2026-06-29 –, A02
Building a production-grade WMTS for satellite imagery sounds straightforward—until you hit cloud-native reality. This talk charts UP42’s journey from a 2024 hackathon to a live beta service, exposing the hard lessons learned while delivering STAC-catalogued imagery to professional GIS tools at scale.
The Architecture Battle
Why GeoServer? While commercial options were cost-prohibitive and emerging tools like TiTiler lacked maturity, GeoServer offered OGC-compliance and a proven REST API. However, "standard" setups quickly crumbled under B2B demands. We’ll dive into:
The FUSE Trap
How GCP Cloud Storage FUSE crippled tile-seeding performance, and why we pivoted to native GCP BlobStore plugins to unlock massive throughput.
The Scaling Wall
Why vanilla GeoServer’s clustering failed us, necessitating a strategic (and bumpy) migration to GeoServer Cloud’s microservices architecture.
The Integration Tax
Real-world troubleshooting of Helmfile fixes, CSI driver misconfigurations, and the "silent" bugs that haunt cloud-native geospatial stacks.
Hard-Earned Takeaways
We’re sharing our internal RFCs and benchmarks so you don’t have to learn the hard way. Learn why you must evaluate plugin maturity over hype, why FUSE is a bottleneck for tile writes, and why continuous load testing is the only way to survive the jump from "it works on my machine" to "it works for the world."
Senior Software Engineer with 10+ years of experience, including the last three at UP42 scaling cloud-native geospatial systems. Expert in Java, Kubernetes, and microservices, I specialize in OGC-compliant services and high-concurrency WMTS architectures. I focus on bridging the gap between complex spatial processing algorithms and robust, production-ready cloud infrastructure to ensure reliability and performance at scale.
Jeremiah Domingues Gorrin | Senior Backend Engineer, UP42
I am a Senior Backend Engineer at UP42, based in Berlin, where I build the cloud-native infrastructure that turns complex Earth observation data into accessible, actionable insights. UP42 is a leading geospatial developer platform that simplifies the way organizations access and analyze satellite imagery, providing a unified ecosystem for data, processing, and scaling geospatial products.
As a member of the Processing Team, I focus on the "engine room" of the platform. My work involves architecting the backend systems responsible for managing and storing terabytes of geospatial assets, primarily in STAC (SpatioTemporal Asset Catalog) and COG (Cloud Optimized GeoTIFF) formats. By ensuring this data is indexed, stored, and highly available, I help provide the foundation for our users to perform advanced analytics without the typical infrastructure overhead.
A major part of my current focus is building our production-grade WMTS (Web Map Tile Service) using GeoServer. Operating in a Kubernetes environment, I’m tackling the unique challenges of scaling GeoServer Cloud to deliver seamless, high-speed imagery streaming to professional GIS tools. In tandem, I develop the systems that power our processing engine, which allows users to trigger heavy-duty geospatial jobs—such as orthorectification and upsampling—directly on their stored assets.
My technical toolkit is built on Kotlin, Java, and Python, leveraging both GCP and AWS to maintain a resilient, multi-cloud infrastructure. I am passionate about the intersection of software engineering and geospatial science—solving the "unseen" bottlenecks in data throughput and compute orchestration so that our users can focus on solving global challenges.
Ultimately, I see my role as the bridge between raw geospatial storage and production-ready intelligence. Whether I’m optimizing a GeoServer cluster or streamlining a processing job workflow, my goal is to ensure that the view from above is always just an API call away.