Cheering on coworkers: Building culture with Datadog dashboards | Datadog (opens in new tab)

Datadog engineers developed a real-time tracking dashboard to monitor a colleague’s progress during an 850km, six-day ultra-marathon challenge. By scraping public race statistics and piping the data into their monitoring platform, the team created a centralized visualization tool to provide remote support and office-wide engagement.

Data Extraction and Parsing

The team needed to harvest race data that was only available as plain HTML on the event’s official website.

• A crawler was built using the Python Requests library to automate the retrieval of the webpage's source code.
• The team utilized BeautifulSoup to parse the HTML and isolate specific data points, such as the runner's current ranking and total distance covered.

Ingesting Metrics with StatsD

Once the data was structured, it was converted into telemetry using the Datadog agent and the statsd Python library.

• The script utilized dog.gauge to emit three primary metrics: runner.distance, runner.ranking, and runner.elapsed_time.
• Each metric was assigned a "name" tag corresponding to the runner, allowing the team to filter data and compare participants within the Datadog interface.
• The data was updated periodically to ensure the dashboard reflected the most current race standings.

Dashboard Visualization and Results

The final phase involved synthesizing the metrics into a high-visibility dashboard displayed in the company’s New York and Paris offices.

• The dashboard combined technical performance graphs with multimedia elements, including live video feeds and GIFs, to create an interactive cheering station.
• The system successfully tracked the athlete's 47km lead in real-time, providing the team with immediate updates on his physical progress and elapsed time over the 144-hour event.

This project demonstrates how standard observability tools can be repurposed for creative "life-graphing" applications. By combining simple web scraping with metric ingestion, engineers can quickly build custom monitoring solutions for any public data source.