Version 1.14. This version is no longer supported. For information about how to upgrade to version 1.15, see Upgrading Anthos on bare metal in the 1.15 documentation. For more information about supported and unsupported versions, see the Version history page in the latest documentation.
This page provides basic scaling information for VMs running on
Google Distributed Cloud. The information provided doesn't indicate hard limits
or guaranteed thresholds for the product or your installation. The information
is intended to help you determine whether VM Runtime on Google Distributed Cloud can meet
your computing requirements.
For information about quotas, limits, and scaling for Google Distributed Cloud,
see Quotas and limits.
Maximum VM scaling
We have determined through extensive testing that you can run reliably as many
as 500 VMs concurrently on an GKE cluster with 50 nodes.
Resource usage
To scale up VM deployments, make sure there are enough CPU, memory, and storage
resources in the cluster for both VMs and the control plane components. For
standard resource requirements for cluster node machines, see
Cluster node machine prerequisites.
Note the following VM Runtime on Google Distributed Cloud resource usage for our maximum VM
scaling configuration:
Total CPU share used by all the components in the vm-system namespace is
approximately 1.3 at the peak usage.
Total memory consumed by all the components in the vm-system namespace is
approximately 10 GiB.
Known resource issue
Currently, when the guest agent is enabled,
each VM registers a separate watcher to the API server. Therefore, the number of registered watchers in kube-apiserver increases linearly with the number of the VMs. Depending on the workloads you run, you may
encounter issues related to kube-apiserver as the number of VMs increases. If
you're affected by this issue, you can configure the kube-apiserver or
disable the guest agent if
you aren't using it.
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