You’re building a SaaS product solo. AWS or DigitalOcean? Kubernetes or simple VPS? Microservices or monolith?
Here’s what actually works: Pieter Levels runs Photo AI at $132K MRR on a single $40/month DigitalOcean server. 87% profit margins. His $15K monthly infrastructure spend? That’s AI inference via Replicate. The server? Still $40.
The industry assumes you have a team—DevOps engineers, backend specialists, database administrators. Solo founders don’t. You need infrastructure simple enough to maintain alone while shipping features fast enough to stay competitive.
This guide is part of our comprehensive resource on the solo founder model, where we explore how to build profitable SaaS without VC funding. Here we’re going to cover the specific technical decisions that let solo founders operate at scale. Which VPS to choose, when SQLite actually works in production, how to automate deployments with GitHub webhooks, whether to use Replicate or Fal.ai for AI features. Real costs, real implementations, real decision frameworks.
Let’s get into it.
What is the cheapest VPS hosting option for a solo founder SaaS?
DigitalOcean’s basic droplet starts at $40/month. 2GB RAM, 50GB SSD. That’s enough for early-stage SaaS serving 1,000+ users.
Compare that to alternatives: AWS Lightsail runs $40 for equivalent specs, Linode comes in around $36, Hetzner offers the cheapest at $25/month.
But cheap isn’t always best.
DigitalOcean wins on developer experience and documentation. Their pricing is flat and transparent—no reservation tiers, no complex discount structures, no surprise bills at month-end. You forecast costs without spreadsheets.
AWS has more services, sure. But for budget-friendly web apps, DigitalOcean is cheaper and predictable while AWS is more expensive and variable. AWS pricing complexity requires careful calculation. DigitalOcean just tells you the price.
Photo AI runs on a single $40/month DigitalOcean VPS, handling $132K in monthly revenue. The VPS isn’t the bottleneck—not even close.
When should you upgrade? When you hit 5,000+ concurrent users or encounter specific performance bottlenecks. For most solo founders, that’s years away. Start simple, scale when pain dictates.
If you’re cost-obsessed and your users are primarily European, Hetzner at $25/month makes sense. But documentation matters when you’re debugging at 2am alone. DigitalOcean’s guides have saved more solo founders more sleep than the $15/month difference ever will.
How to set up a $40 per month VPS for a SaaS product?
Security hardening starts with SSH key authentication replacing password logins. Then firewall configuration and automatic security updates.
DNS configuration needs an A record for your domain and a wildcard record pointing to your server IP. The wildcard matters for multi-tenant setups or subdomains.
For web servers, Caddy handles TLS certification automatically and redirects HTTP to HTTPS without manual configuration. It’s simpler than Nginx when you don’t want to become a certificate expert.
Monitoring needs to be set up from day one. At minimum you need uptime checks and disk space alerts. Running out of disk space kills databases in ways that are hard to recover from. Email alerts for error log spikes let you catch problems before customers complain.
The final consideration is Infrastructure-as-Code. Terraform lets you define your entire server configuration in version-controlled files. When your server dies at 3am, you want one-command recovery, not six hours of frantic Googling while customers wait.
How does SQLite performance compare to PostgreSQL for production workloads?
A 4 vCPU VPS can handle approximately 180,000 reads/second from SQLite without any special optimisation. That’s not a typo.
SQLite gets a bad reputation. Developers remember the old advice: “SQLite is for development, PostgreSQL is for production.” That advice is outdated. Modern SQLite scales further than most solo SaaS products will ever need.
Photo AI runs SQLite in production handling 1,000+ customers at $132K MRR. User data, sessions, transactions—all of it on SQLite.
The performance difference matters for specific workloads. SQLite excels at simple SELECT queries—it’s actually 35% faster than PostgreSQL for straightforward reads. But PostgreSQL wins on complex JOINs across large datasets, often by 300% or more.
The real limitation is write concurrency. SQLite locks the entire database file for writes. PostgreSQL offers row-level locking. For read-heavy applications serving thousands of users, SQLite works fine. For write-heavy applications with 500+ concurrent writers, PostgreSQL becomes necessary.
When should you migrate? Concrete triggers: database locks lasting over 100ms, queries timing out under normal load, write lock contention appearing in logs, need for full-text search (PostgreSQL has better native support), or adding team members who need concurrent database access during development.
