Industries moving into distributed, microservice-based architectures have become a standard approach to build our apps and services. Despite the various patterns that have emerged, we still run a patchwork of queues and event buses to achieve resilience and reliability across these disjointed services. This ends up resulting in a queue abyss that inevitably drowns everyone. The problem is that these patterns are leaky abstractions that burden developers with excessive implementation and operational complexity. "Durable Execution" is an emerging programming model concept that automatically and transparently handles the creation and use of queues in order to run your code with complete reliability at the platform level. When developers learn about this approach to writing a fully fault-tolerant codeit, the most common reaction is that it is “too good to be true.” In reality, it really isn't. Soon they see that the technology lives up to its promise. That’s why, through its open source manifestation, temporal.io powers thousands of mission-critical applications. The presentation will introduce you to some of the concepts and level you up into a whole new world called Durable Execution. It will also allow you to climb out of the abyss of disjointed services and into clouds of reliable solutions. So you can fully trust it with your most precious workloads.
Speaker
Maxim Fateev
CEO & Cofounder @Temporal Technologies
Maxim has spent the last 20 years building massive distributed systems for Amazon, Microsoft, Google, and Uber. Among other things, he led the design and development of the AWS SQS backend, and AWS Simple Workflow Service. At Uber, Maxim led the effort on open source projects Cherami and Cadence Workflow. Since October of 2019, Maxim has been the CEO/Cofounder of Temporal Technologies. Its flagship open source project temporal.io is redefining the way large-scale reliable applications are developed and operated.
Session Sponsored By
Durable execution system enabling reliable execution of software services and applications at scale