Fairwinds, a cloud-native infrastructure solutions provider, announced today the availability of Fairwinds Goldilocks, an open source tool for Kubernetes resource management.
The company says Goldilocks takes the guesswork out of setting resource requests and limits on applications running in Kubernetes production deployments, helping to optimize resource utilization and ensure that applications run correctly.
The Goldilocks software is available now via an open source download.
Fairwinds Goldilocks Features
Resource requests and limits are used in Kubernetes to control CPU and memory resources, and they ensure that workloads are scheduled on nodes that can properly support the application.
- Requests define the resources that a container is guaranteed
- Limits refer to a setting at which resources will be restricted
Requests must be set so that applications have enough CPU and memory to run as expected; at the same time, limits must be set to ensure that applications are not taking up more than their share of resources to the detriment of other applications.
Kubernetes provides the ability to set default Namespace settings for requests and limits, but to ensure clusters remain stable, settings should match the unique requirements of each application, says the company.
“Today, Kubernetes users have no easy way to determine the resource requests and limits for their workload and often don’t set them at all. This can lead to issues with cluster stability,” said EJ Etherington, CTO at Fairwinds.
“With our latest open source tool we make it easy to empirically determine those values anytime a new application is deployed into a cluster saving you time, and improving resource utilization and cluster stability.”
Fairwinds Goldilocks is a dashboard that surfaces data from Kubernetes’ Vertical Pod Autoscaler (VPA), which monitors the usage of pods, to make recommendations for setting resource requests and limits.
Users can access a service in the cluster and the dashboard will provide two types of recommendations, depending on the QoS class desired.
QoS classes in Kubernetes resource management have three levels: guaranteed means that the application will be scheduled on a node where resources will be assured; burstable means that the application will be guaranteed a minimum level of resources but will be given more if and when available; best effort, which is not recommended, means that no requests or limits are set and the application will only be allocated resources when all other requests are met.