Efficiency in the Cloud: Leveraging Temporal Cloud Metrics to Autoscale Your Workers at Bitovi

Abstract

In an increasingly connected world, handling traffic spikes effectively is paramount. This talk delves into several autoscaling approaches for Temporal worker clusters.

We’ll explore scaling methodologies, such as using Temporal Cloud metrics, PaaS metrics, or scheduled scaling. We’ll discuss how companies leverage these various options and the pros and cons associated with them. By dissecting these approaches, you’ll gain insights into scaling strategies for meeting demand in real time while optimizing resource allocation in Temporal environments.

We’ll also dive into suggested server metrics for autoscaling Temporal workers. Metrics are the bedrock for informed decision-making, ensuring that resources are allocated judiciously to meet fluctuating demands while maintaining cost efficiency.

Scaling a Temporal worker cluster can be daunting, depending on your requirements and experience level. I’ll walk through the different approaches and provide real-world solutions used to scale some of the production systems Bitovi has the privilege of contributing to.

Finally, I’ll walk you through a live demo showcasing the use of Temporal Cloud metrics to scale a worker cluster dynamically. Attendees will witness firsthand how this scaling strategy adapts to real-time metrics, ensuring minimal latency and optimal resource utilization.

Walk away with tangible strategies to help you scale with Temporal and make smart decisions about how to do it.

About the Presenter

Austin Kurpuis is a seasoned full-stack software engineer with over 12 years of experience across diverse industries, including E-commerce, MedTech, FinTech, Defense, Logistics, and GenAI. His career is marked by high-profile consulting roles for companies such as Apple and GrubHub.