Systems @Scale Spring 2022
Q&A | Moderated by Francois Richard. Featuring Yuri Grinshteyn, Jie Huang, Christopher Bunn, Osama Abuelsorour, Amr Mahdi, Jason Flinn & Arushi Aggarwal
Q&A | Moderated by Francois Richard. Featuring Yuri Grinshteyn, Jie Huang, Christopher Bunn, Osama Abuelsorour, Amr Mahdi, Jason Flinn & Arushi Aggarwal
Systems @Scale Spring 2022
Owl | Arushi Aggarwal & Jason Flinn
We will describe Owl, a new system for high-fanout distribution of large data objects to hosts in Meta’s private cloud. Owl distributes over 700 petabytes of data per day to millions of client processes. It has improved download ...
Systems @Scale Spring 2022
Southpaw: Token-based service load balancing, scaling and QoS system | Osama Abuelsorour & Amr Mahdi
Southpaw is load balancing, scaling and QoS management system for compute-heavy inferencing services. It takes the approach of abstracting services capabilities into tokens and worklanes, where clients are granted tokens that gives ...
Systems @Scale Spring 2022
Vacuum Testing for Resiliency: Verifying Disaster Recovery in Complex | Jie Huang & Christopher Bunn
Engineers at Meta run thousands of services across millions of machines, and those services all have similar needs that can’t be managed by hand: configuration, deployment, monitoring, routing, orchestration, security. To solve the ...
Systems @Scale Spring 2022
Shrinking the Impact of Production Incidents | Yuri Grinshteyn
Shrinking Production Incidents details an organized approach for reducing the overall impact of production outages. Attendees can expect to learn how to prioritize reliability-related engineering tasks based on incident postmortem ...
Systems @Scale Spring 2022
Highly Available and Strongly Consistent Storage Service Using Chain Replication | Kumar Mrinal & Binbin Lu
Highly Available and Strongly Consistent Storage Service Using Chain Replication | Kumar Mrinal & Binbin Lu – In this talk, we present Dumbo – a simple, reliable, highly available, low dependency object storage system ...
Systems @Scale Spring 2022
ACS: De-Identified Authentication at Scale | Shiv Kushwah & Haozhi Xiong
Privacy is core to Meta engineering culture, and one of our fundamental principles is data minimization. We strive to collect and create the minimum amount of data required to provide service. One critical space we’ve identified across ...
Systems @Scale Spring 2022
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward | Ivan Santa Maria Filho
Cosmos is the exabyte-scale big data platform at Microsoft, and SCOPE is its main analytics engine. SCOPE and Cosmos support ETL pipelines, decision support systems, and machine learning pipelines. Applications range from simple ...
Systems @Scale Spring 2022
Scaling Data Ingestion for ML Training at Meta | Aarti Basant
AI models drive several Meta products like News Feed, Ads, IG Reels, language translation to name a few. Our ranking models consume massive datasets to continuously improve user experience on our platform. In this talk, we discuss our ...
Systems @Scale Spring 2022
Cassandra@Scale: A Deep Dive into Apache Cassandra 4.0 | Dinesh Joshi
At almost two years in the making Apache Cassandra 4.0 is here. With a focus on performance and stability, it is full of interesting features. This talk takes you through a tour of the new features and performance improvements. From ...
Systems @Scale Spring 2022
Manifold: Storage Platform Consolidation | Jacob Lacouture
Since 2016, we’ve built, deployed, and scaled a new BLOB storage platform at Meta, called Manifold. Manifold builds on existing BLOB storage infrastructure, but provides a richer, higher-level, general purpose API, and thereby enables ...
Systems @Scale Spring 2022
Transparent Memory Offloading @Meta | Niket Agarwal, Dan Schatzberg, Johannes Weiner
The unrelenting growth of the memory needs of emerging data center applications, along with ever-increasing cost and volatility of DRAM prices, has led to DRAM being a major infrastructure expense. Alternative technologies, such as ...
