Most data engineering and geospatial projects follow a predictable infrastructure blueprint: an ingestion cron job, an enterprise database (like PostGIS), a hosted API layer, a dynamic tile server, and a frontend client. Before you write a single line of business logic, your cloud architectural diagram already carries a fixed monthly overhead.
For Village Finder an open-source interactive mapping application tracking over 78,000 Indian villages, live market rates, and land records I have decided to reject the traditional stack.
Instead, I applied core DevOps, GitOps, and DataOps principles to build an entirely serverless, self-updating data platform. The operational infrastructure bill? Exactly $0.
Here is the architectural blueprint of how I shifted left on geospatial data infrastructure.
The foundational principle of GitOps is that Git is the single source of truth. If your infrastructure states can live in a declarative YAML file, your application data can too.
