Kubernetes
Monitor compute, GPU, storage, and network costs for AI and other workloads by namespace, deployment, or label. Identify pod waste and rightsize workloads.
Case study
Vantage just works the way we work. With Terraform, Kubernetes, and all the tools we already use. It fits right into our stack, which made adoption easy.
Nick Van Wiggeren —CTO, PlanetScale
Read case studyGet set up in minutes via Helm
Vantage’s custom built agent offers a single in-cluster deployment that handles both metrics collection and uploads to Vantage without any intermediary requirements.
Identify pod waste and act on it
Get real time pod rightsizing recommendations to correct over-allocated vCPU and memory on a per-container basis.
Attribute network costs to pods
Allocate network spend to the pods that drive it, broken out by intra-zone, cross-AZ, cross-region, and internet egress traffic, and charge it back alongside compute and GPU costs.
Track GPU and AI workload costs
See GPU costs for AI and machine learning workloads by namespace or label, including shared NVIDIA MIG GPUs, alongside out-of-cluster costs from AWS, GCP, Oracle, or Azure.
Centrally manage hundreds of clusters
Track progress organization-wide by creating and sharing Kubernetes efficiency reports across your entire fleet of nodes.
