Evaluating the transition from HPA to KEDA in an Event-Driven Architecture Deployed in Kubernetes (2024)
This thesis investigates the scalability of a system in Kubernetes, comparing two scaling methods: Horizontal Pod Autoscaling (HPA) and Kubernetes Event-Driven Autoscaling (KEDA). The study uses a Proof of Concept (POC) for a company that wishes to remain anonymous. The research tests the system's ability to scale based on CPU/memory utilization with HPA and event-driven triggers using KEDA, particularly focusing on the system's response to different levels of HTTP requests and event-driven workloads. The tests are conducted in a Minikube environment using Amazon SQS as the message broker, providing insights into the performance and efficiency of these two scaling methods in a real-world scenario.