SQLite is easy to deploy, easy to program against, and easy to test. No separate database server to run, no connection pooling to configure, no authentication to secure. The database is a file. Back it up like a file. Deploy it like a file. For detailed PHP and SQLite technical implementation patterns, see our boring stack guide.
For many solo founders, SQLite will outlast their business. Premature optimisation kills more startups than database choice ever will.
How to implement GitHub webhook auto-deploy to production?
Deployment automation lets you push code to GitHub and have it live in production within seconds. Pieter Levels has 37,000+ git commits in 12 months—over 100 deploys per day. He does this by deploying straight to production with no staging environment.
The architecture requires three components: a deployment script on your server, a webhook endpoint to receive GitHub’s POST request, and the GitHub webhook configuration itself.
Your deployment script handles code updates, dependency installation, database migrations, and graceful application restarts. It also needs logging for debugging failed deployments and health check validation after deployment completes.
The webhook endpoint receives GitHub’s POST request and validates the secret token before executing anything. GitHub signs each request with HMAC-SHA256 using your secret. Your endpoint verifies the signature. If it matches, deployment proceeds. If not, reject it. This stops anyone from deploying to your server by simply knowing your webhook URL.
Rollback is simple because it’s git: revert the bad commit, push to GitHub, webhook triggers, deployment runs. You’re back to the previous working state in under a minute.
GitHub Actions offers more sophisticated CI/CD if you need automated testing before deploy, or if you’re deploying to multiple environments. But for solo founders who test locally and ship fast, a simple webhook beats complex CI/CD pipelines.
How to choose between Replicate and Fal.ai for AI inference?
If you’re building AI-powered SaaS, choosing the right AI API hosting infrastructure is critical. Here’s how Replicate and Fal.ai compare.
Fal.ai charges $0.99/hour for A100 GPUs, $1.89/hour for H100s. They use usage-based pricing billed per second, plus output-based pricing for their hosted models.
Replicate pricing is different: $0.0023 per second of GPU time. An 8-second Stable Diffusion XL image generation costs $0.018. At 1,000 images per day, that’s $540/month. At 10,000 images daily, you’re at $5,400/month.
Photo AI spends approximately $15K/month on Replicate at $132K MRR—about 11% of revenue. That’s sustainable for a business with 87% profit margins.
Fal.ai is optimised for fast inference, especially for generative media. They claim 2.1 second average cold starts compared to Replicate’s 4.5 seconds. For user-facing applications where every second of wait time increases abandonment, that matters.
The decision framework: under 100 requests per day, Replicate’s per-second billing is cheaper. At 1,000+ requests per day, Fal.ai’s predictable per-request pricing becomes attractive. Need model variety? Replicate has 50,000+ community models. Need speed? Fal.ai’s 2x faster cold starts improve user experience.
Neither creates vendor lock-in. Both use standard model formats. If costs explode, migration to self-hosted RunPod is possible, though it adds operational complexity.
Within 3 to 6 months of deployment, most teams find that inference has overtaken training as the dominant cost driver. Budget accordingly. Your AI costs will grow faster than your server costs.
Self-hosting becomes viable when AI costs hit 15-20% of revenue. At 11% of revenue, the operational complexity of managing GPUs, scaling infrastructure, and handling model updates costs more in founder time than Replicate charges in dollars.
How to integrate Stripe payments as a solo developer?
Stripe charges 2.9% + $0.30 per card payment in the US. It’s used by solo founders at $132K MRR and by companies at billions in revenue. The integration complexity is the same either way.
Your integration choice matters. Stripe Checkout provides a hosted payment page—the fastest path to accepting money. You redirect users to Stripe’s interface, they pay, Stripe redirects them back. You write almost no payment code.
Stripe Elements gives you control over the payment UI while staying on your domain. More work to implement, better user experience, identical security since Stripe still handles the card data.
For solo founders, start with Checkout. You can always migrate to Elements later when the design matters.
The customer portal is what makes Stripe work for solo operations. It lets users update payment methods, cancel subscriptions, and view invoices without contacting you. Every self-service feature is one less support email.
Webhooks handle the asynchronous nature of payments. Payment succeeds? You get payment_intent.succeeded. Subscription cancelled? You get subscription.deleted. Payment failed? You get invoice.payment_failed.
Webhook security matters. Stripe signs each webhook with HMAC-SHA256. Verify the signature before processing any events. Replay attacks can compromise security without proper verification.
Testing requires zero money. Stripe test mode provides test card numbers for every scenario: successful payments, declined cards, authentication required, invalid CVV, expired cards. Test every edge case before going live.
