Google Associate-Cloud-Engineer資格認証攻略 & Associate-Cloud-Engineer復習内容

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Google Associate-Cloud-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Ensuring successful operation of a cloud solution | 20% | - Managing cost and performance
- 1. Analyze cost reports
- 2. Optimize resource usage
- Managing resources
- 1. Troubleshoot common issues
- 2. Update configurations
- 3. Scale resources
- Monitoring and logging
- 1. Use Cloud Monitoring
- 2. Use Cloud Logging
- 3. Set up alerts
|
| Setting up a cloud solution environment | 20% | - Setting up cloud projects and accounts
- 1. Manage quotas and limits
- 2. Create resource hierarchy
- 3. Manage IAM roles and permissions
- 4. Manage users and groups
- 5. Enable APIs
- 6. Apply organizational policies
- Managing billing configuration
- 1. Set budgets and alerts
- 2. Create and manage billing accounts
- 3. Link projects to billing accounts
- 4. Configure billing exports
|
| Deploying and implementing a cloud solution | 25% | - Deploying and implementing Google Kubernetes Engine resources
- 1. Deploy workloads
- 2. Create and manage clusters
- 3. Configure networking for GKE
- Deploying and implementing serverless resources
- 1. Create Cloud Functions
- 2. Deploy Cloud Run services
- Deploying and implementing Compute Engine resources
- 1. Manage images and snapshots
- 2. Launch virtual machines
- 3. Create managed instance groups
- 4. Configure access and security
- Deploying and implementing data solutions
- 1. Provision databases
- 2. Set up data processing pipelines
|
| Configuring access and security | 17.5% | - Configuring network security
- 1. Configure private access
- 2. Manage security controls
- 3. Secure VPC networks
- 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
|
| Planning and configuring a cloud solution | 17.5% | - Planning and configuring storage resources
- 1. Plan data durability and availability
- 2. Select storage classes
- 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 compute resources
- 1. Plan data storage solutions
- 2. Plan instance configuration
- 3. Choose storage options
- 4. Select compute options
|
>> Google Associate-Cloud-Engineer資格認証攻略 <<
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Google Associate Cloud Engineer Exam 認定 Associate-Cloud-Engineer 試験問題 (Q292-Q297):
質問 # 292
Your company has a large quantity of unstructured data in different file formats. You want to perform ETL transformations on the dat a. You need to make the data accessible on Google Cloud so it can be processed by a Dataflow job. What should you do?
- A. Upload the data to Cloud Storage using the gsutil command line tool.
- B. Upload the data into Cloud SQL using the import function in the console.
- C. Upload the data into Cloud Spanner using the import function in the console.
- D. Upload the data to BigQuery using the bq command line tool.
正解:A
解説:
"large quantity" : Cloud Storage or BigQuery "files" a file is nothing but an Object
質問 # 293
You are using the gcloud container clusters create app-cluster command to deploy a Google Kubernetes Engine (GKE) cluster in a new Google Cloud project. The command fails with the following error:
ERROR: (gcloud.container.clusters.create) ResponseError: code=403, message=Kubernetes Engine API has not been used in the project before or it is disabled.
You need to resolve the issue. What should you do?
- A. Run the gcloud services enable container.googleapis.com command, and then run the cluster creation command again.
- B. Disable the " Require enabling Workload Identity Federation for GKE " organization policy, and then run the cluster creation command again.
- C. Rerun the command with the --enable-autoprovisioning flag.
- D. Add the Kubernetes Engine Admin IAM role to your user account, and then run the cluster creation command again.
正解:A
解説:
The correct answer is A because the error explicitly says that the Kubernetes Engine API has not been used before or is disabled in the project. Google Cloud services must be enabled before their APIs can be used, even when the user has sufficient IAM permissions. The command gcloud services enable container.googleapis.com enables the GKE API for the selected project. After that, the original cluster creation command can be rerun. Disabling a Workload Identity Federation organization policy is unrelated to this API-disabled error. The --enable-autoprovisioning flag configures node auto- provisioning and does not enable the GKE API. Adding Kubernetes Engine Admin permissions may be necessary for authorization, but it does not solve a disabled API condition.
質問 # 294
During a recent audit of your existing Google Cloud resources, you discovered several users with email addresses outside of your Google Workspace domain.
You want to ensure that your resources are only shared with users whose email addresses match your domain. You need to remove any mismatched users, and you want to avoid having to audit your resources to identify mismatched users. What should you do?
- A. Create a Cloud Scheduler task to regularly scan your projects and delete mismatched users.
- B. Set an organizational policy constraint to limit identities by domain to automatically remove mismatched users.
- C. Set an organizational policy constraint to limit identities by domain, and then retroactively remove the existing mismatched users.
- D. Create a Cloud Scheduler task to regularly scan your resources and delete mismatched users.
正解:C
解説:
https://cloud.google.com/resource-manager/docs/organization-policy/org-policy-constraints This list constraint defines the set of domains that email addresses added to Essential Contacts can have. By default, email addresses with any domain can be added to Essential Contacts. The allowed/denied list must specify one or more domains of the form @example.com. If this constraint is active and configured with allowed values, only email addresses with a suffix matching one of the entries from the list of allowed domains can be added in Essential Contacts. This constraint has no effect on updating or removing existing contacts. constraints/essentialcontacts.allowedContactDomains
質問 # 295
You are the team lead of a group of 10 developers. You provided each developer with an individual Google Cloud Project that they can use as their personal sandbox to experiment with different Google Cloud solutions. You want to be notified if any of the developers are spending above $500 per month on their sandbox environment. What should you do?
- A. Create a single budget for all projects and configure budget alerts on this budget.
- B. Create a budget per project and configure budget alerts on all of these budgets.
- C. Create a single billing account for all sandbox projects and enable BigQuery billing exports. Create a Data Studio dashboard to plot the spending per project.
- D. Create a separate billing account per sandbox project and enable BigQuery billing exports. Create a Data Studio dashboard to plot the spending per billing account.
正解:B
解説:
Set budgets and budget alerts Overview Avoid surprises on your bill by creating Cloud Billing budgets to monitor all of your Google Cloud charges in one place. A budget enables you to track your actual Google Cloud spend against your planned spend. After you've set a budget amount, you set budget alert threshold rules that are used to trigger email notifications. Budget alert emails help you stay informed about how your spend is tracking against your budget. 2. Set budget scope Set the budget Scope and then click Next. In the Projects field, select one or more projects that you want to apply the budget alert to. To apply the budget alert to all the projects in the Cloud Billing account, choose Select all. https://cloud.google.com/billing/docs/how-to
/budgets#budget-scop
Reference: https://cloud.google.com/billing/docs/how-to/budgets
質問 # 296
You have a large 5-TB AVRO file stored in a Cloud Storage bucket. Your analysts are proficient only in SQL and need access to the data stored in this file. You want to find a cost-effective way to complete their request as soon as possible. What should you do?
- A. Create a Hadoop cluster and copy the AVRO file to NDFS by compressing it. Load the file in a hive table and provide access to your analysts so that they can run SQL queries.
- B. Create a BigQuery table and load data in BigQuery. Run a SQL query on this table and drop this table after you complete your request.
- C. Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request.
- D. Load data in Cloud Datastore and run a SQL query against it.
正解:C
解説:
https://cloud.google.com/bigquery/external-data-sources
An external data source is a data source that you can query directly from BigQuery, even though the data is not stored in BigQuery storage.
BigQuery supports the following external data sources:
Amazon S3
Azure Storage
Cloud Bigtable
Cloud Spanner
Cloud SQL
Cloud Storage
Drive
質問 # 297
......
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