Cloud hosting costs for startups range from $0 to $10,000+ per month depending on your traffic, architecture, and how well you manage your infrastructure. The problem is that most founders have no idea where they fall on that spectrum until they get their first surprise bill.
We have managed cloud infrastructure for products ranging from early stage MVPs to platforms with 100K+ active users. Here is what you will actually pay at each stage, what drives costs up, and how to keep them under control.
Stage 1: Pre Launch and Early Traction, $0 to $50 per Month
If you are building your MVP or have your first few hundred users, hosting should cost almost nothing. The modern stack makes this possible.
Vercel free tier handles most web applications with zero configuration. You get serverless functions, edge caching, automatic HTTPS, and preview deployments. Most startups do not outgrow the free tier for 6 to 12 months.
Supabase free tier gives you a PostgreSQL database, authentication, real time subscriptions, edge functions, and 500MB of storage. That is a complete backend for $0. The Pro plan at $25/month removes the free tier limits and adds daily backups, which is worth it the moment you have paying customers.
Stripe charges nothing until you process payments, then takes 2.9% + $0.30 per transaction. No monthly fee.
Total: $0 to $50 per month for a fully functional web application with authentication, a database, and payment processing. If you are spending more than this before product market fit, you are overbuilding your infrastructure.
Stage 2: Growing Product, $50 to $500 per Month
You have traction. A few thousand users, real traffic, and a growing database. This is where costs start to show up, but they should still be modest.
Compute costs are the first thing that grows. Serverless functions (Vercel, Supabase Edge Functions) charge per invocation. At 1 million function calls per month, you are looking at $20 to $40 in compute. If you are running a traditional server on AWS or GCP, a small instance (t3.medium or equivalent) costs $30 to $60 per month.
Database costs scale with storage and connections. Supabase Pro at $25/month handles most products at this stage. If you are on AWS RDS, a db.t3.medium PostgreSQL instance costs $50 to $80 per month. Add $20 to $40 for storage depending on your data volume.
File storage and CDN become relevant once you serve images, videos, or user uploads. Supabase Storage, AWS S3, or Cloudflare R2 cost $0.02 to $0.03 per GB stored. CDN costs (Cloudflare, Vercel, CloudFront) are typically $5 to $20 per month at this traffic level.
Monitoring and logging add $0 to $50 per month. Sentry is free up to 5K errors per month. Vercel Analytics is included in their Pro plan. If you are running your own logging stack (Datadog, New Relic), expect $20 to $50 per month at this scale.
Total: $50 to $500 per month. The wide range depends on whether you are using managed platforms (Vercel + Supabase) or running your own infrastructure on AWS/GCP.
Stage 3: Scaling Product, $500 to $5,000 per Month
Tens of thousands of users, significant API traffic, and a database measured in gigabytes rather than megabytes. This is where architecture decisions start having real dollar consequences.
Database is usually the biggest line item. A Supabase Pro plan with additional compute and storage runs $75 to $300 per month. On AWS RDS, a db.r6g.large with 100GB of storage costs $200 to $400 per month. Add read replicas for read heavy workloads and you double that.
Compute scales with traffic patterns. Serverless is cost effective for bursty traffic. Consistent high traffic is cheaper on reserved instances. A startup processing 10 million API requests per month pays $100 to $300 in serverless compute, or $60 to $150 for a dedicated instance handling the same load.
Third party services add up silently. Email delivery ($20 to $100/month), SMS ($50 to $200/month), AI API calls ($100 to $1,000/month), search (Algolia at $50 to $200/month), and analytics ($50 to $200/month). Individually small. Collectively significant.
At Traderly, scaling to 100K users required careful optimization of database queries, connection pooling, and CDN caching. The infrastructure cost scaled sublinearly with user growth because the architecture was designed for it from the start, not retrofitted after the bill arrived.
The Bill Shock Traps
Most startup cloud cost problems come from the same handful of mistakes.
Leaving dev environments running. That staging server you spun up 3 months ago and forgot about? Still costing $60 per month. Those 4 preview databases from branches that never merged? Still incurring storage charges. Audit your running resources monthly. We have seen startups cut 20 to 30% of their cloud bill just by shutting down forgotten resources.
Unoptimized database queries. A single missing index on a table with 500K rows can cause your database to do 100x more work than necessary. That translates directly to higher CPU usage, more IOPS, and a bigger bill. We covered this in detail in our architecture mistakes guide, database design is where most performance (and cost) problems originate.
Overprovisioning for theoretical scale. You do not need a db.r6g.4xlarge instance for 5,000 users. You do not need 3 availability zones for a product that has not validated product market fit. You do not need a Kubernetes cluster for a monolithic application. Right size your infrastructure for your actual traffic, not the traffic you hope to have in 18 months.
Ignoring egress costs. Cloud providers charge for data leaving their network. AWS charges $0.09 per GB for egress. If your API returns large payloads or you serve lots of images directly from S3 without a CDN, egress charges can be surprisingly high. Put a CDN in front of everything. Cloudflare is free and eliminates most egress costs.
How to Keep Costs Under Control
Use managed platforms as long as possible. Vercel, Supabase, and similar platforms handle scaling, security patches, and infrastructure management. The premium you pay over raw AWS is offset by the engineering time you save not managing servers. Our cloud and DevOps service helps teams find the right balance between managed and self hosted.
Monitor costs weekly, not monthly. Set up billing alerts at 50%, 80%, and 100% of your expected spend. AWS Cost Explorer, GCP Cost Management, and Vercel's usage dashboard all support this. Catching a runaway cost in week 1 is a $100 problem. Catching it in month 3 is a $3,000 problem.
Optimize the database first. 80% of cloud cost optimization comes from 20% of the work, and that 20% is almost always database optimization. Proper indexes, connection pooling, query optimization, and caching. These changes are free to implement and can cut your compute costs by 50% or more.
Budget for 15 to 20% of your cloud bill as optimization work. Every quarter, spend a few days reviewing your infrastructure, shutting down unused resources, right sizing instances, and optimizing the most expensive queries. The ROI on this work is consistently 3x to 5x, you spend $1,000 in engineering time and save $3,000 to $5,000 per year in hosting.
Plan Your Infrastructure Budget
If you want help right sizing your cloud infrastructure or you are staring at a bill that does not make sense, reach out to our team. We will give you an honest assessment of what your product should cost to run.