Stripe’s documentation is excellent. When you’re stuck at 2am implementing payment logic, their guides will save you.
How to handle customer support solo at 1,000+ users?
The foundation is a knowledge base that answers the obvious questions. Getting started guides, common issues, account management, billing explanations. Write once, reference forever. A good knowledge base deflects 60-70% of potential support requests.
Email automation handles the rest. Stripe webhooks trigger automated emails for payment events. Payment failed? Send an email explaining why with a link to update the card. Subscription upgraded? Send a confirmation with a feature guide.
Live chat feels responsive but kills productivity for solo founders. You’re constantly interrupted. Email-based support lets you batch responses into a single daily session. Set expectations: 24-hour response time. Then beat it.
Build a template library for common questions. Maintain 15-20 pre-written responses covering frequent issues, with merge fields for personalisation. You’re not copying and pasting identical emails—you’re starting from 80% complete and customising the final 20%.
Prioritise ruthlessly. Payment issues get immediate attention—they’re blocking revenue. Feature requests get batched for weekly review. Bug reports get prioritised by severity and user count affected.
Use customer data to personalise onboarding. Email domain, project name, and full name enable AI-powered background research during signup. Show new users what people like them find valuable.
The tools don’t matter as much as the system. Email works fine. Intercom and Zendesk add capabilities but also maintenance overhead. For solo founders, simple beats sophisticated until you’re drowning in tickets.
Support is product research. Get login access and review incoming tickets regularly. Customers are always a reality reservoir when companies exert powerful reality distortion fields. Your support inbox tells you what’s actually broken.
What are the real infrastructure costs at $100K MRR for a solo founder?
Photo AI at $132K MRR has total infrastructure costs of approximately $15K/month. The breakdown: $15,000 Replicate API, $40 DigitalOcean VPS, $1,000 miscellaneous services.
That’s an 87% profit margin. $132K revenue minus $15K costs equals $117K monthly profit for a solo founder with zero employees. For complete infrastructure cost benchmarks by revenue level, see our detailed financial analysis.
The entire operation runs on a single $40/month server. The VPS isn’t the cost driver—AI inference is. That’s typical for AI-powered SaaS products.
Cost evolution as you scale: at launch expect $40/month VPS and maybe $100/month in AI credits. At $10K MRR it’s $40/month VPS and $1,000-1,500/month AI inference. At $50K MRR it’s $40/month VPS and $5,000-8,000/month AI inference. At $100K MRR it’s $40/month VPS and $12,000-15,000/month AI inference.
The pattern is clear. VPS hosting stays flat until you hit performance bottlenecks. AI costs scale with usage. Other services like monitoring, email, and backups add up to $1,000-2,000/month at scale.
Traditional SaaS products spend 15-25% of revenue on infrastructure. Solo founders achieve 10-13% through radical simplification and managed services. Pieter Levels makes $3 million per year with zero employees across multiple products. The infrastructure strategy scales across his portfolio.
Compare profit margins: solo founders at 60-87% versus typical VC-funded SaaS at 20-30%. The difference is payroll. No team means no salaries, no benefits, no office, no HR overhead. Infrastructure costs don’t change much with employee count. People costs dominate. This infrastructure efficiency is a core component of solo founder fundamentals.
Cost reduction opportunities emerge at scale. Migrating high-volume AI inference from Replicate to self-hosted RunPod can save 40-60%. But that adds operational complexity—GPU management, scaling logic, model deployment pipelines. The savings need to justify the maintenance burden.
FAQ Section
What tech stack do successful solo founders use for their SaaS products?
Pieter Levels uses vanilla PHP, HTML, CSS, jQuery, SQLite, and simple VPS servers. No React, no Next.js, no Docker, no Kubernetes. His reasoning: he knows it well, it’s simple to maintain alone, fast to build and deploy, scales fine for his needs, no dependency hell.
This is what we call the boring stack advantage. It prioritises maintainability and shipping velocity over architectural trends. Django for Python, Laravel for PHP, and Rails for Ruby offer similar batteries-included philosophies for solo developers.
Can SQLite handle thousands of users in production?
Yes. SQLite works well for read-heavy applications serving 10,000+ daily active users. A 4 vCPU VPS handles approximately 180,000 reads/second without special optimisation.
Write-heavy applications hit concurrency limits around 500-1,000 concurrent writers. Migrate to PostgreSQL when experiencing write lock contention, needing full-text search, or requiring complex analytical queries.
