The founder was deep in AWS documentation. VPCs, subnets, security groups, IAM roles. Three weeks later, he still hadn't written any product code.
"I just need to deploy my app," he said. "Why is this so complicated?"
Because AWS is designed for companies with dedicated infrastructure teams. Not for founders who just want to ship something.
The Cloud Decision Landscape
Choosing cloud infrastructure is one of the most consequential decisions early-stage startups make. Get it wrong, and you'll spend weeks learning tools that don't help you ship product. Get it right, and infrastructure becomes invisible—you deploy, it works, you move on.
The problem is that the "right" choice depends on your stage, your team, and your product. What's perfect for a Series B company is overkill (and expensive) for a pre-seed startup.
Let's break down the options honestly.
The Three Paths for Early-Stage Startups
Early-stage startups have three reasonable choices, plus variations and combinations:
Path #1: Managed Platforms
What they are: Services like Heroku, Vercel, Railway, Render, Supabase, Fly.io, and others that handle infrastructure for you. You deploy your code, they handle the servers, scaling, and operations.
What they offer:
- Deploy with git push or a simple dashboard
- Automatic SSL certificates
- Built-in databases (sometimes)
- Simple scaling (upgrade tier)
- Minimal DevOps knowledge required
What they don't offer:
- Fine-grained control over infrastructure
- The lowest possible costs at scale
- Access to advanced cloud services
- Complete portability
Best for:
- Pre-revenue or early revenue startups
- Teams without dedicated infrastructure expertise
- Products with straightforward requirements
- Founders who want to focus on product, not infrastructure
Real-world example: A fintech startup launched on Vercel + Supabase. They had zero DevOps experience. Total infrastructure setup time: 2 hours. Monthly cost at launch: $50/month. Monthly cost at 10,000 users: $200/month.
Path #2: Major Cloud Providers
What they are: Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. These are comprehensive cloud platforms offering virtually every service you might need.
What they offer:
- Almost unlimited flexibility
- Advanced services (ML, analytics, specialized databases)
- Cost optimization at scale
- Enterprise-grade security and compliance
- Transferable skills (these are industry standards)
What they don't offer:
- Simplicity—you need to configure everything
- Guidance—you must know what you need
- Managed experience—you're managing the infrastructure
- Quick setup unless you already know what you're doing
Best for:
- Teams with cloud expertise
- Products with specific requirements
- Companies planning significant scale
- Situations where cost optimization matters
Real-world example: A healthcare startup chose AWS because of HIPAA compliance requirements. They had a technical co-founder with AWS experience. Infrastructure setup took 3 weeks. Monthly cost: $500/month. The flexibility allowed them to implement custom compliance controls.
Path #3: Hybrid Approach
What it is: Start with managed platforms, migrate to major clouds when you need it. Most successful startups end up here.
How it works:
- Launch on managed platforms (fast, simple)
- Identify when you need more control or lower costs
- Migrate specific services to major clouds
- Eventually have a hybrid setup
Best for:
- Most startups (this is the most common path)
- Situations where needs evolve
- Teams who want to defer complexity
Real-world example: An e-commerce startup launched on Railway. At 50,000 users, their monthly bill reached $3,000. They migrated to AWS, kept managed services for some components, and reduced costs to $800/month while gaining more control.
Detailed Comparison: Major Cloud vs Managed
Let's compare the two most common paths directly:
Factor | Managed Platforms | Major Cloud Providers |
|---|---|---|
Setup Time | Hours | Days to weeks |
Learning Curve | Minimal | Significant |
Monthly Cost (early) | $50-200 | $200-1000 |
Monthly Cost (scale) | $1000-5000+ | $500-5000+ |
Control | Limited | Complete |
Troubleshooting | Platform handles | You handle |
Skills Transferability | Limited | High |
Scaling | Automatic (tier upgrades) | Manual configuration |
Vendor Lock-in | High | Low to medium |
Cost Analysis at Different Stages
Pre-Revenue / Pre-Launch:
- Managed: $0-100/month (free tiers available)
- Major Cloud: $100-500/month (learning and experimentation)
Launch / Product-Market Fit (0-1000 users):
- Managed: $100-300/month
- Major Cloud: $300-1000/month
Growth (1000-100,000 users):
- Managed: $500-2000/month
- Major Cloud: $500-3000/month
Scale (100,000+ users):
- Managed: $2000-10000+/month
- Major Cloud: $1000-10000+/month (cost advantage emerges here)
Key insight: The cost crossover point varies, but for most startups, managed platforms are more cost-effective until you reach significant scale. The question is whether you'll reach that scale—and when.
