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Gemini Executive Synthesis

Artemis.fyi, a real-time tracker for the Artemis II Moon mission.

Technical Positioning
A simplified, user-friendly Artemis II tracker that aggregates public data sources (JPL Horizons API, NASA DSN XML feed) to provide essential mission information without unnecessary complexity.
SaaS Insight & Market Implications
Artemis.fyi addresses a common user experience gap in public data consumption: the need for simplified, aggregated views of complex, disparate information. While a niche application, its development highlights the value of robust data pipeline construction from publicly available, often underutilized, APIs. The project's success in synthesizing JPL Horizons and NASA DSN data into an intuitive interface demonstrates a market opportunity for specialized data aggregation and visualization services. This approach reduces user friction by abstracting data complexity, a principle applicable across various industries. The emphasis on data correctness and the manual effort in pipeline construction underscore the ongoing challenge and value in transforming raw public data into reliable, actionable insights.
Proprietary Technical Taxonomy
real-time tracker JPL Horizons API ephemeris data Orion spacecraft position velocity range NASA Deep Space Network (DSN)

Raw Developer Origin & Technical Request

Source Icon Hacker News Apr 5, 2026
Show HN: Artemis.fyi - Real-time tracker for the Artemis II Moon mission

There are plenty of Artemis II trackers out there. I looked at a bunch and kept running into the same issues - some had data that didn't look right, it was hard to use on smaller screen, others felt overly complicated for what I actually wanted to know: what's the crew doing, where is Orion, how fast is it going. The best one I found was issinfo.net/artemis, which inspired a lot of the design.So I built my own. The part that was genuinely interesting to me was the data. Turns out anyone can query JPL's Horizons API for full ephemeris data on the Orion spacecraft - position, velocity, range - for free. I had no idea this existed.Even better: NASA's Deep Space Network publishes a live XML feed (eyes.nasa.gov/dsn/data/dsn.xml) that updates every 5 seconds showing exactly which ground antennas are talking to which spacecraft. Right now two dishes in Canberra are locked onto Orion - one sending commands, both receiving 6 Mbps of S-band telemetry at 296,000 km. You can see Juno at Jupiter, JWST, Mars Odyssey, all in the same feed. It's pretty amazing what's just sitting there in the open.The app fetches trajectory from Horizons, crew activities from NASA's published flight plan, and live ground station status from DSN. I'll be honest - it's mostly vibe-coded with supervision. The data pipeline is the part that was more manual: figuring out what's publicly available, how to compute relative positions from raw vectors, how to cache and backfill. That was the fun part.Code is open on GitHub. I built it for myself and as a fun exercise, but happy for any feedback - especially around data correctness and what other public data sources are out there that I might be missing.Source: github.com/dmarchuk/artemis....

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Frequently Asked Questions

Market intelligence mapped to Artemis.fyi, a real-time tracker for the Artemis II Moon mission..

How is Artemis.fyi, a real-time tracker for the Artemis II Moon mission. positioned in the market?
Based on our AI analysis of the original developer request, its primary technical positioning is: A simplified, user-friendly Artemis II tracker that aggregates public data sources (JPL Horizons API, NASA DSN XML feed) to provide essential mission information without unnecessary complexity.
What architecture is tied to Artemis.fyi, a real-time tracker for the Artemis II Moon mission.?
Our proprietary extraction maps Artemis.fyi, a real-time tracker for the Artemis II Moon mission. to adjacent architectural concepts including real-time tracker, JPL Horizons API, ephemeris data, Orion spacecraft.

Engagement Signals

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Cross-Market Term Frequency

Quantifies the cross-market adoption of foundational terms like cache and range by tracking occurrence frequency across active SaaS architectures and enterprise developer debates.