Tracks/Track 14 — Cloud FinOps & Infrastructure/14-4
Track 14 — Cloud FinOps & Infrastructure

14-4: Kubernetes Cost Management

Right-sizing K8s pods, combating cluster sprawl, and allocating costs in dense multi-tenant container architectures.

1 Lessons~45 min

🎯 What You'll Learn

  • Model namespace allocation costs
  • Prevent Pod resource hoarding
  • Optimize Cluster Auto-scaler economics
Free Preview — Lesson 1
1

The Fallacy of Free Containers

Kubernetes is fundamentally a resource packing algorithm. However, most developers set their "Resource Requests" far higher than necessary out of caution. If 50 pods request 4GB of RAM but only use 500MB, the Kubernetes scheduler thinks the node is full.

The scheduler then spins up another expensive EC2 node to handle the "demand," creating massive cluster bloat while physical server utilization sits at 12%.

Tools like Kubecost map the actual CPU cycles consumed by a specific Pod back to the owning engineering team's namespace, creating strict financial accountability for over-provisioning.

Cluster Utilization Gap

The ratio of CPU/RAM actively used by processes versus the total capacity purchased from the cloud provider.

Often hovers around 20%. Target: 65%+
Right-Sizing Recapture Value

The immediate savings generated by lowering Pod resource requests to match historical usage P99s.

Massive compounding reduction
📝 Exercise

Implement aggressive Pod limits across staging environments.

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01import { orchestrator } from '@exogram/core';
02
03const router = new AgentRouter({);
04strategy: 'COST_EFFICIENT_SLM',
05fallback: 'FRONTIER_MODEL'
06});
07
08await router.guardrail(payload);
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Module Syllabus

Lesson 1: The Fallacy of Free Containers

Kubernetes is fundamentally a resource packing algorithm. However, most developers set their "Resource Requests" far higher than necessary out of caution. If 50 pods request 4GB of RAM but only use 500MB, the Kubernetes scheduler thinks the node is full.The scheduler then spins up another expensive EC2 node to handle the "demand," creating massive cluster bloat while physical server utilization sits at 12%.Tools like Kubecost map the actual CPU cycles consumed by a specific Pod back to the owning engineering team's namespace, creating strict financial accountability for over-provisioning.

15 MIN
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