You’ve set up a web application to run on Kubernetes, but how will you make sure that you’re getting the maximum performance from your infrastructure and allocating the optimal resources to each microservice? What about tuning the microservices themselves? Can Kubernetes, the application, and the infrastructure, all be tuned in concert to meet the required performance SLA at scale?
Watch an in-depth session together with BlazeMeter where we discuss how to automate the process of tuning system parameters such as the resources in Kubernetes, and the number of worker threads in a web server.
- The basics of automatic static performance tuning
- Best practices for creating a load test for the purpose of performance tuning
- How to prepare and run automatic optimization using Concertio’s Optimizer Studio
- Demo of automatically optimizing a Kubernetes cluster that runs on Google Cloud, with Magento, Apache web server, Blazemeter and Optimizer Studio