Autoscaling Algorithm for Managing Clients on Kubernetes Clusters
January 1, 2022CrowdStrike Computer Science, 2021–22
Liaison(s): Luke Hunter ’03, Julius Lauw ’20, Jonathan Fuentes, Eric Schow
Advisor(s): Lucas Bang
Students(s): Joshua Cheung, Isabel Duan, Thomas Fleming (PM), Rachel Wander, Wayne Ying
CrowdStrike is a leading provider of cloud-native endpoint protection. They want to be able to automatically scale server resources to account for changing volumes of security event traffic. The CrowdStrike Clinic Team is redesigning an existing automatic scaling algorithm to scale Kafka consumers in Kubernetes. The most effective algorithm will minimize the amount of processing time and the cost of deploying consumers to best support CrowdStrike and its customers.