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:
- You're running 20+ microservices (not 3)
- You need multi-cloud orchestration (not "we might someday")
- You have a dedicated DevOps team (not your CTO doing it on weekends)
- 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:
- Your managed solution costs more than K8s + engineer time
- You're CPU/memory constrained and need fine-grained resource allocation
- You have actual compliance requirements (not theoretical ones)
- You've hired someone whose full-time job is infrastructure
Until then? Ship product. Kubernetes can wait.
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