https://cloud.google.com/logging/docs/api/v2/resource-list
GKE Containers have more log than GKE Cluster Operations:
.-GKE Containe:
cluster_name: An immutable name for the cluster the container is running in.
namespace_id: Immutable ID of the cluster namespace the container is running in.
instance_id: Immutable ID of the GCE instance the container is running in.
pod_id: Immutable ID of the pod the container is running in.
container_name: Immutable name of the container.
zone: The GCE zone in which the instance is running.
VS
.-GKE Cluster Operations
project_id: The identifier of the GCP project associated with this resource, such as "my-project".
cluster_name: The name of the GKE Cluster.
location: The location in which the GKE Cluster is running.

Reference: https://cloud.google.com/resource-manager/docs/access-control-proj The primitive role roles/viewer provides read access to all resources in the project. The permissions in this role are limited to Get and list access for all resources. As we have an out of the box role that exactly fits our requirement, we should use this.
Ref: https://cloud.google.com/resource-manager/docs/access-control-proj It is advisable to use the existing GCP provided roles over creating custom roles with similar permissions as this becomes a maintenance overhead. If GCP modifies how permissions are handled or adds/removes permissions, the default GCP provided roles are automatically updated by Google whereas if they were custom roles, the responsibility is with us and this adds to the operational overhead and needs to be avoided.

Reference: https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed
https://cloud.google.com/appengine/docs/standard/go/config/appref
"App Engine calculates the number of instances necessary to serve your current application traffic based on scaling settings such as target_cpu_utilization and target_throughput_utilization. Setting min_idle_instances specifies the number of instances to run in addition to this calculated number. For example, if App Engine calculates that 5 instances are necessary to serve traffic, and min_idle_instances is set to 2, App Engine will run 7 instances (5, calculated based on traffic, plus 2 additional per min_idle_instances)." Automatic scaling creates dynamic instances based on request rate, response latencies, and other application metrics. However, if you specify the number of minimum idle instances, that specified number of instances run as resident instances while any additional instances are dynamic.
Ref: https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed