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Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

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Google Associate Cloud Engineer Exam Sample Questions (Q368-Q373):

NEW QUESTION # 368
An employee was terminated, but their access to Google Cloud Platform (GCP) was not removed until 2 weeks later. You need to find out this employee accessed any sensitive customer information after their termination. What should you do?

A. View Data Access audit logs in Stackdriver. Search for the user's email as the principal.
B. View System Event Logs in Stackdriver. Search for the service account associated with the user.
C. View System Event Logs in Stackdriver. Search for the user's email as the principal.
D. View the Admin Activity log in Stackdriver. Search for the service account associated with the user.

Answer: A

Explanation:
https://cloud.google.com/logging/docs/audit
Data Access audit logs Data Access audit logs contain API calls that read the configuration or metadata of resources, as well as user-driven API calls that create, modify, or read user-provided resource data.
https://cloud.google.com/logging/docs/audit#data-access

NEW QUESTION # 369
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 dataViewer user 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 jobUser role to the group.
C. 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.
D. 1. Create an IAM entry for each data scientist ' s user account.2. Assign the BigQuery jobUser role to the group.

Answer: B

Explanation:
Read the dataset ' s metadata and to 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.
BigQuery Data Viewer
(roles/bigquery.dataViewer)
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.
Lowest-level resources where you can grant this role:
Table
View
BigQuery Job User
(roles/bigquery.jobUser)
Provides permissions to run jobs, including queries, within the project.
Lowest-level resources where you can grant this role:
Project
to run jobs https://cloud.google.com/bigquery/docs/access-control#bigquery.jobUser databaseUser needs additional role permission to run jobshttps://cloud.google.com/spanner/docs/iam#spanner.databaseUser

NEW QUESTION # 370
You manage three Google Cloud projects with the Cloud Monitoring API enabled. You want to follow Google-recommended practices to visualize CPU and network metrics for all three projects together. What should you do?

A. 1. Create a fourth Google Cloud project
2. Create a Cloud Workspace from the fourth project and add the other three projects
B. 1 Create a Service Account and apply roles/viewer on the three projects
2. Collect metrics and publish them lo the Cloud Monitoring API
3. Add CPU and network Charts for each of the three projects.
C. 1. Create a Cloud Monitoring Dashboard
2. Collect metrics and publish them into the Pub/Sub topics
3. Add CPU and network Charts (or each of (he three projects
D. 1. Create a Cloud Monitoring Dashboard.
2. Select the CPU and Network metrics from the three projects.
3. Add CPU and network Charts lot each of the three protects.

Answer: D

NEW QUESTION # 371
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. Use the BigQuery interface to review the nightly Job and look for any errors
B. Review the Error Reporting page in the Cloud Console to find any errors.
C. In Cloud Logging create a filter for your Data Studio report
D. Use Cloud Debugger to find out why the data was not refreshed correctly

Answer: D

NEW QUESTION # 372
Your company has workloads running on Compute Engine and on-premises. The Google Cloud Virtual Private Cloud (VPC) is connected to your WAN over a Virtual Private Network (VPN). You need to deploy a new Compute Engine instance and ensure that no public Internet traffic can be routed to it. What should you do?

A. Create the instance without a public IP address.
B. Create a deny-all egress firewall rule on the VPC network.
C. Create a route on the VPC to route all traffic to the instance over the VPN tunnel.
D. Create the instance with Private Google Access enabled.

Answer: D

Explanation:
Get private access to Google services, such as storage, big data, analytics, or machine learning, without having to give your service a public IP address.
Reference: https://cloud.google.com/vpc

NEW QUESTION # 373
......

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