Speaker: Yuri Shkuro

Microservices bestow many benefits on the organizations adopting them, but they come with a steep price: complexity of the resulting architecture. Distributed tracing is a recognized way of dealing with that complexity and getting back the visibility into our systems. At Uber we discovered that this visibility is not enough to be able to understand the system behavior. A trace for a single request from our mobile app may consist of several thousand data points. That’s too much information for engineers to weed through, especially in a high-stress outage situation when every minute counts. Complexity strikes again.

In this talk we present a methodology that uses data mining to learn the typical behavior of the system from massive amounts of distributed traces, compares it with pathological behavior during outages, and uses complexity reduction and intuitive visualizations to guide the user towards actionable insights about the root cause of the outages. The technique has proven to be highly effective in drastically reducing time to mitigation of high severity outages. The visualizations are built using the modules available in the open source as part of Jaeger, Uber's distributed tracing platform and an incubating project at Cloud Native Computing Foundation.

Details to be confirmed

There is limited seating, separate registration is required. Join some leading experts in microservices to share your challenges, hear from others who have similar challenges, and collaborate together on ways to take what you’ve learned at QCon back to work. The event is open to attendees and sponsors of the conference. 

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