Brien Posey August 9, 2017
Kubernetes is designed to address some of the difficulties that are inherent in managing large-scale containerized environments. However, this doesn’t mean Kubernetes can scale in all situations all on its own. There are steps you can and should take to maximize Kubernetes’ ability to scale—and there are important caveats and limitations to keep in mind when scaling Kubernetes. I’ll explain them in this article.
Gord Sissons May 18, 2017
In Kubernetes, we often hear terms like resource management, scheduling and load balancing. While Kubernetes offers many capabilities, understanding these concepts is key to appreciating how workloads are placed, managed and made resilient. In this short article, I provide an overview of each facility, explain how they are implemented in Kubernetes, and how they interact with one another to provide efficient management of containerized workloads. If you’re new to Kubernetes and seeking to learn the space, please consider reading our case for Kubernetes article.
Resource management is all about the efficient allocation of infrastructure resources. In Kubernetes, resources are things that can be requested by, allocated to, or consumed by a container or pod. Having a common resource management model is essential, since many components in Kubernetes need to be resource aware including the scheduler, load balancers, worker-pool managers and even applications themselves. If resources are underutilized, this translates into waste and cost-inefficiency. If resources are over-subscribed, the result can be application failures, downtime, or missed SLAs. Read more