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Introduction

Early Release

Welcome to Building Serverless Geospatial Apps on AWS. Geospatial systems are not a natural fit for serverless architectures. Their underlying data models — large rasters, complex geometries, and spatial indexes — clash with the event-driven, stateless patterns that make serverless systems effective. As a result, building scalable geospatial applications has often meant falling back on traditional infrastructure, missing the advantages of serverless approaches.

This guide is an experimental resource developed to address that gap. It collects patterns observed and tested in production, showing how serverless technologies can be applied to geospatial problems in practice. The focus is on reusable, adaptable solutions built with AWS services and open-source tools, offering a foundation for developers who want to combine modern cloud architectures with geospatial workloads.

A central idea is that the choice of data model is as important as the choice of technology. Geographic data can be restructured to align with serverless patterns: large spatial files stored in an object store, tiled or indexed features mapped to key-value stores, or normalised geometries persisted in relational databases. Each model makes different trade-offs, but restructuring the data is what enables scalability. By adapting the data model — rather than the platform — cloud-native patterns can be applied effectively to geospatial problems.

Cloud Native

The guide presents practical architecture patterns for developers building geospatial solutions on AWS. Each pattern includes:

  • A short description
  • When to use it (and trade-offs)
  • An architecture diagram
  • Links to examples and further resources

The patterns presented here are grounded in production experience and refined through developing geospatial architectures at scale. They are also inspired by ideas shared within the FOSS4G community, with references to relevant talks and repositories included throughout. This guide offers a set of practical building blocks for developers to adapt to their own needs.

About

Tomas Holderness is a Geographer and Technologist, and CTO at Addresscloud where he leads product, engineering and data teams building geospatial solutions for insurance.

© Tomas Holderness 2025. All rights reserved.