Specific Platform Recommendations
For Frontend / Full-Stack Frameworks
Vercel:
- Excellent for Next.js, React, Vue, Svelte
- Zero-config deployments
- Great free tier
- Excellent performance and edge caching
- Best for: Frontend-heavy applications
Railway:
- Simpler than AWS, more control than Heroku
- Good for full-stack applications
- Reasonable pricing
- Good developer experience
- Best for: Full-stack apps that need more than Vercel offers
Render:
- Heroku alternative with better pricing
- Good for: Applications that need background workers
For Databases
Supabase (PostgreSQL):
- Open-source Firebase alternative
- Real-time subscriptions
- Built-in auth and storage
- Best for: Applications needing database + auth + storage
PlanetScale (MySQL):
- Serverless MySQL
- Excellent scaling
- Best for: MySQL-based applications at scale
Neon (PostgreSQL):
- Serverless PostgreSQL
- Excellent for: Applications with variable load
For Major Cloud Providers
AWS (Amazon Web Services):
- Largest ecosystem
- Most services
- Steepest learning curve
- Best for: Complex requirements, enterprise features
Google Cloud Platform (GCP):
- Strong in data/ML
- More intuitive than AWS
- Competitive pricing
- Best for: Data-heavy applications, startups familiar with Google
Microsoft Azure:
- Best for Windows/.NET environments
- Strong enterprise integration
- Good for: Microsoft-centric technology stacks
When Managed Platforms Make Sense
Use managed platforms when:
You Have Limited Technical Resources
You need to ship fast and can't afford infrastructure complexity. Every hour spent learning infrastructure is an hour not spent building product.
Example: Solo founder with no DevOps experience. Chose Vercel + Supabase. Shipped MVP in 2 weeks.
Your Needs Are Simple
A web app, a database, maybe some background jobs. Nothing exotic. No unusual compute requirements. No specific compliance needs.
Example: B2B SaaS application with standard CRUD operations. Chose Railway. Works perfectly.
You're Still Validating
You don't know if this product will succeed. Don't invest in infrastructure for a product that might pivot or fail.
Example: Testing multiple ideas. Used free tiers on managed platforms. Minimal cost, maximum flexibility.
Time-to-Market Matters
Competitors are moving. You need to ship now. Infrastructure is a means to an end, not the product itself.
Example: Founder with deadline from investor. Used Heroku. Shipped on time.
When Major Clouds Make Sense
Use major clouds when:
You Have Specific Requirements
Unusual compute needs, specific compliance requirements, complex networking, or services that managed platforms can't provide.
Example: Healthcare startup needing HIPAA compliance. Used AWS with HIPAA-eligible services. Compliance built-in.
You Have Cloud Expertise
A technical co-founder or engineer with significant cloud experience. Someone who knows what they're doing.
Example: CTO with 10 years AWS experience. Built on AWS from day one. Infrastructure decisions made in hours, not days.
You're Confident You'll Scale
You have evidence that you'll reach significant scale. The cost savings at scale justify the complexity.
Example: B2B platform expecting rapid growth. AWS infrastructure designed to scale. Costs optimized from day one.
You Need Advanced Services
Machine learning, advanced analytics, specialized databases, or services that managed platforms don't offer.
Example: AI-powered application needing custom ML infrastructure. Used GCP for Vertex AI integration. Couldn't get this on managed platforms.
The Migration Path
If you start on managed platforms and eventually need to migrate, here's a practical path:
Phase 1: Begin on Managed (0-6 months)
Goal: Ship product, validate idea, learn from users
Stack example:
- Frontend: Vercel
- Backend: Next.js API routes or Railway
- Database: Supabase or PlanetScale
- Auth: Supabase Auth or Clerk
- Storage: AWS S3 (via SDK) or Supabase Storage
Focus: Speed to market, learning, iteration
Phase 2: Identify Needs (6-18 months)
Goal: Understand what's working, what's not, what's coming
Questions to answer:
- What services are we paying for but not using?
- What limitations are we hitting?
- What new requirements are emerging?
- What's our scale trajectory?
Actions:
- Monitor costs and usage
- Identify pain points
- Plan for next phase
Phase 3: Selective Migration (18+ months)
Goal: Optimize cost, gain control, prepare for scale
Common migrations:
- Move database from Supabase to PlanetScale or AWS RDS
- Move compute from Railway to AWS ECS or GCP Cloud Run
- Move storage to AWS S3 with CDN
- Keep managed services for what they're good at
Strategy:
- Migrate one component at a time
- Run parallel systems during migration
- Test thoroughly before cutting over
- Have rollback plan
Timeline: 2-6 months for comprehensive migration
Common Mistakes to Avoid
Mistake #1: Starting with AWS When You Don't Need It
The founder who spent three weeks learning AWS instead of shipping product. This is the most common early-stage infrastructure mistake.
