Deep Dive into Your Kubernetes
The adoption of cloud computing introduces a number of new challenges and managing cloud waste is proving to be one of the most difficult. When using public cloud IaaS and PaaS, organizations are billed continuously as consumption occurs, instead of a once-off as it happens when they procure their data center capacity. In cloud computing, organizations are confronted with the difficulty of creating accurate cost estimates. They are often hit by bills that they apparently can’t explain and struggle to identify items that are responsible for the waste. As a result, financial management is often overlooked until spend is out of control.
Now enter Kubernetes. Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services. It has a large and rapidly growing ecosystem. Understanding where underutilization or waste is being generated from is even more difficult. When you try and run cost analysis on your Kubernetes, the bill doesn’t have any context about the workloads being orchestrated. When the financial team asks if there is any possibility to lower the Kubernetes cost, how do you handle that? How and where are you able to find Node waste or even Pod waste (underutilization)?
We have launched a new function that allows our users to “deep dive” into Kubernetes and understand within a Node where underutilization is occurring. Pileus understands how to find those underutilized components. Our proprietary algorithms are able to evaluate the utilization of each Cluster. Our Platform is enabled to look deep into induvial Pods. The multi “Group By” data set selection allows you to group by Namespace, Labels, Node, Instance Type, Linked Account and more. When you combine the Group By option with our powerful Filters you suddenly gain a granularity into your Kubernetes that no other platform provides.
Pileus recognizes that each organization might and usually does, set different parameters for utilization. Understanding this, we have included the option of applying custom weight metrics for each Node. It is possible to set the weight of the 3 cost drivers, CPU, Memory, and Network usage. This puts the control in the hands of the user and provides ultimate understanding of how the cost of that particular Node is derived. This enables you to adjust each specific Node in a custom way and reduce the spending.
Cost savings is one of the biggest drivers behind the adoption of the cloud. As companies increasingly adopt cloud-based technologies such as Kubernetes, to support efficient and agile operations, explaining the cost becomes crucial. Some are seeing unexpected costs grow. This happens for any number of reasons. A key reason is the inclination to pad application and infrastructure resource allocations. This is done in an effort to avoid instability in a dynamic cloud environment. Over-provisioning made sense with a traditional non-elastic infrastructure. However, cloud-native application orchestrators like Kubernetes have built-in features that allow systems to automatically respond to environmental changes. Over-provisioning CPU and memory incur costs that may not be necessary in the current day and age. Pileus is the platform that enables the discovery of underutilized resources.
On a finial note and a fun fact: The origin of the name Kubernetes (“koo-burr-NET-eez”) stems from the Greek, meaning helmsman or pilot.