Uber’s observability engineers present their work on distributed tracing (Jaeger), sampling (XYS), and metrics processing (M3).
At the Uber Open Summit Sofia 2019, we showcased how open source technologies are driving the future of artificial intelligence, site reliability, and other domains.
Noticing increased latency in our metrics platform, Uber engineers track down a bug related to stack growth in a goroutine, resulting in a fix elevated to the Go open source GitHub repository.
Celina Ward discusses her journey to engineering, what it was like to present at Kubecon 2018, and what’s next for M3, Uber's open source metrics platform.
Ever wondered what it’s like to work in tech at Uber New York City? Just blocks from Times Square and Bryant Park, Uber’s new office in midtown Manhattan is home to more than a dozen teams, hundreds of employees (and growing), and a wide variety of engineering roles.
Part of Uber's open source M3 metrics system, our query engine can support real-time, large-scale computation and multiple query languages.
Uber’s Observability team built a robust, scalable metrics and alerting pipeline to detect, mitigate, and notify engineers of issues as they occur.
Uber open source projects leads give updates on seven of our projects, all of which will be showcased at the upcoming Uber Open Summit 2018.
Keynote speakers include Jim Zemlin, executive director of the Linux Foundation, and Zoubin Ghahramani, chief scientist at Uber AI Labs.
M3, Uber's open source metrics platform for Prometheus, facilitates scalable and configurable multi-tenant storage for large-scale metrics.