Most teams see one line item: "EKS — $82,400/mo." Atmosly turns that into real Kubernetes cost optimization: it breaks cloud spend down to namespace, service, and team, flags the idle resources and oversized workloads, and turns real p95 usage into right-sizing the dev team can apply themselves. Across AWS, GCP, and Azure — not a spreadsheet.
Kubernetes Cost Optimization runs continuously on every connected cluster, powered by in-cluster cost telemetry — Kubernetes cost optimization and cloud cost management in one loop. No tagging project, no quarterly spreadsheet, just the cost visibility your engineers can act on.
One bill becomes a map. Automatic cost allocation splits spend by account, by cluster, by namespace, and by service — instance type, load balancer, NAT gateway, data transfer, and storage, each on its own line. Then hand each team its own showback and chargeback view.
Atmosly reads each workload's p95 over time and proposes a concrete new request/limit, with the dollar impact attached. Reserved-instance and savings-plan opportunities surface the same way — ranked by monthly savings.
Set budgets and get notified the moment daily spend crosses the line. A monthly forecast tells you where you'll land. Idle workloads and orphaned volumes get flagged before they quietly bleed another month of spend.
The cost visibility engineers trust because it comes from the cluster — and finance trusts because it reconciles to the cloud bill. Cloud cost management both sides can finally agree on.
Amazon EKS, Google GKE, and Azure AKS spend normalized into a single dashboard — EKS, GKE, and AKS cost optimization side by side, with per-cloud and per-account totals reconciled to the bill.
Powered by in-cluster cost telemetry, so spend maps to the actual workloads — not just the cloud account.
Concrete request/limit changes from observed usage, each with its dollar impact, applied as a reviewable PR.
Reserved-instance and savings-plan recommendations sized to your steady-state, ranked by monthly savings.
Give every team its own cost view so spend has an owner — without standing up a FinOps function.
Daily-budget and monthly-estimate alerts, plus a month-end forecast from your current run-rate.
Connect one cluster read-only and you'll have a full cost breakdown — idle workloads, oversized requests, and right-sizing recommendations — on your dashboard in about five minutes. No tagging project, no sales call.
Install the agent with one Helm command, or connect through the direct cloud integration. It needs read-only access — no write permissions to assess your spend, on AWS, GCP or Azure.
≈ 2 minutes · read-onlySpend maps to namespace, service and team automatically, using metrics from the Prometheus already running in your cluster — idle workloads, oversized requests and orphaned volumes flagged, reconciled to the cloud bill.
≈ 5 minutes · no tagging projectRight-sizing, unused-resource cleanup, right-node selection and Spot recommendations open as pull requests the owning team reviews, merges and can revert.
reviewable · reversibleReal Kubernetes cost reduction, measured — here's what resource optimization from actual usage delivers once the recommendations ship.
*Representative of customer-reported outcomes. Your results depend on workload mix and current utilization.
A deploy, an incident, a security finding, and a cost change are the same story — surfaced in one UI, with one audit trail.
Cost IntelligenceTwelve Kubernetes cost optimization tools compared for 2026 — OpenCost, Kubecost, CAST AI, Karpenter, StormForge, ScaleOps, Densify, Zesty, CloudZero, Goldilocks, AWS Compute Optimizer and Atmosly — mapped to the four layers of cluster waste, with a two-week evaluation runbook.
AI SRE"AI SRE" now means four different things. We compare Cleric, Metoro, Datadog Bits, K8sGPT and Atmosly Astra on the axis that matters at 3am: does the tool just diagnose the incident, or actually ship the fix?
AI SRETen crash-looping pods of one Deployment should be one page, not ten. Why Kubernetes alert fatigue is a grouping problem — and how workload-identity grouping and an AI SRE agent fix it.
Connect one cluster, read-only. The cost breakdown, idle resources, and right-sizing recommendations show up on your dashboard in about five minutes — the cloud waste you're paying for, made visible. Free, no sales call.