RTC @Scale 2022
Real-time Communication for Today and Future Experiences – Maher Saba
Real-time Communication for Today and Future Experiences – Maher Saba
RTC @Scale 2022
Holographic Video Calling – Nitin Garg
Holographic Video Calling – Nitin Garg During COVID, the importance of video calling grew as people were stuck and separated from their family and friends. But the 2D experience falls short of making you feel present in the same ...
RTC @Scale 2022
Spatial Communications at Scale in Virtual Environments – Paul Boustead
Spatial Communications at Scale in Virtual Environments – Paul Boustead Talking with a group of friends face-to-face can be very engaging, with fast-paced turn-taking and overlapping conversations. You can even have such a ...
RTC @Scale 2022
RTC3 – Justin Uberti
RTC3 – Justin Uberti The real-time communications industry has evolved rapidly since the release of Skype in 2003, and saw unprecedented growth during the COVID-19 pandemic. This talk will look at the trends of the last 20 years ...
RTC @Scale 2022
RTC @Scale, Future RTC Experiences – Live Q&A
RTC @Scale, Future RTC Experiences – Live Q&A RTC @Scale, Future RTC Experiences Session – Live Q&A with Nitin Garg, Paul Boustead, Justin Uberti, and Rahul Gowda
RTC @Scale 2022
Developing Machine Learning Based Speech Enhancement Models for Teams and Skype – Ross Cutler
Developing Machine Learning Based Speech Enhancement Models for Teams and Skype – Ross Cutler Microsoft Teams and Skype are used daily by hundreds of millions of users, and their usage has increased significantly since the ...
RTC @Scale 2022
Can AI Disrupt Speech Compression? – Jan Skoglund
Can AI Disrupt Speech Compression? – Jan Skoglund AI and deep learning has radically advanced many speech and audio processing applications. For example, we have all experienced improvements in speech recognition and synthesis in ...
RTC @Scale 2022
RTC @Scale, Audio ML – Live Q&A
RTC @Scale, Audio ML – Live Q&A RTC @Scale, Audio ML Session – Live Q&A with Ross Cutler and Jan Skoglund
RTC @Scale 2022
RTC @Scale Live Panel – RTC in the Metaverse
RTC @Scale Live Panel – RTC in the Metaverse RTC @Scale Live Panel with Sriram Srinivasan, Mike Arcuri, Paul Boustead, and Cullen Jennings.
RTC @Scale 2022
AV1 Encoder for RTC – Marco Paniconi
AV1 Encoder for RTC – Marco Paniconi In this presentation we discuss the various features and techniques that make libaom AV1 encoder suitable for RTC applications: from encoding tool selection to reducing complexity of the ...
RTC @Scale 2022
AV1 for RTC: Current and Future – Zoe Liu
AV1 for RTC: Current and Future – Zoe Liu In this talk, we will mainly focus on the state-of-the-art AV1 software encoding capability for its deployment in RTC use cases, taking our Aurora1 AV1 as an instantiation. RTC in essence ...
RTC @Scale 2022
RTC @Scale, Video – Live Q&A
RTC @Scale, Video – Live Q&A RTC @Scale, Video Session – Live Q&A with Marco Paniconi and Zoe Liu.
RTC @Scale 2022
Making Meta RTC Audio More Resilient – Andy Yang
Making Meta RTC Audio More Resilient – Andy Yang The users of Meta RTC products experience a very diverse set of network conditions, some of those may be far from perfect. In this presentation, we are going to cover the following ...
RTC @Scale 2022
Private Calling at WhatsApp – Xi Deng
Private Calling at WhatsApp – Xi Deng WhatsApp’s mission is to connect the world privately by designing a product that’s simple and private. Privacy and security is in our DNA. In this presentation, we are going to talk ...
RTC @Scale 2022
Group Call End-to-End Encryption and the Challenges of Encrypting Large Calls – Abo-Talib Mahfoodh
Group Call End-to-End Encryption and the Challenges of Encrypting Large Calls – Abo-Talib Mahfoodh Meta helps billions of users connect daily by providing real time communication services. Group call is one of these services were ...
