01
Requests are guessed once
Teams set CPU and memory requests during launch, then forget them. Months later, nodes are full on paper and empty in reality.
Why teams call us
The symptoms behind the search
02
Autoscaling stops at the node
Cluster autoscaling helps, but it cannot fix poor pod sizing, bad node pools, missing disruption budgets or workloads that cannot move.
03
Nobody sees service cost
Cloud bills show clusters and nodes. Engineering needs namespace, service, team and environment cost to make better choices.
What you get
Practical deliverables, not just advice
The output is designed for engineering teams that need to act: roadmaps, controls, dashboards, automation, runbooks and implementation support.
Requests and limits plan
Right-sized CPU and memory settings based on real utilization, not old guesses.
Autoscaling architecture
Cluster autoscaler, Karpenter, HPA, VPA, node auto-provisioning or provider-native scaling tuned to the workload.
Node pool and Spot strategy
Separate pools for steady, bursty, GPU, memory-heavy and interruptible workloads with safe fallback paths.
Kubernetes cost allocation
Kubecost, labels and dashboards that show spend by namespace, service, owner and environment.
How the work flows
From first look to handover
Profile the cluster
We inspect nodes, pods, requests, utilization, scaling behavior, workloads, storage and network cost.
Identify safe moves
We separate low-risk waste from changes that need staging, load testing or a rollback plan.
Tune and automate
We implement autoscaling, sizing, node pool and Spot improvements with observability in place.
Hand over cost visibility
Your team gets dashboards, owners and review rituals so clusters stay lean as services grow.
Tools we can work with
Improve the stack you already have
We usually make your current tools cleaner before recommending a switch. The goal is a better operating model, not a shiny tool migration.
EKSAKSGKEKarpenterCluster AutoscalerHPAVPAKubecostPrometheusGrafanaDatadogTerraformHelm
Questions
What people ask before we start
It should not. We separate billing-only changes from runtime changes, stage risky moves, and use health checks, disruption budgets and rollback plans.
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