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Google Associate-Cloud-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Deploying and implementing a cloud solution	25%	- Deploying and implementing data solutions 1. Set up data processing pipelines 2. Provision databases - Deploying and implementing serverless resources 1. Deploy Cloud Run services 2. Create Cloud Functions - Deploying and implementing Google Kubernetes Engine resources 1. Deploy workloads 2. Configure networking for GKE 3. Create and manage clusters - Deploying and implementing Compute Engine resources 1. Create managed instance groups 2. Launch virtual machines 3. Manage images and snapshots 4. Configure access and security
Planning and configuring a cloud solution	17.5%	- Planning and configuring storage resources 1. Select storage classes 2. Plan data durability and availability - Planning and configuring compute resources 1. Select compute options 2. Plan data storage solutions 3. Choose storage options 4. Plan instance configuration - Planning and configuring network resources 1. Design VPC networks 2. Choose load balancing options 3. Plan firewall rules 4. Plan hybrid connectivity
Ensuring successful operation of a cloud solution	20%	- Managing resources 1. Scale resources 2. Update configurations 3. Troubleshoot common issues - Monitoring and logging 1. Use Cloud Monitoring 2. Set up alerts 3. Use Cloud Logging - Managing cost and performance 1. Optimize resource usage 2. Analyze cost reports
Setting up a cloud solution environment	20%	- Managing billing configuration 1. Configure billing exports 2. Create and manage billing accounts 3. Link projects to billing accounts 4. Set budgets and alerts - Setting up cloud projects and accounts 1. Apply organizational policies 2. Create resource hierarchy 3. Manage quotas and limits 4. Manage users and groups 5. Enable APIs 6. Manage IAM roles and permissions
Configuring access and security	17.5%	- Configuring network security 1. Configure private access 2. Secure VPC networks 3. Manage security controls - Managing data security 1. Enable encryption 2. Manage access to data - Managing IAM 1. Manage service accounts 2. Define roles and permissions 3. Implement least privilege access

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Google Associate Cloud Engineer Exam Sample Questions (Q380-Q385):

NEW QUESTION # 380
Your security team has been reluctant to move to the cloud because they don't have the level of network visibility they're used to. Which feature might help them to gain insights into your Google Cloud network?

A. Subnets
B. Firewall rules
C. Flow logs
D. Routes

Answer: C

NEW QUESTION # 381
You have files in a Cloud Storage bucket that you need to share with your suppliers. You want to restrict the time that the files are available to your suppliers to 1 hour. You want to follow Google recommended practices. What should you do?

A. Create a service account with just the permissions to access files in the bucket. Create a JSON key for the service account. Execute the command gsutil signurl -d 1h gs:///**.
B. Create a service account with just the permissions to access files in the bucket. Create a JSON key for the service account. Execute the command gsutil signurl -m 1h gs:///*.
C. Create a JSON key for the Default Compute Engine Service Account. Execute the command gsutil signurl -t 60m gs:///***
D. Create a service account with just the permissions to access files in the bucket. Create a JSON key for the service account. Execute the command gsutil signurl -p 60m gs:///.

Answer: A

Explanation:
This command correctly specifies the duration that the signed url should be valid for by using the -d flag. The default is 1 hour so omitting the -d flag would have also resulted in the same outcome. Times may be specified with no suffix (default hours), or with s = seconds, m = minutes, h = hours, d = days. The max duration allowed is 7d. Ref: https://cloud.google.com/storage/docs/gsutil/commands/signurl

NEW QUESTION # 382
You manage an App Engine Service that aggregates and visualizes data from BigQuery. The application is deployed with the default App Engine Service account. The data that needs to be visualized resides in a different project managed by another team. You do not have access to this project, but you want your application to be able to read data from the BigQuery dataset. What should you do?

A. In Cloud IAM of your project, ensure that the default App Engine service account has the role of BigQuery Data Viewer.
B. Ask the other team to grant your default App Engine Service account the role of BigQuery Job User.
C. In Cloud IAM of your project, grant a newly created service account from the other team the role of BigQuery Job User in your project.
D. Ask the other team to grant your default App Engine Service account the role of BigQuery Data Viewer.

Answer: D

Explanation:
Explanation
The resource that you need to get access is in the other project.
roles/bigquery.dataViewer BigQuery Data Viewer
When applied to a table or view, this role provides permissions to:
Read data and metadata from the table or view.
This role cannot be applied to individual models or routines.
When applied to a dataset, this role provides permissions to:
Read the dataset's metadata and list tables in the dataset.
Read data and metadata from the dataset's tables.
When applied at the project or organization level, this role can also enumerate all datasets in the project.
Additional roles, however, are necessary to allow the running of jobs.

NEW QUESTION # 383
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. 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 nodeSelectorto their pod specification.
B. Create your own Kubernetes cluster on top of Compute Engine with nodes that have GPUs.
Dedicate this cluster to your ML team.
C. Recreate all the nodes of the GKE cluster to enable GPUs on all of them.
D. Ask your ML team to add the "accelerator: gpu" annotation to their pod specification.

Answer: A

Explanation:
Before using GPUs on GKE, keep in mind the following limitations:
You cannot add GPUs to existing node pools.
GPU nodes cannot be live migrated during maintenance events.
https://cloud.google.com/kubernetes-engine/docs/how-to/gpus

NEW QUESTION # 384
Your coworker has helped you set up several configurations for gcloud. You've noticed that you're running commands against the wrong project. Being new to the company, you haven't yet memorized any of the projects. With the fewest steps possible, what's the fastest way to switch to the correct configuration?

A. Run gcloud configurations list followed by gcloud configurations activate .
B. Run gcloud config configurations list followed by gcloud config configurations activate.
C. Run gcloud config list followed by gcloud config activate.
D. Re-authenticate with the gcloud auth login command and select the correct configurations on login.

Answer: B

NEW QUESTION # 385
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