BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-europe-2025//talk//7H7P3 8 BEGIN:VTIMEZONE TZID:CET BEGIN:STANDARD DTSTART:20001029T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-europe-2025-7H7P38@talks.staging.osgeo.org DTSTART;TZID=CET:20250716T170000 DTEND;TZID=CET:20250716T170500 DESCRIPTION:Traditional Geographic Information Systems (GIS) are often deve loped as monolithic software. This project presents a case study that expl ores the development of geospatial software using microservices and contai nerization\, focusing on core modular elements such as images\, containers \, and service orchestration. The use case involves serving geospatial dat a related to radiological measurement data for routine monitoring and emer gency response scenarios. The implementation is fully open-source and incl udes the following technologies: Docker\, PostgreSQL/PostGIS\, GeoServer\, Node.js\, and OpenLayers. The primary aim is to share practical insights into modular software development and provide a streamlined guide for rapi dly building lean\, portable and maintainable geospatial applications.\n\n Background and Motivation\n\nMonolithic software development poses numerou s limitations compared to component-based approaches. In the proposed arch itecture\, all key GIS components - data storage\, management\, and visual ization - are modularized and isolated into independent services. Each ser vice is encapsulated within its own Docker container\, simplifying deploym ent and ongoing maintenance. This isolation enables independent developmen t of each component\, provided that the interfaces (e.g.\, APIs) remain co nsistent.\n\nFor example\, by fully integrating a relational database mana gement system (RDBMS) such as PostgreSQL/PostGIS\, GIS applications can de legate core functions—including user and role management\, query optimiz ation\, data storage and retrieval\, and backup and recovery—to the data base layer. This eliminates the need to build such functionality from scra tch\, promoting a concept known as decoupling. Decoupling is central to ti ered software architectures as it minimizes interdependencies\, improves f lexibility and enables autonomous development across components.\n\nMicros ervices and Containerization in GIS\n\nThe architecture presented in this study organizes components like data storage and visualization into a mult i-service environment using Docker. Docker provides an ecosystem that enca psulates the operating system and all required dependencies\, enabling OS- level and software-level virtualization (Acharya et al.\, 2021). Key benef its of this approach include:\n• Portability - containers encapsulate al l required libraries\, dependencies\, software and configurations.\n• Ef ficiency - containers use fewer resources than VMs or server infrastructur es. They also have a positive effect on human resources because they lesse n dependencies between developers.\n• Scalability - supports both horizo ntal and vertical scaling.\n• Isolation - containers are self-contained and reduce the risk of conflicts.\n• Continuous integration - testing an d production environments can be identical\, accelerating development cycl es.\n• Clear ownership - containers have well-defined boundaries\, which prevents individuals from interfering with each other’s work and thereb y improving efficiency.\n• Interoperability - containers and services ca n easily be consumed with no special needs in terms of operating system or software.\n\nThe project implements a 4-tier container orchestration to v isualize the geodata\, PostgreSQL/Postgis for data storage\, pgAdmin as Po stgres’ graphical user interface (GUI)\, Geoserver as a web map server a nd Node.js for client dependencies such as OpenLayers. \n\nComponents can be individually configured and tailored. In a containerized environment\, services are defined as images and deployed as containers. These can be di stributed and executed independently of the host system's configuration. F or example\, deploying a traditional web-based GIS requires manually insta lling and configuring a database (e.g.\, PostgreSQL)\, a web map server (e .g.\, GeoServer)\, and a frontend visualization library (e.g.\, OpenLayers or Leaflet). This process must be repeated for each redundant server to a chieve fault tolerance or switchover capabilities - an inefficient and err or-prone approach.\n\nBy contrast\, containerization allows each component to be defined in configuration files (e.g.\, docker-compose.yml) alongsid e accompanying text files for credentials and settings. The result is a st reamlined and reproducible environment where services interact through wel l-defined interfaces. Containerization enables full-stack development of s ervice-oriented architectures (SOA)\, simplifying workflows needed for red undancy\, fault tolerance and system maintenance. Modularization also faci litates all key tasks across the GIS stack - from data ingestion and analy sis to visualization.\n\nBy isolating each functional component - data ing estion\, storage\, service and visualization into independent Docker conta iners\, the system achieves modularity\, scalability\, and ease of mainten ance. The use of open-source tools like PostgreSQL/ PostGIS\, GeoServer\, and OpenLayers ensures adaptability to a wide range of GIS use cases. This architecture not only simplifies development and deployment but also prov ides a robust foundation for building more complex geospatial systems that support advanced spatial analytics and statistics or elaborate data pipel ines.\n\nReal-World Application: Radiological Emergency Preparedness\n\nTh e application showcases how radiological measurement data can be deployed for various tasks from routine monitoring to emergency response. The Feder al German Office for Radiation Protection (Bundesamt für Strahlenschutz) is responsible for detecting\, assessing\, and reacting to nuclear and rad iological events. It collaborates with European member states and internat ional agencies (e.g.\, Euratom\, IAEA). In an emergency\, it must rapidly collect\, analyze\, and distribute information while proposing protective measures to reduce the impact of nuclear fallout.\n\nScalability is critic al\, as emergency situations often trigger surges in web traffic. The agen cy has prioritized container-based\, component-driven software architectur es for nearly a decade\, yielding significant improvements in continuous i ntegration and deployment (CI/CD)\, scalability\, maintainability\, portab ility\, resilience (e.g.\, service recovery) and overall performance. DTSTAMP:20260527T195034Z LOCATION:PA01 (Quarticle) SUMMARY:Honey\, I shrunk the GIS – Developing scalable and lightweight ge ospatial software applications with microservices and containerization - A rne Schumacher URL:https://talks.staging.osgeo.org/foss4g-europe-2025/talk/7H7P38/ END:VEVENT END:VCALENDAR