When building a SaaS, automations, or a simple AI-powered tool, choosing the right backend can make or break your product’s reliability.
While many developers default to building custom APIs, non-coders have powerful no-code platforms like Make as an alternative.
However, a critical question remains:
Is Make actually reliable as a production backend when used by too many users?
To find out, I built a real-world marketing automation in Make and stress-tested it with increasingly aggressive loads: 50, 100, 200, 500, and finally 1000 calls per minute. The automation mimics a realistic SaaS use case, where it processes YouTube video content to generate personalized marketing emails using AI.
Why This Matters
Before moving on to the technical details, I would like to mention why this matters for your next project. When you’re building a SaaS or automation tool, you have three main backend options:
- Custom API Development: Full control, but takes a lot of time to develop
- Serverless Functions: Fast setup, but complex at scale
- No-Code Automation Platforms: Rapid deployment, but unknown reliability
For rapid MVP development, automation platforms like Make offer an unbeatable time-to-market advantage. But only if they can handle real user loads without breaking.