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Evolving Analytics in the Data Platform

When designing distributed systems teams use their hard-gained experience to try to prevent known failure modes. Once those systems are in production there will be new failures happening and new learnings as a result.

In this talk, we will deep dive into the BBC’s analytics platform architecture, show the failure modes we knew and designed for, and then how we investigated the new unknowns and automated them away.  

This talk will discuss how we arrived at the conclusion of which metrics were of most value and strived to keep things simple. This has been key to everyone in the team understanding the health of the system and what it means when a failure arises.


Blanca Garcia Gil

Principal Systems Engineer @BBC

Blanca Garcia Gil is a Principal Systems Engineer at BBC. She currently works on a team whose aim is to provide a reliable platform at petabyte scale for data engineering and machine learning. She leads a team focused on improving access to data and making sure the data warehouse is performant and reliable for business critical workloads.  

Prior to the BBC, she has had a variety of roles from developing web applications for an agency, mobile prototyping (before smartphones came about!), developing a content management system, or writing highly scalable APIs. She always enjoyed working closer to the backend and since she started developing in the Cloud she took on the challenge of learning about infrastructure. This has led to her deciding to move to an infrastructure automation, performance, and reliability role.

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