RTC @Scale 2022
RTC @Scale, Resilience and Encryption – Live Q&A
RTC @Scale, Resilience and Encryption – Live Q&A RTC @Scale, Resilience and Encryption Session – Live Q&A with Andy Yang, Xi Deng, and Abo-Talib Mahfoodh
Systems @Scale Winter 2021
Week 1 Q&A | Moderated by Ahmad Mamdouh Abdou. Featuring Dávid Bartók, Filip Klepo, Jared Casper, Antonio Davoli & Leandro Silva
Week 1 Q&A | Moderated by Ahmad Mamdouh Abdou. Featuring Dávid Bartók, Filip Klepo, Jared Casper, Antonio Davoli & Leandro Silva
Systems @Scale Winter 2021
Week 2 Q&A | Moderated by Sajal Jain. Featuring Miroslav Crnic, Nick Sukhanov & Sneha Padgalwar
Week 2 Q&A | Moderated by Sajal Jain. Featuring Miroslav Crnic, Nick Sukhanov & Sneha Padgalwar
Systems @Scale Winter 2021
Software and Hardware Remediations At Meta | Antonio Davoli & Leandro Silva
Efficient software and hardware failure remediations are the foundations for sustaining high fleet availability at large-scale environments such as Meta. In this talk, we will describe the general architecture that we use to maximize ...
Systems @Scale Winter 2021
SLICK: Driving SLO Culture At Meta | Dávid Bartók & Filip Klepo
SLIs (Service Level Indicators) and SLOs (Service Level Objectives) are industry-standard concepts to measure the long-term reliability of systems. In this presentation, we are going to talk about SLICK, the central SLO tracking ...
Systems @Scale Winter 2021
Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM | Jared Casper
In this talk we present how we trained a 530B parameter language model on a DGX SuperPOD with over 3,000 A100 GPUs and a high speed Infiniband interconnect, and how we can scale to even larger models. We explore three types of ...
Systems @Scale Winter 2021
LogDevice At Scale | Miroslav Crnic & Nick Sukhanov
Meta uses a strongly consistent distributed log storage system to broadcast updates in graphs, deliver signals to ML training pipelines, and collect data for analytics. All of these cases require the underlying log system to be highly ...
Systems @Scale Winter 2021
Scheduled Deletions At Scale | Sneha Padgalwar
At Meta, a large part of our data is ephemeral in nature, such as Instagram or Meta Stories which need to be deleted after a specific time regardless of the action taken by the user. This is sometimes referred to as Time to Live (TTL). ...
Video @Scale 2021
The Importance of Audio Today
Live Panel – “The Importance of Audio Today”. Recently, Audio has been front and center with the emergence of new audio-only products and experiences and many new audio-focused investments to enhance video viewing. ...
Video @Scale 2021
Highly-Efficient SVT-AV1-based Solutions for VOD Applications
This presentation will highlight the latest improvements of the VOD-targeted high-latency Constant Rate Factor (CRF) and Variable Bit Rate (VBR) modes of the SVT-AV1 encoder. It will first present the latest SVT-AV1 cycles-quality ...
Video @Scale 2021
Scaling Your Encoding Backend Using Eve
In this talk, we will discuss the current state in terms of bitrate/quality and complexity of Two Orioles’ Eve video encoder for the VP9 & AV1 video codecs. VP9 provides meaningful quality improvements over H.264 with a mature ...
Video @Scale 2021
Video Quality Assessment of User Generated Contents
Video quality of User Generated Content (UGC) is extremely difficult to wrangle with due to their high diversity of contents and quality. They bring new challenges to how we traditionally measured and assessed video quality. Most ...
Video @Scale 2021
Measuring Video Quality Using AVQT
AVQT, short for Advanced Video Quality Tool, is a macOS based command line tool which estimates perceptual video quality of compressed videos that might contain video coding and scaling artifacts. Utilizing the AVFoundation framework, ...