For most solo SaaS products serving thousands of users, that day never comes.
Should I use Replicate or build my own AI infrastructure?
Use Replicate until AI costs exceed 15-20% of revenue. Self-hosted RunPod becomes cost-effective above 50,000 AI requests per day but adds operational complexity for solo founders.
The savings in hosting costs get eaten by the time spent maintaining GPU infrastructure. At 11% of revenue on managed services, the maths favours simplicity over optimisation.
How much does it really cost to run a SaaS at $100K MRR?
Infrastructure typically costs 10-13% of revenue for solo founders at this scale. The breakdown varies by product type: AI-powered products spend heavily on inference ($12K-15K/month), traditional SaaS products stay closer to $3K-5K/month. The VPS stays around $40/month either way.
Additional costs for monitoring, email services, and backups add $1K-2K/month. Traditional SaaS spends 15-25% of revenue on infrastructure. Solo founders achieve better margins through aggressive simplification and managed service leverage.
DigitalOcean vs AWS for solo founder hosting?
DigitalOcean offers predictable pricing, excellent documentation, and simpler APIs for solo founders. AWS provides more services but complex pricing that often surprises solo developers.
Choose DigitalOcean for simplicity until needing AWS-specific services like Lambda, DynamoDB, or complex multi-region requirements. Most solo founders never need those capabilities.
What is the typical profit margin for solo founder SaaS at scale?
Typical solo founder SaaS operates at 60-80% margins. The highest optimised examples achieve 87% through infrastructure efficiency and aggressive automation.
VC-funded SaaS with teams typically sees 20-30% margins. The solo advantage compounds through eliminated payroll costs and infrastructure efficiency. No salaries, no benefits, no office lease. Just hosting and tools.
When should I migrate from SQLite to PostgreSQL?
The migration decision depends on specific performance triggers: database locks lasting over 100ms, queries timing out under normal load, write lock contention appearing in logs, or team growth requiring concurrent development.
Typical triggers occur at 500-1,000 concurrent writers for write-heavy applications. Read-heavy applications can run SQLite far longer.
Consider the migration when PostgreSQL’s specific features (full-text search, complex analytical queries) become necessary for your product.
How to set up GitHub webhook auto-deploy with rollback safety?
The webhook architecture requires three components: a server-side deployment script, an endpoint to receive GitHub’s POST requests, and signature validation for security.
The deployment script handles code pulls, dependency updates, and application restarts with health check validation. Security comes from HMAC-SHA256 signature verification on every webhook. Rollback uses git revert to previous commit plus automatic redeployment.
The simplicity of this approach beats complex CI/CD pipelines for solo founders shipping frequently.
What hosting should I use for my solo SaaS startup?
Start with DigitalOcean’s $40/month basic droplet. It’s sufficient for 1,000+ users.
Enable automatic backups, set up Infrastructure-as-Code with Terraform for disaster recovery, and scale when hitting 5,000+ concurrent users.
Alternative: Hetzner at $25/month for lower costs with European datacentres, but DigitalOcean’s documentation and community support justify the extra $15/month.
Steps to migrate from SQLite to PostgreSQL without downtime?
The migration approach involves running both databases temporarily while validating consistency.
You set up PostgreSQL alongside your existing SQLite database, export and import your data with schema validation, then configure your application to write to both systems. Once you’ve verified data consistency, you switch read traffic to PostgreSQL gradually.
After monitoring performance for a few days, you remove the SQLite writes and keep a backup for emergency rollback. The key is validation at each stage before committing to the switch.
What is Infrastructure-as-Code and why do solo founders need it?
Infrastructure-as-Code with Terraform defines server configuration in version-controlled files enabling one-command infrastructure rebuild after system failure.
For solo founders lacking DevOps teams, it means disaster recovery in hours instead of days, consistent staging environments, documented infrastructure decisions, and easy environment cloning for testing.
When your server dies at 3am, Terraform gets you back online before customers notice.
How much does Replicate API cost for AI features in production?
Replicate charges $0.0023 per second of GPU time. Stable Diffusion XL image generation averages 8 seconds equalling $0.018 per image.
At 1,000 images per day that’s $540/month. At 10,000 images daily you’re at $5,400/month.
Budget 10-15% of projected revenue for AI costs at scale. The costs scale linearly with usage, making them predictable but potentially expensive as you grow.
