Client: Top provider of risk management and asset protection software and services to the automotive industry and member of the S&P 400.
Project Overview
This repeat client brought in an individual Sr. Keyhole consultant to automate a manual process using existing internal infrastructure. This project involved adding a new trigger to an existing Google Cloud CI/CD pipeline to automate uploading the output of Locust load tests to an Elasticsearch instance. Prior to this project, load testing was run on a developer device, and the output was manually uploaded in the form of HTML reports.
The Sr. Consultant utilized Google Cloud, Kubernetes, Docker, and Elasticsearch to automate this process. She updated the existing Locust tests to run in headless mode, then configured a Google Cloud CI/CD pipeline to create a Docker artifact and schedule a load test run through a Kubernetes CronJob. The raw output of this run was uploaded to the Elasticsearch instance, and the existing report was uploaded to a Google Cloud Bucket.
Notably, most of the development was performed on her local system since she did not have permission to develop the client infrastructure directly. At the end of the project, the client was able to trigger load test runs and create visuals of the output in Kibana using the data from Elasticsearch.
