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Google Associate-Cloud-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Configuring access and security	15%	- Managing IAM roles and permissions - Securing data and services
Topic 2: Setting up a cloud solution environment	20%	- Setting up cloud projects and accounts - Managing billing and identity access
Topic 3: Planning and configuring a cloud solution	25%	- Configuring storage and database solutions - Configuring compute resources
Topic 4: Ensuring successful operation of a cloud solution	20%	- Monitoring and logging - Managing cloud resources
Topic 5: Deploying and implementing a cloud solution	20%	- Deploying applications and services - Implementing networking components

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Google Associate Cloud Engineer Exam Sample Questions (Q240-Q245):

NEW QUESTION # 240
You have an application that runs on Compute Engine VM instances in a custom Virtual Private Cloud (VPC). Your company's security policies only allow the use of internal IP addresses on VM instances and do not let VM instances connect to the internet. You need to ensure that the application can access a file hosted in a Cloud Storage bucket within your project. What should you do?

A. Deploy a Cloud NAT instance and route the traffic to the dedicated IP address of the Cloud Storage bucket.
B. Add storage.googleapis.com to the list of restricted services in a VPC Service Controls perimeter and add your project to the list of protected projects.
C. Enable Private Service Access on the Cloud Storage Bucket.
D. Enable Private Google Access on the subnet within the custom VPC.

Answer: D

Explanation:
Private Google Access lets you connect VM instances to GCP services without external IP addresses and only internal. A is wrong because even though Private Services Access lets you also access GCP and other services through internal IPs, it also allows the VMs to have external IPs.
https://cloud.google.com/vpc/docs/private-google-access

NEW QUESTION # 241
Your company has a Google Cloud Platform project that uses BigQuery for data warehousing. Your data science team changes frequently and has few members. You need to allow members of this team to perform queries. You want to follow Google-recommended practices. What should you do?

A. 1. Create an IAM entry for each data scientist's user account.
2. Assign the BigQuery jobUser role to the group.
B. 1. Create a dedicated Google group in Cloud Identity.
2. Add each data scientist's user account to the group.
3. Assign the BigQuery dataViewer user role to the group.
C. 1. Create an IAM entry for each data scientist's user account.
2. Assign the BigQuery dataViewer user role to the group.
D. 1. Create a dedicated Google group in Cloud Identity.
2. Add each data scientist's user account to the group.
3. Assign the BigQuery jobUser role to the group.

Answer: B

Explanation:
Explanation/Reference: https://cloud.google.com/bigquery/docs/cloud-sql-federated-queries

NEW QUESTION # 242
Your company is seeking a scalable solution to retain and explore application logs hosted on Compute Engine. You must be able to analyze your logs with SQL queries, and you want to be able to create charts to identify patterns and trends in your logs over time. You want to follow Google-recommended practices and minimize your operational costs. What should you do?

A. Use a custom script to push your application logs to BigQuery for exploration.
B. Use a custom script to push your application logs to Cloud SQL for exploration.
C. Ingest your application logs to Cloud Logging by using Ops Agent, and explore your logs in Logs Explorer.
D. Ingest your application logs to Cloud Logging by using Ops Agent, and explore your logs with Log Analytics.

Answer: D

Explanation:
Ingesting your application logs to Cloud Logging using the Ops Agent and exploring the logs with Log Analytics is the recommended solution. This approach leverages Cloud Logging's built-in capabilities for querying logs with SQL-like syntax and allows you to visualize trends over time, all while minimizing operational costs. Log Analytics provides a powerful interface for log exploration and analysis.

NEW QUESTION # 243
You are operating a Google Kubernetes Engine (GKE) cluster for your company where different teams can run non-production workloads. Your Machine Learning (ML) team needs access to Nvidia Tesla P100 GPUs to train their models. You want to minimize effort and cost. What should you do?

A. Recreate all the nodes of the GKE cluster to enable GPUs on all of them.
B. Create your own Kubernetes cluster on top of Compute Engine with nodes that have GPUs. Dedicate this cluster to your ML team.
C. Add a new, GPU-enabled, node pool to the GKE cluster. Ask your ML team to add the cloud.google.com/gke -accelerator: nvidia-tesla-p100 nodeSelector to their pod specification.
D. Ask your ML team to add the "accelerator: gpu" annotation to their pod specification.

Answer: C

Explanation:
Explanation
This is the most optimal solution. Rather than recreating all nodes, you create a new node pool with GPU enabled. You then modify the pod specification to target particular GPU types by adding node selector to your workloads Pod specification. YOu still have a single cluster so you pay Kubernetes cluster management fee for just one cluster thus minimizing the cost.Ref: https://cloud.google.com/kubernetes-engine/docs/how-to/gpusRef: https://cloud.google.com/kubernetes Example:
apiVersion: v1
kind: Pod
metadata:
name: my-gpu-pod
spec:
containers:
name: my-gpu-container
image: nvidia/cuda:10.0-runtime-ubuntu18.04
command: [/bin/bash]
resources:
limits:
nvidia.com/gpu: 2
nodeSelector:
cloud.google.com/gke-accelerator: nvidia-tesla-k80 # or nvidia-tesla-p100 or nvidia-tesla-p4 or nvidia-tesla-v100 or nvidia-tesla-t4

NEW QUESTION # 244
You are working with a user to set up an application in a new VPC behind a firewall. The user is concerned about data egress. You want to configure the fewest open egress ports. What should you do?

A. Set up a high-priority (1000) rule that blocks all egress and a low-priority (65534) rule that allows only the appropriate ports.
B. Set up a low-priority (65534) rule that blocks all egress and a high-priority rule (1000) that allows only the appropriate ports.
C. Set up a high-priority (1000) rule to allow the appropriate ports.
D. Set up a high-priority (1000) rule that pairs both ingress and egress ports.

Answer: B

Explanation:
Implied rules
Every VPC network has two implied firewall rules. These rules exist, but are not shown in the Cloud Console:
Implied allow egress rule. An egress rule whose action is allow, destination is 0.0.0.0/0, and priority is the lowest possible (65535) lets any instance send traffic to any destination, except for traffic blocked by Google Cloud. A higher priority firewall rule may restrict outbound access.
Internet access is allowed if no other firewall rules deny outbound traffic and if the instance has an external IP address or uses a Cloud NAT instance. For more information, see Internet access requirements.
Implied deny ingress rule. An ingress rule whose action is deny, source is 0.0.0.0/0, and priority is the lowest possible (65535) protects all instances by blocking incoming connections to them. A higher priority rule might allow incoming access. The default network includes some additional rules that override this one, allowing certain types of incoming connections.
https://cloud.google.com/vpc/docs/firewalls#default_firewall_rules

NEW QUESTION # 245
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