Video @Scale 2021
Optimizing Storage Efficiency for FB Video Processing
Like the rest of the video world, Facebook Video has significantly grown year to year. While we celebrate the growth rate, we are also concerned about the resources consumption to support the growth, which became worse during COVID. ...
Video @Scale 2021
ASIC-RDX and Compute-Compression Efficiency Optimization for UGC Video Processing
Facebook and user-generated content (UGC) platforms encode videos at “billion-scale” and deliver them worldwide to a variety of devices (Mobile/Laptop/TV) across different networks. The popularity of UGC videos can vary widely ranging ...
Video @Scale 2021
Behind the Curtains: A/B Tests in Video Land
A/B testing on video isn’t just about tweaking recommendations or picking the perfect thumbnail. Every aspect of video benefits from rapid experimentation including the infrastructure – streaming algorithms, codecs, bitrates, caching ...
Video @Scale 2021
Media Provenance as a Prevention for Malicious Synthetic Media
Malicious synthetic media – both deepfakes and cheapfakes – are rising in prevalence and importance. End users are rapidly losing trust in media, and their ability to tell authentic media from inauthentic has greatly diminished. This ...
Video @Scale 2021
Smart Crop and Smart Preview via Video Understanding
Understanding video content has been a focus for video-sharing platforms. It is one of the most important driving forces for the growth in distribution, discovery, user experience and monetization. Instream video understanding is the ...
Video @Scale 2021
Highly Available Live Encoding Using Go and Kubernetes
Two years ago, iStreamPlanet set out to build a cloud-native software transcoder with the reliability and feature set to support some of the highest profile live channels and events in the world. Some of our goals included: 4+ 9’s of ...
Video @Scale 2021
Performance of Low-Latency DASH/CMAF and Low-Latency HLS Systems
Reducing end-to-end streaming latency is critical for HTTP-based live video streaming. There are currently two new technologies in this domain: Low-Latency HTTP Live Streaming (LL-HLS) and Low-Latency Dynamic Adaptive Streaming over ...
Video @Scale 2021
Measuring the Reliability of Live Video Infrastructure
Serving Live Videos with high reliability is challenging, not only from the perspective of deploying improvements on top of a distributed system but also from the perspective of defining correct measurements to capture reliability gaps ...
Video @Scale 2021
Keynote
Hear from Paresh Rajwat, the Vice President and Head of Product for Facebook Audio, Video, and Music.
Systems @Scale Fall 2021
Week 3 Live Q&A – Systems @Scale Fall 2021 Edition
Week 3 Live Q&A – Systems @Scale Fall 2021 Edition with speakers discussing Challenges@Scale
Systems @Scale Fall 2021
Scaling Back-End Deployment @ Facebook
We present how Facebook’s unified Continuous Deployment (CD) system, Conveyor, powers safe and flexible service deployment across all services at Facebook. Conveyor enables services owners to build highly customized deployment ...
Systems @Scale Fall 2021
Lessons from Building a Large-scale, Multi-cloud Data Platform at Databricks
The cloud is becoming one of the most attractive ways for enterprises to store, analyze, and get value from their data, but building and operating a data platform in the cloud has a number of new challenges compared to traditional ...
Systems @Scale Fall 2021
Making Distributed Priority Queue Disaster Ready
Facebook Ordered Queue Service (FOQS) is a distributed priority queue service that powers hundreds of services and products across the Facebook stack. Facebook users have come to rely on its services to remain connected to their ...
Systems @Scale Fall 2021
Scaling Apache Kafka in the Cloud
Confluent Inc provides cloud based data stream platforms based on Apache Kafka. Running an open source product like Kafka on the public cloud offerings of Amazon, Google, and Microsoft offers an interesting array of challenges. This ...