Why it happens:
- AWS feels professional
- Big companies use AWS
- You want to be prepared for scale
- FOMO about doing things "right"
The cost: Weeks of lost development time. Mental overhead of learning complex systems. Delayed launch.
The fix: Start simple. Defer complexity. You can always migrate later.
Mistake #2: Ignoring Costs Until It's Too Late
Managed platforms have simple pricing until you don't. Suddenly your bill is $5,000/month and you don't know why.
Why it happens:
- Pricing looks reasonable at low usage
- Usage grows faster than expected
- You're focused on product, not costs
- Alerting isn't set up
The cost: Unexpected expenses, cash flow problems, forced migration under pressure.
The fix: Monitor costs from day one. Set up billing alerts. Understand pricing tiers.
Mistake #3: Over-Engineering for Future Scale
Building infrastructure for 10 million users when you have 10.
Why it happens:
- You want to be prepared
- It feels professional
- You're worried about rewriting
- "We'll scale into this"
The cost: Delayed launch, increased complexity, wasted effort on scenarios that may never happen.
The fix: Build for 10x current scale, not 1000x. Defer complexity until you need it.
Mistake #4: Under-Engineering for Current Needs
Using tools that can't handle your actual requirements.
Why it happens:
- Chose cheapest option
- Didn't anticipate needs
- Optimized for wrong factors
- Didn't test properly
The cost: Performance problems, downtime, forced migrations, poor user experience.
The fix: Understand your actual requirements. Test with realistic loads. Don't choose tools that can't handle your needs.
Mistake #5: Not Learning from Others
Repeating mistakes that others have already made.
Why it happens:
- Everyone wants to learn from their own experience
- Too much advice feels overwhelming
- You think your situation is different
- Confirmation bias
The cost: Reinventing the wheel. Making avoidable mistakes.
The fix: Talk to founders who've been through this. Read case studies. Learn from others' experience.
The Decision Framework
Still unsure? Answer these questions:
Question 1: Do you have cloud expertise on your team?
Yes → Consider major cloud (AWS/GCP/Azure) No → Start with managed platforms
Question 2: What are your infrastructure requirements?
Simple (web app + database + auth) → Managed platforms Complex (ML, compliance, specialized services) → Major cloud
Question 3: What's your timeline?
Need to ship in weeks → Managed platforms Have months for infrastructure → Either, depending on other factors
Question 4: What's your budget?
Very limited ($0-500/month) → Managed platforms (free tiers) Moderate ($500-2000/month) → Managed platforms Significant ($2000+/month) → Either, depending on other factors
Question 5: How confident are you in your product-market fit?
Validated, growing → Major cloud (prepare for scale) Still searching → Managed platforms (defer infrastructure decisions)
The Practical Recommendation
For most early-stage startups:
Start with Vercel (for frontend) + Supabase (for backend/database)
Or:
Start with Railway or Render (for full deployment)
Focus on your product. Ship fast. Learn from users.
When your infrastructure bill becomes a significant expense (say, over $1,000/month consistently), or when you have requirements that managed platforms can't meet, then—and only then—consider moving to AWS or GCP.
By that point, you'll have the revenue to afford proper infrastructure management. And you'll have the knowledge to make good decisions about it.
The Bottom Line
The goal is to ship your product, not to build infrastructure.
Choose the path that gets you to market fastest. Optimize when you have something worth optimizing.
The best infrastructure is the one you don't think about because it just works. That might mean managed platforms today and major cloud tomorrow. That's fine. That's the natural evolution.
Trust me: I've seen hundreds of startups make this decision. The ones who ship fast and figure it out later almost always do better than the ones who spend months building infrastructure for products that never launch.
According to research from Y Combinator, successful startups defer infrastructure decisions until they have evidence those decisions matter. And according to data from Stripe's Atlas program, startups that ship in weeks rather than months have significantly higher survival rates.
Need Help With Your Cloud Strategy?
At Startupbricks, we help startups choose the right infrastructure for their stage. We've seen what works and what doesn't across dozens of technology stacks and migration paths.
Whether you need:
- Help choosing your initial infrastructure
- A migration plan from managed to cloud
- Cost optimization for your current setup
- Architecture review for scale readiness
We can help you make the right decision for your specific situation.