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Why Your Kubernetes Setup Is Burning Money

6 min read
IM

Iván Martínez Agüero

Fractional CTO & Technical Architect

Why Your Kubernetes Setup Is Burning Money

Most startups don't need Kubernetes. If you're pre-Series A and running K8s, you're probably burning $5K-$15K per month on infrastructure complexity that's actively slowing you down.

The Kubernetes Trap

Here's what happens: Your technical co-founder reads that "all modern apps run on Kubernetes." Your lead engineer wants it on their resume. Your cloud consultant bills hourly to set it up.

Three months later:

  • Your AWS bill tripled
  • Deployments take 2 hours instead of 5 minutes
  • Your engineer spends 40% of their time debugging cluster issues
  • You still haven't shipped the feature your users actually want

When You Actually Need Kubernetes

You need K8s when:

  1. You're running 20+ microservices (not 3)
  2. You need multi-cloud orchestration (not "we might someday")
  3. You have a dedicated DevOps team (not your CTO doing it on weekends)
  4. Your traffic patterns justify the complexity (100K+ daily active users with spiky loads)

What You Should Use Instead

If you're pre-product/market fit:

  • Vercel/Netlify for frontend
  • Railway/Render for backend
  • Managed databases (not self-hosted PostgreSQL on K8s)
  • Total cost: $100-500/month

If you're post-PMF but pre-scale:

  • AWS ECS/Fargate (Kubernetes-lite)
  • CloudRun on GCP
  • Fly.io for global edge
  • Total cost: $500-2000/month

The Real Cost of K8s

It's not just the infrastructure. It's:

  • 20+ hours/month of engineering time maintaining clusters
  • 2-3 day onboarding time for new developers
  • Delayed feature velocity while debugging networking issues
  • Opportunity cost of not working on product

Pro tip: If your current setup can handle 10x your current traffic, optimization is premature. Ship features instead.

The Trigger to Scale Up

Migrate to Kubernetes when:

  1. Your managed solution costs more than K8s + engineer time
  2. You're CPU/memory constrained and need fine-grained resource allocation
  3. You have actual compliance requirements (not theoretical ones)
  4. You've hired someone whose full-time job is infrastructure

Until then? Ship product. Kubernetes can wait.


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