Deploying a Large Scale Army of AI-Driven Testing Bots
AI-driven test execution is helping organizations scale their software validation and verification efforts and keep pace with the speed of DevOps. However, this new level of test automation is not without additional infrastructure costs. AI testing bots tend to consume a significant amount of resources when using deep machine learning models to generate and execute test cases. And so a new problem has arisen: how do we scale AI-driven testing efficiently and reliably to support the needs of large enterprises? Join Patrick Alt as he describes an approach for running hundreds of AI testing bots in parallel using Kubernetes. By leveraging a distributed cloud architecture, you too can deploy an army of AI testing bots that can achieve the scale and level of orchestration required to test complex enterprise applications. Patrick gives tips and tricks that yield key advantages such as ease of use and cost reduction via dynamic autoscaling. Discover how to further increase speed, scale, and compatibility by enabling integrations across a combination of cloud-based or on-premise device labs. Leave empowered to solve enterprise-level testing challenges using AI at scale, with little to no human intervention required.
Patrick Alt is a Software Architect at test.ai, building AI-powered automation tools that help testers, developers, and business stakeholders accelerate their releases. His expertise focuses on designing automated testing tools, domain-specific languages, full-stack software development, and DevOps. Patrick has dual Master's degrees in Computer Science from the Georgia Institute of Technology and the University of Stuttgart. He is a part of the Artificial Intelligence for Software Testing Association, contributing to AI-driven software testing prototypes. He has published research articles in IEEE and ACM-sponsored conferences and workshops.