Constellation automates scalable, geo-distributed API load testing to allow developers to test how their system responds to requests from all over the globe.
• Architected a serverless load-generation framework with the capability to simultaneously simulate, record, store, and visualize metrics for up to 10,000 virtual users from 26 distinct geographical locations
• Automated and streamlined the deployment of cloud infrastructure based on user input, reducing dozens of complex AWS actions to two Constellation commands.
• Developed a command line interface that provides real-time status for multi-regional deployment.
• Wrote and containerized components that support load generation and monitoring including:
• a load generation engine that generates and monitors HTTP traffic following a user-defined test script by utilizing Node.js promises and Axios instances
• a data collection ELT pipeline that provides a single stream of data to a central AWS Timestream database
• a data visualization tool that provides detailed visibility for convenient performance analysis of test results
• Authored the Constellation case study: https://constellation-load-testing.github.io/case-study.html
• Collaborated remotely with an international team of four engineers across four timezones