Associate-Cloud-Engineer Exam Dumps - Google Cloud Certified - Associate Cloud Engineer

Add the network tag allow-udp-636 to the VM instance running the LDAP server.

Create a route called allow-udp-636 and set the next hop to be the VM instance running the LDAP server.

Add a network tag of your choice to the instance. Create a firewall rule to allow ingress on UDP port 636 for that network tag.

Add a network tag of your choice to the instance running the LDAP server. Create a firewall rule to allow egress on UDP port 636 for that network tag.

Run a test using simulated maintenance events. If the test is successful, use preemptible N1 Standard VMs when running future jobs.

Run a test using simulated maintenance events. If the test is successful, use N1 Standard VMs when running future jobs.

Run a test using a managed instance group. If the test is successful, use N1 Standard VMs in the managed instance group when running future jobs.

Run a test using N1 standard VMs instead of N2. If the test is successful, use N1 Standard VMs when running future jobs.

Attach a public IP to the instances and allow incoming connections from the internet on port 22 for SSH.

Use a third party tool to provide remote access to the instances.

Use the gcloud compute ssh command with the --tunnel-through-iap flag. Allow ingress traffic from the IP range 35.235.240.0/20 on port 22.

Create a bastion host with public internet access. Create the SSH tunnel to the instance through the bastion host.

Create a Cloud Monitoring Workspace.

Create a VPC network in the project.

Enable the compute googleapis.com API.

Grant yourself the IAM role of Compute Admin.

Use your existing CI/CD pipeline Use the generated Docker images and deploy them to Cloud Run. Update the configurations and the required endpoints.

Use your existing continuous integration and delivery (CI/CD) pipeline. Use the generated Docker images and deploy them to Cloud Function. Use the same configuration as on-premises.

Use the existing codebase and deploy each service as a separate Cloud Function Update the configurations and the required endpoints.

Use your existing codebase and deploy each service as a separate Cloud Run Use the same configurations as on-premises.

Provision preemptible Compute Engine instances.

Provision Compute Engine instances with GPUs attached.

Provision Compute Engine instances with local SSDs attached.

Provision Compute Engine instances with M1 machine type.

Deploy the application on GKE, and add a HorizontalPodAutoscaler to the deployment.

Deploy the application on GKE, and add a VerticalPodAutoscaler to the deployment.

Create a GKE cluster with autoscaling enabled on the node pool. Set a minimum and maximum for the size of the node pool.

Create a separate node pool for each application, and deploy each application to its dedicated node pool.

Create a single custom VPC with 2 subnets. Create each subnet in a different region and with a different CIDR range.

Create a single custom VPC with 2 subnets. Create each subnet in the same region and with the same CIDR range.

Create 2 custom VPCs, each with a single subnet. Create each subnet is a different region and with a different CIDR range.

Create 2 custom VPCs, each with a single subnet. Create each subnet in the same region and with the same CIDR range.