{"slug": "building-aquastat-why-we-started-tracking-data-center-water-usage", "title": "Building AquaStat: Why We Started Tracking Data Center Water Usage", "summary": "A developer built AquaStat, an API-first platform for collecting and analyzing data center water usage data. The project aims to organize scattered information from sustainability reports, government documents, and local sources into a usable resource for developers, researchers, and journalists. AquaStat emphasizes data quality, source attribution, and transparent methodology.", "body_md": "When people think about data centers, they usually think about servers, GPUs, electricity, and AI.\n\nVery few people think about water.\n\nThat realization is what led me to start building **AquaStat**.\n\nModern data centers consume significant amounts of water for cooling. Depending on the technology, climate, and workload, water usage can vary dramatically from one facility to another.\n\nFinding reliable information about that usage, however, is often difficult.\n\nSome facilities voluntarily publish sustainability reports. Others release only limited information. In many cases, information is scattered across government documents, environmental reports, local news articles, permits, or community discussions.\n\nI wanted to build a platform that could organize this information into something developers, researchers, journalists, and the public could actually use.\n\nAquaStat is an API-first platform focused on collecting, organizing, and analyzing information related to data center water usage.\n\nThe long-term vision includes:\n\nRather than hiding calculations, I want AquaStat to explain where information comes from and how conclusions are reached whenever possible.\n\nI'm designing AquaStat around several principles:\n\nEverything should be accessible through documented APIs before being exposed through a graphical interface.\n\nDocumentation should be treated as part of the product, not an afterthought.\n\nWhenever AquaStat estimates or derives values, the methodology should be understandable and repeatable.\n\nThe project uses a modern TypeScript stack with an emphasis on maintainability, testing, and developer experience.\n\nOne of the biggest technical challenges isn't writing the API itself.\n\nIt's data quality.\n\nPublic information comes from many different sources:\n\nThose sources often disagree with each other.\n\nOne of the goals of AquaStat is to preserve source attribution instead of pretending every number is perfectly known.\n\nWhen information cannot be verified, it should be identified as uncertain rather than presented as fact.\n\nThis project has already pushed me to learn more about:\n\nIt's also reinforced how important good documentation and clear system design are when projects begin to grow.\n\nThe roadmap currently focuses on:\n\nAquaStat is still evolving and actively being worked on, but I'm excited to continue building it in public.\n\nI'll be writing more about the architecture, technical decisions, lessons learned, and challenges along the way.\n\nIf you're interested in APIs, developer tooling, environmental technology, or open-source software, I'd love to hear your feedback and ideas.", "url": "https://wpnews.pro/news/building-aquastat-why-we-started-tracking-data-center-water-usage", "canonical_source": "https://dev.to/magnexis/building-aquastat-why-we-started-tracking-data-center-water-usage-d43", "published_at": "2026-07-16 15:38:28+00:00", "updated_at": "2026-07-16 16:08:32.079578+00:00", "lang": "en", "topics": ["developer-tools", "ai-infrastructure"], "entities": ["AquaStat"], "alternates": {"html": "https://wpnews.pro/news/building-aquastat-why-we-started-tracking-data-center-water-usage", "markdown": "https://wpnews.pro/news/building-aquastat-why-we-started-tracking-data-center-water-usage.md", "text": "https://wpnews.pro/news/building-aquastat-why-we-started-tracking-data-center-water-usage.txt", "jsonld": "https://wpnews.pro/news/building-aquastat-why-we-started-tracking-data-center-water-usage.jsonld"}}