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As Datadog continues to grow, their team needed to prioritize data center expansion. Unfortunately, their Postgres architecture-previously supporting a handful of data centers-became a painful liability for operators & service owners. Hidden coupling, operational toil, & reliance on components like PgBouncer surfaced major coordination challenges for data center expansion.
To understand what needed to change, the team used AI-assisted analysis to examine how Postgres was actually being used across hundreds of services. By analyzing real production workloads, queries, & traffic patterns, they identified hidden dependencies & unsafe assumptions that were impossible for individual teams to investigate alone, allowing them to deliver architectural & service-level changes with confidence.
In this talk, the speaker will share how their team simplified a production Postgres architecture to enable safe, repeatable, & hands-off data center expansion. They will walk through the original design, the failure modes that forced change, & the deliberate tradeoffs they made. The presentation will demonstrate how they used Temporal to automate previously manual workflows, removed redundant dependencies, & ultimately deprecated PgBouncer in favor of a homegrown Postgres proxy.
This practical, experience-driven talk about simplifying Postgres at scale will show how Datadog used automation to tame complexity, AI to detangle existing workloads, & built database architectures that can grow without becoming an operator's nightmare.
Speaker: Fabiana Scala
I am a Staff Engineer at Datadog, I like to focus on providing platform solutions for the product teams to focus on developing their business logic. I am also very active in mentoring other women engineers at Datadog & love to share my knowledge with my peers. Outside of work you can find me playing board games, tennis or traveling.
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