Elizabeth Carretto

Senior Software Engineer @Netflix

Elizabeth Carretto is a Senior Software Engineer at Netflix in Productivity Engineering, where she builds UIs for the observability space. Her work focuses on delivering value from observability data to service operators through products like Edgar, a troubleshooting tool built on top of distributed tracing. She enjoys building tools that help engineers quickly understand an issue when they get paged in the middle of the night.


Solving Mysteries Faster with Observability

Everyone loves a good mystery, but not when it involves operating our services. Investigating production issues in a microservice architecture can make you feel like a detective, combing through evidence and gathering clues to reconstruct the scene of a crime, all while the clock is ticking. You hop from log store to dashboard, digging for details as you strive to unravel what really happened. All this time spent investigating is expensive, for engineers as well as customers -- and even then, finding an issue is not the same as resolving it!  

Edgar is a tool used and built by Netflix engineers to quickly investigate and solve production issues. Edgar starts with distributed tracing, which shows a request’s path through a complex system. But the request’s path is only a small part of the data available about a request. Dozens of dashboards hold their own insights on what happened, and it takes time for engineers to jump between individual dashboards. Edgar strives to get all this data in one place, supplementing traces with additional context like log correlation, metadata about services, and intelligent analysis. Not only does this help Netflix engineers investigate more efficiently, it empowers our customer service operations to access the same information. Our engineers and customer service operations rely on Edgar so they can quickly get our members back to enjoying their favorite movies and shows. 

You’ll leave this talk with an understanding of how we enhance distributed tracing with additional context like logs and metadata to resolve issues. You’ll see examples of how Edgar has paid off and hear about challenges we faced. Finally, we’ll inspire you to leverage the data you already have to help you and your team solve mysteries faster.


Tuesday Nov 10 / 02:40PM EST (40 minutes )

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