Systems @Scale Fall 2021
Week 2 Live Q&A – Systems @Scale Fall 2021 Edition
Week 2 Live Q&A – Systems @Scale Fall 2021 Edition with speakers discussing Reliability & Testing
Systems @Scale Fall 2021
Power Loss Siren: Making Facebook Resilient to Power Outages
Power outages cause the majority of unplanned server downtime in Facebook data centers. During a power outage, thousands of servers can go offline simultaneously for several hours, which can lead to service degradations. At Facebook, ...
Systems @Scale Fall 2021
Scaling Testing at a Startup: Integration Testing GraphQL Services with Jest
BigSpring is a mobile first platform for lifelong skilling with measurable ROI. We use GraphQL to power our services. We would love to talk about how we use Jest to integration test our resolvers and other business logic built in our ...
Systems @Scale Fall 2021
Automatic Testing for Services at Scale
Developing at speed and scale across Facebook’s many services requires testing frameworks that help developers iterate on features quickly and with minimal friction, while helping to catch bugs early. Learn why we’ve built our own ...
Systems @Scale Fall 2021
Blaming in a Blameless World
Attribution of reliability in a microservice architecture can be solved, and has been solved, in very different ways due to how services are cataloged across the industry. Our hypothesis at Lyft was that service catalogs can become ...
Systems @Scale Fall 2021
Amazon Redshift Reinvented
In 2013, eight years ago, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift, the first fully managed, petabyte-scale cloud data warehouse solution. Amazon Redshift made it simple and ...
Systems @Scale Fall 2021
Week 1 Live Q&A – Systems @Scale Fall 2021 Edition
Week 1 Live Q&A – Systems @Scale Fall 2021 Edition with speakers discussing Capacity & Efficiency
Systems @Scale Fall 2021
End-2-End Resource Accounting Leveraging Distributed Tracing
Transitive Resource Accounting (TRA) is a system that builds on top of Facebook’s distributed traces platform, Canopy, with the goal of capturing end-2-end request cost metrics and attributing them back to the originating caller. This ...
Systems @Scale Fall 2021
Log Events @ Twitter: Challenges of Handling Billions of Events per Minute
At Twitter, hundreds of thousands of microservices emit important events triggered by user interactions on the platform. The Data Platform team has the requirement to aggregate these events by service type and generate consolidated ...
Systems @Scale Fall 2021
RAS: A Resource Allowance System for Perpetual Region-wide Resource Allocation
Facebook is undergoing a massive design shift in capacity management and service placement to scale the efficiency of our datacenter resources. At the core of this shift is the Resource Allowance System (RAS) that continuously ...
Systems @Scale Summer 2021
Week 4 Live Q&A – Systems @Scale Summer 2021 Edition
Systems @Scale, Summer – Week 4 Q&A with speakers discussing Performance
Systems @Scale Summer 2021
Resource Guarantees in a Multi-Tenant Infrastructure
The Facebook cloud supports a variety of workloads including those which are CPU intensive, memory bound, I/O bound, latency sensitive, or a combination of these, on hardware that ranges from smaller single socket servers to load ...
Systems @Scale Summer 2021
Platform Agnostic Observability System for AI Accelerators
Application specific hardware platforms play a crucial role in meeting the growing latency and compute demands of workloads like deep learning, content understanding and video encoding. However, it is challenging to operate these ...
Systems @Scale Summer 2021
Performance Wins with BPF: Getting Started
BPF (eBPF) tracing is the superpower that can analyze everything, helping you find performance wins, troubleshoot software, and more. But with many different front-ends and languages, and years of evolution, finding the right starting ...
Systems @Scale Summer 2021
Week 3 Live Q&A – Systems @Scale Summer 2021 Edition
Systems @Scale, Summer – Week 3 Live Q&A with speakers discussing Scalability
Systems @Scale Summer 2021
What is Behind Alibaba’s Double 11 Shopping Festival – The Architecture Evolution of Flink Stream-Batch Unification UNIFICATION
In this talk, we share some of the most exciting achievements of Flink at Alibaba in recent years, including two main topics: one is the architecture evolution of stream-batch unification; the other is the recent efforts to improve ...
