Utilization

Kubernetes spend, under control.

Containers hide cost behind abstraction. OPTMIN allocates K8s spend down to namespace, workload and team — then rightsizes, catches replica drift, and reclaims idle pods automatically, reliability first.

Cost allocation Rightsizing Drift detection
Cluster · prod-eurightsizablenamespace: payments · 18 pods3 idle pods flagged
Up to 50%
K8s cost reduction
Reliability-first
every action
1 command
read-only install

Allocate cost to the workload

Map cluster spend to namespace, deployment and team — so Kubernetes stops being a single untagged line item.

  • Namespace, workload and team allocation
  • Shared cost split fairly across tenants
  • Cost per service and per request
Cost · namespacesliveGroup by: Namespace ▾Last 30 days ▾NAMESPACEMONTHLY COSTΔ MoMpayments$41k▲ 4%checkout$32k▼ 2%search$22k▲ 1%data-pipeline$16k▼ 3%monitoring$7k▼ 1%5 of 12 namespaces$118k total / mo

Rightsize and reclaim, reliability-first

OPTMIN spots over-provisioned requests, replica drift and idle pods — and the Rightsizer agent corrects them, with your approval and health at the center.

  • Right-size CPU/memory to real usage
  • Catch replica drift before it costs you
  • Reclaim idle pods and orphaned volumes
Rightsizingauto-fixrequests vs actual usageover-provisioned → rightsized-38% reclaimed
Challenges we solve

Kubernetes is a black box for lean teams.

Balancing K8s efficiency with reliability creates delays and bottlenecks across the whole org.

The challenge

Too much time babysitting clusters

Autoscalers, debugging, scaling environments and policy enforcement never end — without dedicated platform engineers, teams are stretched thin.

How OPTMIN solves it

Autonomous rightsizing and drift detection run continuously, so the cluster tunes itself — your team approves, OPTMIN does the work.

The challenge

Over-provisioning to avoid outages

Teams pad CPU and memory 'just in case'. With no usage data, that waste compounds with zero accountability.

How OPTMIN solves it

Pod-level baselines right-size requests and limits to real demand — reliability-first, never trading away uptime.

The challenge

Siloed tools, fragmented view

Monitoring, cost and logging live in separate tools; a unified picture of health, performance and spend is nearly impossible.

How OPTMIN solves it

One pane maps cost to namespace, workload and team alongside utilization — health, performance and spend in context.

The challenge

Complexity explodes at scale

Hybrid and multi-cloud across many clusters makes consistent governance hard; reliability and compliance slip.

How OPTMIN solves it

Policy guardrails by workload criticality, environment and business hours apply across every cluster and cloud, automatically.

Tame your Kubernetes bill

Connect a cluster read-only and see where the waste is. Live in minutes.