Learn how engineering organizations are building internal platforms that deliver real outcomes: faster delivery, safer operations, and reduced developer cognitive load. This track explores the architectural, organizational, and operational trade-offs behind successful platform engineering initiatives, including balancing standardization with flexibility at scale.
From this track
Building a Migration Platform: Moving 100+ Netflix RDBMS Workloads to Aurora PostgreSQL
In late 2024, Netflix made a bet: consolidate the vast majority of our relational database use cases onto a single engine: Amazon Aurora PostgreSQL.
Platform Engineering’s Second Act: From Vending Machine to Passport Control
Three years ago on the QCon SF stage, I made the case for “Acceleration, Autonomy, and Accountability” as the pillars of a successful platform. Those pillars haven't moved. AI has just rewritten what each one requires, and the platform team's job along with it.
Smruti Patel
SVP of Engineering @apollographql
Alex Mann
Senior Engineering Manager @apollographql
Why Most Platform Teams Fail: The Adoption Problem Nobody Wants to Own
We have all seen the moment: the platform goes live, the launch deck looks sharp, the portal is polished, the golden paths are documented, and yet teams quietly continue doing things the old way. Not always because the platform is bad, but because adoption was assumed, not owned.
Shweta Vohra
Architecture Leader @Booking.com, Author of "Decoding Platform Engineering Patterns" & "Dear Software and AI Architect", 24+ Years Experience Building Cloud, Platform, and AI Systems
