Stop Overpaying for Kubernetes
KubeOptimiser analyses every workload, recommends precise CPU & memory limits, and opens a GitOps PR to apply the fix — with one click.
Cluster Overview
142 workloads profiledpayments-api
confidence 98%
Most clusters are quietly bleeding money
Engineers set CPU and memory limits once, defensively, and never revisit them. The result is paying for capacity nobody uses.
of Kubernetes clusters are overprovisioned, reserving far more CPU and memory than workloads ever consume.
average wasted spend per cluster — capacity provisioned, billed, and left idle month after month.
of engineering time to manually profile, tune, test, and roll out limits for a single workload.
From install to savings in five steps
No agents to babysit, no dashboards to build. Deploy once and let KubeOptimiser do the profiling, the math, and the pull requests.
Deploy the in-cluster agent
~2 minA lightweight, read-only agent installs via Helm. No sidecars, no code changes, no restarts.
Profile every workload automatically
The agent samples real usage via Prometheus or the Kubernetes Metrics API, building a per-workload profile across daily and weekly cycles.
Review recommendations with confidence scores
Precise CPU & memory requests and limits appear in the dashboard — each with an explanation of why, the data behind it, and a confidence score.
One click opens a GitOps PR
GitHub · GitLab · BitbucketApply a fix and KubeOptimiser opens a pull request against your infra repo — a clean Helm, values, or Terraform diff, ready for review.
Merge, apply, and track the savings
Your existing CD pipeline applies the change. KubeOptimiser tracks realised savings against baseline so you can prove the impact.
Everything you need to run lean clusters
A complete cost-optimisation control plane — recommendations, autoscaling, and allocation in one place.
Right-sizing engine
CPU & memory recommendations with full explainability — see the usage data and reasoning behind every suggested limit.
GitOps-native
Generates Helm diffs, values overrides, or Terraform HCL — committed as a reviewable PR, never applied behind your back.
Cost allocation
Per-workload, per-namespace, and per-node cost breakdowns with native AWS, GCP, and Azure billing rates.
HPA & KEDA scaling
Design, preview, and apply horizontal autoscaling and event-driven KEDA policies directly from the UI.
Predictive scaling
Schedule scale-up ahead of known traffic peaks — sales, launches, batch jobs — so you're never caught cold or over-buying.
Multi-cluster
Manage dozens of clusters across regions and clouds from a single pane of glass, with org-wide rollups.
Recommendation → Pull request → Realised savings
Every change flows through Git, so it's reviewed, audited, and revertible. No magic, no drift.
Start free. Scale when you save.
Every tier pays for itself the moment it trims a single overprovisioned workload.
- 1 cluster · up to 20 nodes
- Up to 5 users
- Core right-sizing recommendations
- Basic cost view
- Self-hosted
- GitOps PR automation
- Up to 5 clusters · 100 nodes
- Everything in Community
- GitOps PR automation
- HPA / KEDA management
- Predictive scaling
- Email support
- Unlimited clusters & nodes
- SAML SSO & multi-org
- SLA + dedicated support
- Custom billing model
- Audit logs & RBAC
- Onboarding & training
Platform teams ship leaner clusters
We cut our EKS bill by $22k a month in the first quarter. The PR workflow meant zero new process — it just showed up in our normal review queue.
The explainability is what sold our engineers. Every recommendation comes with the data, so nobody argues — they just merge. 160 workloads right-sized in a week.
Predictive scaling carried us through Black Friday without a single manual intervention — and we still came in 31% under budget.