The quest for resilience and agility has driven us into the modern age of microservices. Bringing services to market on a microservice architecture demands utilization of sprawling technology offerings and tooling. While daunting at first glance, we can break down the process into 3 major categories: In this hands on series, we will use.

Still waiting for ML training to be over? Tired of running experiments manually? Not sure how to reproduce results? Wasting too much of your time on devops and data wrangling? Spending lots of time tinkering around with data science is okay if you’re a hobbyist, but data science models are meant to be incorporated into real business applications. Businesses won’t invest in data science if they don’t see a positive ROI.

ContainIQ runs all infrastructure on Google Cloud (GKE), and was able to get Speedscale installed within a few minutes. After installing the Speedscale operator, ContainIQ began capturing traffic from the primary gateway where service calls come into a cluster.

Why this combination you ask? Load testing is my passion, and I am partial to Kubernetes. I challenged myself to share a use case that many could relate to, focused on a business critical application. Websites came to mind and WordPress is the world’s most popular website management system. Of course, nginx is the most popular web server so let’s throw that into the mix. And Kubernetes? With more than 50% of corporations adopting Kubernetes in 2021, what better system to run in.