Explanation:
Include the forwarder agent in a DaemonSet deployment. is the right answer
The one-pod-per-node approach is followed by DaemonSets in GKE, either across the entire cluster or only a selection of nodes. DaemonSets automatically add pods to new nodes when you add them to a node pool. Therefore, you may automate the installation and configuration of the Splunk forwarder agent on each GKE cluster node by configuring the pod to utilize the Splunk forwarder agent image and with some minimal design (for example, defining which logs need to be forwarded).
Explanation:
Gsutil provides object composition or parallel upload to handle the upload of larger files.
For big, local files you want to upload in parallel to cloud storage, the gsutil program can also automatically use object composition. A large file is divided into smaller bits, uploaded in parallel, then reconfigured once in the cloud (and deleted from the temporary components it created locally).
Explanation:
Edit the number of replicas in the YAML file and rerun the kubectl apply. kubectl apply -f app-deployment.yaml. is the right answer.
This one is the only method that ensures you use the desired state configuration. You may keep the Kubernetes cluster in its intended condition by modifying the YAML file to contain five replicas and applying it using Kubectl apply.
Explanation:
Using a cloud VPN, Google App Engine offers connectivity to on-premises systems. Subnetworks can be created within your Compute Engine network. By doing so, you can enable VPN scenarios like accessing corporate network databases.
Explanation:
Use gcloud to expand the IP range of the current subnet. is the right answer
The existing subnet's subnet mask is 255.255.255.240, which means that the maximum number of addresses that can be used is 16. Since there are 4 bits open in the network prefix of /28, or 2 to the power of 4, there are 16 IP addresses.
Explanation:
A decent storage choice with analysis capabilities is BigQuery. Additionally, ACLs and views can be used to limit access to the data. BigQuery manages project and dataset permissions via access control lists (ACLs). You can utilize BigQuery, a petabyte-scale analytics data warehouse, to execute SQL queries over enormous volumes of data almost instantly. In BigQuery, generating an authorized view also refers to granting a view access to a dataset. You can share query results with specific users and groups using an approved idea without giving them access to the underlying tables. You can limit which columns (fields) users can query using the SQL query for the view. You establish an authorized idea in this tutorial.
Explanation:
The project viewer gives the visibility that the security team requires while adhering to the principle of least privilege. Refer to Organization and Project Access Control in the GCP manual.