Systems @Scale Summer 2021
Consolidating Storage Backend at Scale with Tectonic Filesystem
Tectonic is Facebook’s exabyte-scale, datacenter-wide distributed filesystem. Prior to Tectonic, Facebook’s storage infrastructure consisted of a constellation of smaller, specialized storage systems. Blob storage was spread across ...
Systems @Scale Summer 2021
ARKDB: The Key-Value Engine for Alibaba Cloud Storage Services
Alibaba Cloud offers a comprehensive set of storage services, including Object Storage Service (OSS), File Storage Service (NAS) and NoSQL Tablestore with high durability, high availability, high scalability and strong consistency. All ...
Systems @Scale Summer 2021
Week 2 Live Q&A – Systems @Scale Summer 2021 Edition
Systems @Scale, Summer – Week 2 Live Q&A with speakers discussing Cluster Management, Capacity, and Provisioning @Scale
Systems @Scale Summer 2021
Dynamic Leasing of Spare Capacity to Improve Fleet Utilization with Optimus
Optimus, our spare capacity leasing system, coordinates capacity allocations on millions of machines to improve global capacity utilization and meet fast growing business needs. Within Facebook’s infrastructure, spares are ...
Systems @Scale Summer 2021
Morcor – Co-location of Mixed Workloads at Uber
Uber infrastructure broadly supports 3 kinds of workloads: stateless microservices, big data (batch) and stateful, each running on its own hardware silo. Morcor aims to reduce the cost of infrastructure through co-location of stateless ...
Systems @Scale Summer 2021
Managing a Million Kubernetes Clusters
Azure Kubernetes Service (AKS) manages Kubernetes clusters on behalf of customers. AKS stays agnostic to the customer workload and manages the accessibility, performance, and reliability of these clusters without requiring full ...
Systems @Scale Summer 2021
Defining Service Level Objectives for Exposure Notifications Servers
This session will share the real-world lessons from reliability engineering work on the Exposure Notifications Server – A project from Google and Apple in an effort to slow the spread of COVID-19. The work from Google SRE ...
Systems @Scale Summer 2021
Better Resilience Through Self Tuning
William previously worked at Netflix, and this presentation will highlight some of the strategies he used while working there. He has the permission of Netflix to discuss them at this conference. As companies grow and the number of ...
Systems @Scale Summer 2021
Avoiding Overload in Distributed Systems
At AWS, we build systems using a variety of complementary strategies for maintaining predictable, consistent performance in the face of overload. In this talk, we describe techniques such as implementing layers of protection, ...
Systems @Scale Summer 2021
Live Traffic Load-Testing-Measuring and Validating Capacity at Facebook
Facebook is made up of hundreds of heterogeneous services in geographically distributed data center regions. To reliably run, providing a sufficient amount of capacity for all sub-systems and services is crucial. However, understanding ...
Systems @Scale Summer 2021
Week 1 Live Q&A – Systems @Scale Summer 2021 Edition
Systems @Scale, Summer – Week 1 Live Q&A with speakers discussing Reliability.
Systems @Scale Spring 2021
Virtualizing Consensus in Delos for Rapid Upgrades and Happy Engineers
We will be hosting a talk about our work on Virtualizing Consensus In Delos For Rapid Upgrades And Happy Engineers during our virtual Systems @Scale event at 11am PT on Wednesday, March 17th, followed by a live Q&A session. Please ...
Systems @Scale Spring 2021
FlightTracker: Social graph consistency at scale
We will be hosting a talk about our work on FlightTracker: Social graph consistency at scale during our virtual Systems @Scale event at 11am PT on Wednesday, March 17th, followed by a live Q&A session. Please submit any questions ...
Systems @Scale Spring 2021
Systems @Scale Spring 2021: Week 3
Welcome to the third week of Systems@Scale – Spring 2021, Virtual Edition – featuring recorded sessions & Live Q&As with Maxim Fateev, Girish Joshi, and Dan Shiovitz.
