🌐 Choosing the Right Hosting for Your Code: VPS vs Cloud vs Alternatives

TL;DR: For production Python applications that need to run 24/7, VPS with systemd is the sweet spot combining cost-effectiveness with full control. For learning and prototyping, free options like GitHub Actions work great. We’ve considered different options for persistent [Python] code run.

As a spoiler we share here a hidden table with results

Feature	VPS 🎉🎉🎉	Cloud Alternatives
Cost	$0 (already paid for)	Free tiers often limited
Uptime	24/7 persistent	Cloud free tiers time out
Control	Full root access	Restricted environments
Security	Your own network/firewall	Shared infrastructure
No surprises	No rate limits	Clouds throttle free tier
Setup time	5 minutes	Varies (often complex)

What Are Your Hosting Options?

When it comes to running Python applications, you have several hosting choices, each with different trade-offs between cost, control, and convenience. Let’s break them down:

🚀 Free/Low-Cost Options

GitHub Actions/Workflows

Pros	Cons	Best For
✅ Completely free ✅ Powerful compute resources ✅ Built-in CI/CD	❌ Time-limited runs (6h max) ❌ Not always-on ❌ No persistent storage	Cron jobs, batch processing, scheduled tasks

Heroku (Free Tier)

Pros	Cons	Best For
✅ Easy deployment with Git ✅ Always-on (with limitations) ✅ Free SSL certificates	❌ Sleeps after 30 minutes ❌ Limited resources (512MB RAM) ❌ Free tier expires	Simple web apps, prototypes, learning

PythonAnywhere

Pros	Cons	Best For
✅ Python-focused environment ✅ Built-in web editor ✅ Pre-installed packages	❌ Limited free tier ❌ Bandwidth restrictions ❌ Less control over environment	Learning Python, small projects, education

💻 VPS Solutions

DigitalOcean, Vultr, Hetzner

Pros	Cons	Best For
✅ Full system control ✅ Cost-effective ($5-20/month) ✅ Always-on 24/7	❌ Requires sysadmin knowledge ❌ Manual setup required ❌ Security management needed	Production apps, learning Linux, custom setups

AWS EC2 (Free Tier)

Pros	Cons	Best For
✅ Enterprise-grade infrastructure ✅ Free for 12 months ✅ Scalable resources	❌ Complex pricing structure ❌ Free tier expires ❌ Steep learning curve	Learning AWS, small production apps, enterprise

☁️ Managed Cloud Platforms

Google Cloud Run, AWS Lambda

Pros	Cons	Best For
✅ Auto-scaling ✅ Pay-per-use pricing ✅ Zero server management	❌ Cold start delays ❌ Vendor lock-in ❌ Complex for simple tasks	Microservices, event-driven apps, scalable services

Railway, Render

Pros	Cons	Best For
✅ Modern deployment experience ✅ Easy CI/CD integration ✅ Good developer experience	❌ More expensive than VPS ❌ Less control over infrastructure ❌ Limited customization	Startups, teams, rapid prototyping

📊 Comparison Matrix

Platform	Cost	Control	Always-On	Learning Curve
GitHub Actions	Free	Low	No	Easy
Heroku Free	Free	Low	Limited	Easy
PythonAnywhere	Free-$	Medium	Yes	Easy
VPS	$5-20/mo	High	Yes	Medium
AWS EC2	$0-50/mo	High	Yes	Hard
Cloud Run	$0-100/mo	Medium	Yes	Medium

🎯 Recommendations by Use Case

👨‍🎓 Learning & Education

• Start with: GitHub Actions + PythonAnywhere
• Why: Free, no setup required, great for learning

🧪 Prototyping & MVPs

• Start with: Heroku + Replit
• Why: Quick deployment, focus on code, not infrastructure

🏭 Production Applications

• Start with: VPS + Systemd (our detailed guide)
• Why: Full control, cost-effective, reliable 24/7 operation

🏢 Enterprise & Scale

• Start with: AWS/GCP + Managed Services
• Why: Auto-scaling, enterprise features, team collaboration

🏆 Why VPS Wins for Always-On Services

VPS is the sweet spot for [Python] daemons because it offers:

• ✅ Full control over system resources
• ✅ No time limits or sleep policies
• ✅ Cost-effective ($5-10/month for reliable service)
• ✅ Perfect for systemd daemon setup
• ✅ Learning Linux system administration

For our detailed guide on setting up Python daemons on VPS with systemd, check out our complete tutorial.

Key Problems with Cloud for Daemons:

1. Forced Sleep/Timeout: All free tiers stop your process after minutes/hours.
2. No True Background Processes: Clouds assume stateless HTTP requests.
3. Cold Starts: Your code restarts from scratch on every request (slow!).
4. Hidden Costs: Free tiers often exclude databases, storage, or network egress.

🚫 Critical Warning: Trying to hack around this (e.g., pinging your Cloud Run app hourly to keep it awake) violates ToS and gets your account banned.

💡 When to Consider Cloud (Rare Cases)

Only if:

• You need global scalability (millions of users)
• You require managed databases (e.g., AWS RDS)
• Your VPS is underpowered for the task
• You’re building a public-facing API (use Cloud Run + Cloud Scheduler ping)

For 95% of personal projects, your VPS is superior. Cloud free tiers are marketing traps for persistent services.

📊 Cost Comparison (1 Year)

Solution	Cost	Uptime	Setup Effort	Best For
Your VPS	$0	99.9%+	Low (5 min)	Daemons, long-running apps
Google Cloud Run	$5/mo*	95%	Medium	HTTP APIs (with sleep)
AWS EC2 T4g.nano	$3.50/mo	99.5%	High	Full VM control (paid)
GitHub Actions	$0	0%	Medium	CI/CD only (not daemons)

💡 Key Takeaways

• Free options are great for learning and scheduled tasks
• VPS offers the best balance of cost, control, and reliability
• Managed cloud is ideal for scaling and enterprise needs
• Choose based on your current needs, not future dreams
• Start simple and migrate as your needs grow

🚀 Next Steps

Ready to deploy your Python application on a VPS? Check out our comprehensive guide on setting up Python daemons with systemd for production-ready deployments.