You’re building something real — often with a small product team and no one whose job is infrastructure. Servers, databases, deployments and monitoring feel like a second company.
Here’s the good news: you don’t need to hire a full-time DevOps engineer on day one. You need the right setup — or a partner who owns it.
Start Simple But Start Right
The biggest mistake early-stage teams make is either overcomplicating things (Kubernetes on day one) or undercooking them (deploying directly from a laptop).
Here’s what a solid starting infrastructure looks like:
The Minimum Viable Infrastructure
-
A managed platform: Use a Platform-as-a-Service like Railway, Render or Fly.io for your main application. They handle deployments, SSL and basic scaling.
-
A managed database: Don’t run your own database. Use a managed service — Supabase, PlanetScale or your cloud provider’s managed database option.
-
A deployment pipeline: Set up GitHub Actions or similar CI/CD. Push to main → tests run → app deploys. This takes 30 minutes to set up and saves you hours every week.
-
Basic monitoring: At minimum, set up uptime monitoring (UptimeRobot is free) and error tracking (Sentry has a free tier).
Total cost: $50–$200/month for a low-traffic application.
When to Upgrade
Your simple setup will carry you further than you think. But there are clear signals that you need to level up:
- Your cloud bill crosses $500/month — time to optimize
- You’re getting real traffic — auto-scaling becomes important
- You’re losing sleep over outages — monitoring and alerting need an upgrade
- You’re spending more than 20% of your time on infrastructure — that time should go to product
The Middle Ground
When you outgrow the basics, here’s the next level:
- Move to a proper cloud provider (AWS, GCP or Azure) with Infrastructure-as-Code.
- Set up proper environments — staging + production, not just production.
- Implement auto-scaling — your app handles traffic spikes without you.
- Add comprehensive monitoring — know about problems before your users do.
- Set up automated backups — because data loss is not recoverable.
This is typically where a partner like Kernul comes in. We set all of this up for you in 2–3 weeks and manage it ongoing.
What About AI-Specific Infrastructure?
If your product uses AI (and you’re reading this blog, so it probably does), you’ll have additional infrastructure needs:
- Model hosting: Where your AI model runs and serves predictions
- GPU compute: If you’re running your own models (not just calling an API)
- Vector databases: For RAG-based applications
- Data storage: Training data, embeddings, model artifacts
For early-stage teams without a dedicated infra hire, our recommendation is:
- Start with APIs (OpenAI, Anthropic, etc.), when possible — let them handle the GPU headache.
- Use serverless GPU platforms (Modal, Replicate, RunPod), if you need custom models.
- Only run your own GPU infrastructure when you have a clear cost or performance reason to do so.
The Three Rules of Early-Stage Infrastructure
After working with dozens of pre-seed and seed startups, here are the three rules we always give:
Rule 1: Automate Everything You Do Twice
If you’re SSH-ing into a server to deploy, you’ll keep doing it. If you set up a pipeline once, it deploys for you always.
Rule 2: Pay for Managed Services
Your time is worth more than the $50/month difference between managed and self-hosted. Every hour you spend managing Postgres is an hour you do not spend on your product.
Rule 3: Get Help Before You Need It
The worst time to look for infrastructure help is when your site is down and users are leaving. Get a solid foundation early.
Your Next Step
If you’re a pre-seed or seed team without a dedicated infrastructure engineer, we’d love to help you set up infrastructure that just works. Our Starter plan ($1,500/month) gives you a named infrastructure partner while your product team ships features.
No infrastructure headaches. Monitoring and on-call coverage scale with your plan. Just a reliable product your users can rely on.