Systems @Scale Spring 2021
Workflows@Facebook: Powering developer productivity and automation at Facebook scale
We will be hosting a talk about our work on Workflows@Facebook: Powering Developer Productivity And Automation At Facebook Scale during our virtual Systems @Scale event at 11am PT on Wednesday, March 10th, followed by a live Q&A ...
Systems @Scale Spring 2021
Week 2 Live Q&A – Systems @Scale Spring 2021 Edition
Welcome to the second week of Systems@Scale – Spring 2021, Virtual Edition – featuring recorded sessions & Live Q&As with Chidambaram Muthu, Dan Danaila, and Sazzala Reddy.
Systems @Scale Spring 2021
Optimizing video storage via Semantic Replication
We will host a talk about our work on Optimizing video storage via Semantic Replication during our virtual Systems @Scale event at 11am PT on Wednesday, March 3rd, followed by a live Q&A session. Please submit any questions you may ...
Systems @Scale Spring 2021
Week 1 Live Q&A – Systems @Scale Spring 2021 Edition
Welcome to the first week of Systems@Scale – Spring 2021, Virtual Edition – featuring recorded sessions and Live Q&A sessions with Akshay Nanavati, Niharika Devanathan, and Gerhard Lazu.
Performance @Scale NY
Performance @Scale 2020: Optimizing the Instagram Web Tier
Instagram is one of the largest Python deployments which supports billions of people using the service. As the system and features keep growing, so has our compute footprint. This was even more evident this year when global lockdowns ...
Performance @Scale NY
Performance @Scale 2020: Improving UX with resource prioritization
With today’s complex web content, ordering the requests for resources can have a dramatic impact on the resulting user experience. Patrick will explore what the impact of the ordering can have, discuss practical solutions to ...
Performance @Scale NY
Performance @Scale 2020: Scaling machine learning on graphs
Networks (graphs) of people’s social and content interactions are a rich source of data for machine learning algorithms. Traditional machine learning algorithms do not naturally take graph-structured data as input, so unsupervised ...
Performance @Scale NY
Performance @Scale 2020: Understanding emotion for happy users
In this talk we will look at how to collect, analyze, and act on a few metrics that tell us more about how our user feels when using the site. We can trend how these metrics change over a user’s browsing experience, and we can improve ...
Performance @Scale NY
Performance @Scale 2020: Facebook’s developer infrastructure
In our first talk of the conference you’ll hear how Facebook is scaling its performance efforts across many apps that are growing and evolving rapidly. What are the newest directions Facebook is exploring to make apps fast and keep ...
Keeping the Lights On @Scale
Keeping the Lights on @Scale 2020: Panel discussion
This panel discussion will explore how our global engineering team immediately came together as one at the start of the pandemic. Through it all, Facebook wasn’t just “keeping the lights on.” Our team was ushering in the future of ...
Keeping the Lights On @Scale
Keeping the Lights on @Scale 2020: Remote Work @Scale
On March 6, Facebook closed its global offices and employees began working from home. It was the start of the largest remote work experiment ever created. This presentation will provide an inside look at how we enabled our engineers to ...
AI @Scale
AI @Scale: Flyte: Making MLOps and DataOps a reality
Flyte is the backbone for large-scale Machine Learning and Data Processing (ETL) pipelines at Lyft. It is used across business critical applications ranging from ETA, Pricing, Mapping, Autonomous, etc. At its core it is a Kubernetes ...
AI @Scale
AI @Scale 2020: Azure Cognitive Services @Scale
Azure Cognitive Services sits at the core of many essential products and services at Microsoft for internal and external workloads. Anand’s talk describes the hardware and software infrastructure that supports Ai services at global ...
AI @Scale
AI @Scale 2020: Mastercook: Large scale concurrent model development in ads ranking
We will discuss a novel model development process and tools we introduced to ads ranking machine learning teams, where a single model can be concurrently developed by dozens of engineers, whose changes to the model are centralized ...