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UID:pretalx-foss4g-europe-2026-VLTRPL@talks.osgeo.org
DTSTART;TZID=EET:20260629T153000
DTEND;TZID=EET:20260629T160000
DESCRIPTION:Building a production-grade WMTS for satellite imagery sounds s
 traightforward—until you hit cloud-native reality. This talk charts UP42
 ’s journey from a 2024 hackathon to a live beta service\, exposing the h
 ard lessons learned while delivering STAC-catalogued imagery to profession
 al GIS tools at scale.\n\nThe Architecture Battle\nWhy GeoServer? While co
 mmercial options were cost-prohibitive and emerging tools like TiTiler lac
 ked maturity\, GeoServer offered OGC-compliance and a proven REST API. How
 ever\, "standard" setups quickly crumbled under B2B demands. We’ll dive 
 into:\n\nThe FUSE Trap\nHow GCP Cloud Storage FUSE crippled tile-seeding p
 erformance\, and why we pivoted to native GCP BlobStore plugins to unlock 
 massive throughput.\n\nThe Scaling Wall\nWhy vanilla GeoServer’s cluster
 ing failed us\, necessitating a strategic (and bumpy) migration to GeoServ
 er Cloud’s microservices architecture.\n\nThe Integration Tax\nReal-worl
 d troubleshooting of Helmfile fixes\, CSI driver misconfigurations\, and t
 he "silent" bugs that haunt cloud-native geospatial stacks.\n\nHard-Earned
  Takeaways\nWe’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 mach
 ine" to "it works for the world."
DTSTAMP:20260604T223452Z
LOCATION:A02
SUMMARY:Scaling the Sky: From Hackathon to Production on scale with GeoServ
 er Cloud - Matheus Pinheiro dos Santos\, Jeremiah Dominguez Gorrin
URL:https://talks.osgeo.org/foss4g-europe-2026/talk/VLTRPL/
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UID:pretalx-foss4g-europe-2026-MLDRHM@talks.osgeo.org
DTSTART;TZID=EET:20260630T153000
DTEND;TZID=EET:20260630T160000
DESCRIPTION:For any geospatial platform\, the ability to serve imagery at s
 cale is the ultimate "stress test." When our team at UP42 began building a
  production-grade WMTS service\, we quickly realized that moving from a fu
 nctional setup to a high-performance one requires more than just adding mo
 re hardware. This talk shares our iterative journey of migrating from a "V
 anilla" GeoServer architecture to a microservices-based GeoServer Cloud en
 vironment\, and the systematic load testing that guided every decision alo
 ng the way.\n\nWe will walk through our "detective-style" approach to perf
 ormance tuning. Using Apache JMeter to simulate heavy production loads\, w
 e treated our infrastructure as a series of integration points where bottl
 enecks could hide. Rather than a smooth transition\, the move to a cloud-n
 ative architecture revealed a new landscape of challenges that required us
  to look deeper into the system than we had ever anticipated.\n\nThroughou
 t our testing phases\, we uncovered a variety of hidden performance killer
 s\, including:\n- Storage Hurdles: How standard cloud-mount solutions stru
 ggled with tile-writing workloads and why native cloud storage plugins bec
 ame essential.\n- Concurrency Caps: The realization that default configura
 tions for thread limits and traffic control are often too conservative for
  modern cloud environments.\n- The Proxy Trap: How internal communication 
 between services can become a bottleneck even when individual components a
 re performing well.\n- Resource Optimization: The relationship between CPU
 /Memory allocation and the ability to handle parallel tasks like simultane
 ous seeding and streaming.\n\nThis presentation is a practical guide for a
 nyone looking to push GeoServer beyond its default limits. We will share o
 ur "battle map" for isolating bottlenecks\, bypassing load balancers for d
 iagnostic testing\, and the critical importance of keeping load testing co
 ntinuous as your architecture evolves.\n\nKey Takeaways\n- The Migration R
 eality: GeoServer Cloud offers the foundation for horizontal scaling\, but
  it requires a specialized tuning strategy compared to standalone instance
 s.\n- Systematic Isolation: Learn how to test individual microservices (GW
 C\, Gateway\, etc.) in isolation to pinpoint exactly where latency is intr
 oduced.\n- Visibility Matters: The importance of combining log analysis\, 
 thread dumps\, and performance metrics to solve "silent" performance issue
 s.\n- End-to-End Testing: Why you must test the full integration path earl
 y to find bottlenecks that only appear under high concurrency.
DTSTAMP:20260604T223452Z
LOCATION:A12
SUMMARY:Scaling GeoServer: From Vanilla Architecture to Cloud Performance O
 ptimization - Jan Christian\, Matheus Pinheiro dos Santos
URL:https://talks.osgeo.org/foss4g-europe-2026/talk/MLDRHM/
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