not apply changes: every change is approved by your team.
How do I get started?
Get a free Cloud Cost Assessment, or try the free cloud cost tools first.