A Log Analysis SaaS Built in 30 Days That Hit $1,287 MRR With 41 Paying Customers

The Strategy

Production incidents at 2 AM are already stressful enough without having to manually parse thousands of log lines to figure out what went wrong. Most developers have experienced the frustration of scrolling through endless error output trying to piece together a timeline of failures. Existing log management tools are powerful but complex, and none of them focus specifically on turning raw chaos into a quick, readable incident summary. StackTrace was built in 30 days to solve exactly this problem. Gian Soriano created a SaaS that accepts raw production logs, parses them structurally, applies AI tagging using the OpenAI API, and generates concise summaries that highlight what failed, where it failed, why it failed, and the probable root cause. The output is designed to be readable by an on call engineer at 2 AM without needing to understand the full log context. The tech stack combines Next.js 14 and TailwindCSS on the frontend, deployed on Vercel, with a Node.js and Express backend running on Railway. PostgreSQL handles primary data storage, Redis manages caching and job queues, and Supabase provides additional data layer support. Authentication runs through Clerk and billing through Stripe, keeping the SaaS infrastructure straightforward. The 30 day results speak clearly: 312 total signups, 41 paying customers, and $1,287 in monthly recurring revenue. The 13% signup to paid conversion rate is notably strong for a developer tool, and the 1.9% churn rate across those first 30 days suggests the product delivers enough value that early adopters stick around.

How It Works

Results