In this blog post we use podtato-head to demonstrate how to load test kubernetes microservices and how Speedscale can help understand the relationships between them. No, that's not a typo, podtato-head is an example microservices app from the CNCF Technical Advisory Group for Application Delivery, along with instructions on how to deploy it in numerous different ways. There are more than 10 delivery examples, you will surely learn something by going through the project. We liked it so much we forked the repo to contribute our improvements.
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.