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 stale, but ownership derived from an on-call rotation will be significantly more reliable for attribution. We'd like to share our journey through combining Envoy, Pagerduty, and an organizational hierarchy to identify reliability concerns across Lyft through standardized SLOs and Director-level rollups.

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 integration testing framework for services and how we combine it with ideas from fuzzing to enable fully autonomous testing.

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 TypeScript Node.js code base. We'll cover how we setup test data, mock connections and collect code coverage as part of our CI/CD process on Github Actions. Being a global and a business critical app, reliability and development velocity is key and we hope to share some hard earned lessons in introducing comprehensive testing to an existing GraphQL repo.

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, all data center racks are equipped with batteries that can provide backup power for a few minutes after power outages. Power Loss Siren (PLS) is a rack level, low latency, distributed power outage detection and alerting system. PLS leverages existing in-rack batteries to notify services about impending power outages and helps mitigate the impact of power outages on services. Typical mitigations include promoting remote database secondaries when primaries are experiencing power outages, routing requests away from hosts experiencing power outages, flushing memory to disk, etc. PLS also helps simplify physical infrastructure management by not requiring additional power source redundancy for critical services.

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 presentation gives an overview of these challenges and discusses some of the solutions that Confluent uses to meet them.

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 friends and families. As such, it is absolutely crucial for Facebook to continue operating with high availability during events which may impact its data centers. Being a core building block of Facebook infrastructure, FOQS is expected to handle loss of a data center gracefully and transparently to its clients. Dillon and Jasmit will talk about how the architecture of FOQS has evolved to be resilient to disasters, the technical challenges of hosting a globally available system, and the operational challenges that came with migrating existing tenants of FOQS to disaster ready installations with zero downtime at Facebook scale.

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 on-premises data systems. I will explain some of these challenges based on my experience at Databricks, a startup that provides a data analytics platform as a service on AWS, Azure, and Google Cloud. Databricks manages millions of VMs per day to run data engineering and machine learning workloads using Apache Spark, TensorFlow, Python and other software for thousands of customers.

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 pipelines from easy-to-use components and supports building, testing, and deploying a diverse range of services. To go further, we explore how Conveyor's deployment system, Push, provides users with tools to deploy new binary versions safely and gradually across the Facebook fleet.

The speakers from the day's sessions will join a Q&A about their work.