Trillions of requests.
Petabyte scale.
Unprecedented functionality.
Yesterday's hyperbole is today's reality.
Some companies have created systems so large they are difficult to comprehend. Despite fears of AI coming for everyone's jobs, mere mortals are responsible for designing, building, and operating these software behemoths.
For everyone who has sat in awe and thought "how did they do that?" QCon presents Architectures You've Always Wondered About. Continuing a tradition since the first QCon 18 years ago, this flagship track brings together a collection of stories from innovative companies who are pushing the limits with modern software systems.
Be inspired by speakers sharing real-world examples of how they've scaled systems to handle massive amounts of traffic, data, and complexity. Learn from their challenges so you're prepared for your own journey to hyperbolic scale.
From this track
Supporting Diverse ML Systems at Netflix
Monday Nov 18 / 10:35AM PST
Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications.
David Berg
Senior Software Engineer @Netflix, Previously @IBM Almaden Research Center, Ph.D in Computational Neuroscience
Romain Cledat
Senior Software Engineer @Netflix, Metaflow Core Contributor, Previously @Facebook and @Intel
Optimizing Search at Uber Eats
Monday Nov 18 / 11:45AM PST
Uber has an in-house search engine called Search In Action (SIA). As the backbone behind the feed and search capabilities of Uber's Delivery business, SIA plays a crucial role in expanding selection seamlessly for customers which is a strategic advantage to the business.
Janani Narayanan
Applied ML Engineer @Uber, Previously Tech Lead on DynamoDB Control Plane (Early Stage), 10+ Years Tech Industry Experience
Karthik Ramasamy
Senior Staff Software Engineer @Uber, 15 Years of Experience in Design and Implementation of Web Applications, Distributed Systems, Search and Analytics Infrastructure
Changing the Model: Why and How We Re-Architected Slack
Monday Nov 18 / 01:35PM PST
Over time, the architectural assumptions underpinning a software application may diverge further and further from that application's product requirements.
Ian Hoffman
Staff Software Engineer @Slack, Previously @Chairish
Unconference: Architectures You've Always Wondered About
Monday Nov 18 / 02:45PM PST
How GitHub Copilot Serves 400 Million Completion Requests a Day
Monday Nov 18 / 03:55PM PST
GitHub Copilot is the largest LLM powered Code Completion service in the world, serving hundreds of millions of requests per day with an average response time of under 200ms. This is the story of the architecture which powers this product.
David Cheney
Lead, Copilot Proxy @GitHub, Open Source Contributor and Project Member for Go Programming Language, Previously @VMware
Legacy Modernization: Architecting Real-Time Systems Around a Mainframe
Monday Nov 18 / 05:05PM PST
Designing systems that take advantage of modern platforms, tools, and techniques is critical for building scalable, evolvable applications that underpin businesses of all stripes. Leveraging those when your data is captured in a mainframe, which does not scale well, is challenging.
Jason Roberts
Lead Software Consultant @Thoughtworks, 15+ years in Software Development, Azure Solutions Architect Expert
Sonia Mathew
Director, Product Engineering @National Grid, 20+ Years in Tech
