Better Software West 2017 Concurrent Session - Scaling Automated Tests: Choosing an Appropriate Subset | TechWell

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Thursday, June 8, 2017 - 11:30am to 12:30pm

Scaling Automated Tests: Choosing an Appropriate Subset

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Automated testing of an application with many dependent services can be challenging. Achieving continuous deployment across these services can be even more so. Managing, coordinating, and scaling deployments of services can become overwhelming and error prone over time. Ensuring that you are able to detect important defects before customers do can be difficult. Executing only relevant tests after each code change rather than always running everything (boiling the ocean) can be a formidable task and might not scale well as the size of the app increases. Manoj Pahuja and Daniel Clayton suggest a remedy. What if simply adding an additional YAML file in your source code repository could eliminate a lot of these pain points and make managing all these jobs and tasks easier? What if defining properties in this file could select and run the most appropriate tests? What if this file could set up the infrastructure to run the app and tests auto-magically? Manoj and Daniel present ideas and practical solutions that work to scale deployments and automated test runs. Join them as they share strategies to determine which tests to run in response to each code change.

Manoj Pahuja

Test architect at GoDaddy Manoj Pahuja has several years’ experience in test planning, strategy, and automation for web, desktop, and mobile applications. He has worked on building automation frameworks, created and managed test management software, and is an active member of the open source community. Manoj’s experience writing automation in VBScript, Java, Ruby, and now NodeJS has helped him deal with the challenges of automation. A strong believer in learning while sharing, he co-organizes meetups in the San Francisco Bay Area.

Daniel Clayton

Daniel Clayton is principal engineer at GoDaddy with twenty years of software development and architecture experience. For the past nine years, he has developed customer fraud detection systems for GoDaddy, and most recently spent time architecting and developing continuous integration and deployment tools. Previously, Daniel worked with a financial company as a senior software engineer, building eCommerce and merchant fraud detection systems. He has significant experience in many popular technology stacks for both Windows and Linux.