StormForge Optimize Live continuously rightsizes Kubernetes workloads to ensure applications are both cost effective and performant while removing developer toil.
StormForge Optimize Live continuously rightsizes Kubernetes workloads to ensure cloud-native applications are both cost effective and reliable while removing developer toil.
As a vertical pod rightsizing solution, Optimize Live is autonomous, tunable, and works seamlessly with the Kubernetes horizontal pod autoscaler (HPA) at enterprise scale.
Optimize Live addresses both over- and under-provisioned workloads by analyzing usage data with advanced machine learning to recommend optimal resource requests and limits. Recommendations can be deployed automatically on a flexible schedule, accounting for changes in traffic patterns or application resource requirements, ensuring that workloads are always right-sized and freeing developers and platform engineers from the toil and cognitive load of infrastructure sizing.
Highlights
StormForge Optimize Live automatically detects, analyzes, and predictively rightsizes your workloads in K8s using machine learning.
Integrates with your GitOps workflow
Ensure recommendations are always enforced alongside Argo or Flux. No need to change your manifests or pipelines, unless you want to.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
This listing uses a single usage-based pricing dimension. You pay an hourly rate tied to the aggregate CPU requests across your connected Kubernetes clusters. Billing scales with the number of requested CPU cores, so cost rises or falls with your workload footprint. There is no upfront payment and no minimum commitment. Charges appear in your AWS bill, and you can track hourly usage through AWS Cost Explorer. Per-cluster reporting is available once you configure a cost allocation tag.
Top-of-mind questions for buyers
What counts toward the aggregate CPU requests I'm billed on?
Billing is based on the requested CPU cores across each cluster connected to your account. The metric sums the CPU your workloads reserve, not actual CPU used. Requested cores from every connected cluster combine into one aggregate figure that drives your hourly rate.
What happens to my bill if my workloads scale up or down?
Your hourly charge tracks the aggregate CPU requests across connected clusters. When workloads scale up and reserve more CPU cores, the rate rises. When they scale down or you disconnect clusters, it falls. There is no minimum, so cost follows your actual footprint each hour.
Can I see cost broken out by individual cluster?
By default, AWS Marketplace shows only the total cost billed to your account. To get per-cluster reporting, configure a cost allocation tag for the cluster metadata. After that, per-cluster charges appear in AWS Cost Explorer, though it can take up to 48 hours to process.
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