As businesses start increasingly relying on Kubernetes, the need to scale services based on the business demand becomes more important. While the traditional methods like scaling based on the CPU and memory are important, expressing different business metrics in CPU and memory isn’t always straightforward. In this light, auto-scaling based on custom metrics in Kubernetes is going to be immensely helpful.
With the support for custom metrics, services can be scaled dynamically based on the request count or the error count of a particular service. This helps services respond smoothly to sudden bursts and traffic variations ensuring business continuity, also allowing resources allocated optimally among different services.
With its new release, the WSO2 Microgateway supports scaling based on custom metrics, enabling enterprises to scale the runtimes based on request count, error rate, requests in the pipeline and more.
Software Architect/ Associate Director, WSO2
Amila De Silva is a Software Architect/Associate Director in the WSO2 API Manager team. He is also a member of the architecture team that overlooks research and development teams and drives innovation for WSO2 products. He has been a technical consultant specializing in enterprise integration technologies and middleware solutions. Amila has also designed solutions for Telcos.
Software Engineer, WSO2
Renuka Fernando is a Software Engineer in the WSO2 API Manager team. Renuka has experience with working in cloud technologies such as Docker, Kubernetes. His main focus is on research and development of WSO2 K8s API Operator.
