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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q60-Q65):

NEW QUESTION # 60
You are using Data Studio to visualize a table from your data warehouse that is built on top of BigQuery. Data is appended to the data warehouse during the day. At night, the daily summary is recalculated by overwriting the table. You just noticed that the charts in Data Studio are broken, and you want to analyze the problem. What should you do?

A. In Cloud Logging create a filter for your Data Studio report
B. Use the BigQuery interface to review the nightly Job and look for any errors
C. Use Cloud Debugger to find out why the data was not refreshed correctly
D. Review the Error Reporting page in the Cloud Console to find any errors.

Answer: B

Explanation:
https://cloud.google.com/bigquery/docs/managing-jobs#view-job.
Cloud Debugger is for inspecting apps: https://cloud.google.com/debugger/docs.

NEW QUESTION # 61
You have created a Kubernetes deployment, called Deployment-A, with 3 replicas on your cluster. Another deployment, called Deployment-B, needs access to Deployment-A. You cannot expose Deployment-A outside of the cluster. What should you do?

A. Create a Service of type ClusterIP for Deployment A. Have Deployment B use the Service IP address.
B. Create a Service of type LoadBalancer for Deployment A. Have Deployment B use the Service IP address.
C. Create a Service of type LoadBalancer for Deployment A and an Ingress Resource for that Service. Have Deployment B use the Ingress IP address.
D. Create a Service of type NodePort for Deployment A and an Ingress Resource for that Service.
Have Deployment B use the Ingress IP address.

Answer: A

Explanation:
A is not correct because this exposes Deployment A over the public internet.
B is not correct because LoadBalancer will expose the service publicly.
C is not correct because this exposes the service externally using a cloud provider's load balancer, and Ingress can work only with nodeport, not LoadBalancer.
D is correct because this exposes the service on a cluster-internal IP address. Choosing this method makes the service reachable only from within the cluster.
https://kubernetes.io/docs/concepts/services-networking/service/

NEW QUESTION # 62
You have an application that uses Cloud Spanner as a database backend to keep current state information about users. Cloud Bigtable logs all events triggered by users. You export Cloud Spanner data to Cloud Storage during daily backups. One of your analysts asks you to join data from Cloud Spanner and Cloud Bigtable for specific users. You want to complete this ad hoc request as efficiently as possible. What should you do?

A. Create a dataflow job that copies data from Cloud Bigtable and Cloud Spanner for specific users.
B. Create a Cloud Dataproc cluster that runs a Spark job to extract data from Cloud Bigtable and Cloud Storage for specific users.
C. Create two separate BigQuery external tables on Cloud Storage and Cloud Bigtable. Use the BigQuery console to join these tables through user fields, and apply appropriate filters.
D. Create a dataflow job that copies data from Cloud Bigtable and Cloud Storage for specific users.

Answer: C

Explanation:
Explanation
"The Cloud Spanner to Cloud Storage Text template is a batch pipeline that reads in data from a Cloud Spanner table, optionally transforms the data via a JavaScript User Defined Function (UDF) that you provide, and writes it to Cloud Storage as CSV text files."
https://cloud.google.com/dataflow/docs/guides/templates/provided-batch#cloudspannertogcstext
"The Dataflow connector for Cloud Spanner lets you read data from and write data to Cloud Spanner in a Dataflow pipeline"
https://cloud.google.com/spanner/docs/dataflow-connector
https://cloud.google.com/bigquery/external-data-sources

NEW QUESTION # 63
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. Ask the other team to grant your default App Engine Service account the role of BigQuery Job User.
B. In Cloud IAM of your project, ensure that the default App Engine service account has the role of BigQuery Data Viewer.
C. Ask the other team to grant your default App Engine Service account the role of BigQuery Data Viewer.
D. 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.

Answer: C

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 # 64
Your company runs its Linux workloads on Compute Engine instances. Your company will be working with a new operations partner that does not use Google Accounts. You need to grant access to the instances to your operations partner so they can maintain the installed tooling.
What should you do?

A. Ask the operations partner to generate SSH key pairs, and add the public keys to the VM instances.
B. Tag all the instances with the same network tag.
Create a firewall rule in the VPC to grant TCP access on port 22 for traffic from the operations partner to instances with the network tag.
C. Enable Cloud IAP for the Compute Engine instances, and add the operations partner as a Cloud IAP Tunnel User.
D. Set up Cloud VPN between your Google Cloud VPC and the internal network of the operations partner.

Answer: C

Explanation:
To control which users and groups are allowed to use IAP TCP forwarding and which VM instances they're allowed to connect to, configure Identity and Access Management (IAM) permissions.
How to:
Open the IAP admin page and select the SSH and TCP Resources tab.
Open the IAP admin page
Select the VM instances that you want to configure.
Click Show info panel if the info panel is not visible.
Click Add member and configure the following:
New members: Specify the user or group you want to grant access.
Select a role Select Cloud IAP > IAP-Secured Tunnel User.
https://cloud.google.com/iap/docs/using-tcp-forwarding#grant-permission

NEW QUESTION # 65
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