This is the email I've received a few days ago:<p>Hello Google Kubernetes Engine Customer,<p>We are writing to let you know that as part of ensuring better representation of available resources on the node for e2 burstable node types, Google Kubernetes Engine (GKE) has decided to reduce the allocatable CPU resources available to schedule user workloads (known as the node allocatable resources) on e2-micro, e2-small, and e2-medium machine types.<p>What do I need to know?<p>Today, e2-micro, e2-small and e2-medium have 1930 mCPU of allocatable resources for Kubernetes to schedule Pods on per node, and following this change, it will be 940mCPU. Kubernetes uses the node allocatable resources during scheduling to decide how many Pods it should place on the node. If your workloads are currently requesting more CPU resources than what will be available after upgrading, they may become unscheduled after upgrade.<p>We are making this change in order to more accurately represent the resources available in these machine types. These machine types can temporarily burst to 2 vCPUs as documented, but this is not sustained. Note that the underlying compute capabilities and resources are not changing, the machines retain the ability to temporarily burst to 2 vCPU, this change only affects how many resources the Kubernetes scheduler considers when allocating Pods to nodes.<p>When your cluster is upgraded to 1.16.8-gke.17 or 1.17.5-gke.5 or later (whether you perform this manually or you are automatically upgraded), your workloads may become unscheduled if there are not enough allocatable resources in the cluster.