Associate-Cloud-Engineer試験問題集を使って一日でGoogle Cloud Certified試験合格目指す（最新の328解答)
Associate-Cloud-Engineer試験正確な問題集、学習ノートと理論
Google Associate-Cloud-Engineer認定を取得するには、候補者はGCPインフラストラクチャ、ネットワーキング、およびストレージサービスについての良好な理解が必要です。また、GCP上でアプリケーションを展開および管理する経験が必要です。認定試験は、候補者のこれらの領域における知識とスキルをテストする複数選択問題と実際のシナリオで構成されています。
Google Associate-Cloud-Engineer (Google アソシエイト クラウド エンジニア) 認定試験は、Google Cloud が提供するプロフェッショナル認定試験です。この認証は、Google Cloud Platform での作業経験を持ち、その知識と専門知識を証明したい個人を対象としています。試験は、コンピューティング、ストレージ、ネットワーキング、セキュリティなど、Google Cloud Platform の様々な側面に焦点を当てています。
質問 # 142
A company requires that the source, destination, and protocol of all IP packets be recorded when traversing a private subnet.
What is the MOST secure and reliable method of accomplishing this goal.
- A. Enable AWS CloudTrail logging and specify an Amazon S3 bucket for storing log files.
- B. Create VPC flow logs on the subnet.
- C. Create an Amazon CloudWatch log to capture packet information.
- D. Enable source destination check on private Amazon EC2 instances.
正解：B
質問 # 143
You have an instance group that you want to load balance. You want the load balancer to terminate the client SSL session. The instance group is used to serve a public web application over HTTPS. You want to follow Google-recommended practices. What should you do?
- A. Configure an HTTP(S) load balancer.
- B. Configure an external SSL proxy load balancer.
- C. Configure an external TCP proxy load balancer.
- D. Configure an internal TCP load balancer.
正解：A
解説：
Reference:
According to this guide for setting up an HTTP (S) load balancer in GCP: The client SSL session terminates at the load balancer. Sessions between the load balancer and the instance can either be HTTPS (recommended) or HTTP.
https://cloud.google.com/load-balancing/docs/ssl
質問 # 144
You need to migrate invoice documents stored on-premises to Cloud Storage. The documents have the following storage requirements:
* Documents must be kept for five years.
* Up to five revisions of the same invoice document must be stored, to allow for corrections.
* Documents older than 365 days should be moved to lower cost storage tiers.
You want to follow Google-recommended practices to minimize your operational and development costs. What should you do?
- A. Enable retention policies on the bucket, and use Cloud Scheduler to invoke a Cloud Function to move or delete your documents based on their metadata.
- B. Enable object versioning on the bucket, and use Cloud Scheduler to invoke a Cloud Functions instance to move or delete your documents based on their metadata.
- C. Enable object versioning on the bucket, use lifecycle conditions to change the storage class of the objects, set the number of versions, and delete old files.
- D. Enable retention policies on the bucket, use lifecycle rules to change the storage classes of the objects, set the number of versions, and delete old files.
正解：C
解説：
https://cloud.google.com/storage/docs/object-versioning
質問 # 145
You're working for a company as a Cloud engineer. You have a managed instance group for which the autoscaling is enabled if CPU utilization is 70%. Right now there are 4 instances available in this instance group. When you connect to one of the instance, you see that the CPU utilization is 75% and there is no new instance is started in the group. What could be the possible reason for not starting another instance here?
- A. Autoscaling is not active
- B. It will take 60 seconds to launch a new instance
- C. None of the above
- D. Average CPU usage of the instance group is less than 70%
正解：D
質問 # 146
You're trying to provide temporary access to some files in a Cloud Storage bucket. You want to limit the time that the files are available to 10 minutes. With the fewest steps possible, what is the best way to generate a signed URL?
- A. In the UI select the objects and click the Generate Signed URL button.
- B. Create a service account and JSON key. Use the gsutil signurl -t 10m command and pass in the JSON key and bucket.
- C. In the UI select the objects and click the "Sign With Key" button.
- D. Create a service account and JSON key. Use the gsutil signurl -d 10m command and pass in the JSON key and bucket.
正解：D
質問 # 147
You are running multiple VPC-native Google Kubernetes Engine clusters in the same subnet. The IPs available for the nodes are exhausted, and you want to ensure that the clusters can grow in nodes when needed. What should you do?
- A. Expand the CIDR range of the relevant subnet for the cluster.
- B. Create a new VPC, and set up VPC peering with the existing VPC.
- C. Add an alias IP range to the subnet used by the GKE clusters.
- D. Create a new subnet in the same region as the subnet being used.
正解：D
解説：
gcloud compute networks subnets expand-ip-range NAME gcloud compute networks subnets expand-ip-range - expand the IP range of a Compute Engine subnetwork https://cloud.google.com/sdk/gcloud/reference/compute/networks/subnets/expand-ip-range
質問 # 148
Your team is running an on-premises ecommerce application. The application contains a complex set of microservices written in Python, and each microservice is running on Docker containers. Configurations are injected by using environment variables. You need to deploy your current application to a serverless Google Cloud cloud solution. What should you do?
- A. Use your existing continuous integration and delivery (CI/CD) pipeline. Use the generated Docker images and deploy them to Cloud Function. Use the same configuration as on-premises.
- B. Use the existing codebase and deploy each service as a separate Cloud Function Update the configurations and the required endpoints.
- C. Use your existing CI/CD pipeline Use the generated Docker images and deploy them to Cloud Run. Update the configurations and the required endpoints.
- D. Use your existing codebase and deploy each service as a separate Cloud Run Use the same configurations as on-premises.
正解：C
質問 # 149
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. In Cloud Logging create a filter for your Data Studio report
- C. Review the Error Reporting page in the Cloud Console to find any errors.
- D. Use Cloud Debugger to find out why the data was not refreshed correctly
正解：D
質問 # 150
You are planning to move your company's website and a specific asynchronous background job to Google Cloud Your website contains only static HTML content The background job is started through an HTTP endpoint and generates monthly invoices for your customers. Your website needs to be available in multiple geographic locations and requires autoscaling. You want to have no costs when your workloads are not In use and follow recommended practices. What should you do?
- A. Move your website to Google Kubemetes Engine (GKE). and move your background job to Cloud Functions
- B. Move your website to Google Kubemetes Engine (GKE), and move your background job to Compute Engine
- C. Move both your website and background job to Compute Engine
CMove both your website and background job to Cloud Run.
正解：B
質問 # 151
Your organization is a financial company that needs to store audit log files for 3 years. Your organization has hundreds of Google Cloud projects. You need to implement a cost-effective approach for log file retention.
What should you do?
- A. Export these logs to Cloud Pub/Sub and write a Cloud Dataflow pipeline to store logs to Cloud SQL.
- B. Create an export to the sink that saves logs from Cloud Audit to BigQuery.
- C. Create an export to the sink that saves logs from Cloud Audit to a Coldline Storage bucket.
- D. Write a custom script that uses logging API to copy the logs from Stackdriver logs to BigQuery.
正解：B
質問 # 152
You are using Deployment Manager to create a Google Kubernetes Engine cluster. Using the same Deployment Manager deployment, you also want to create a DaemonSet in the kube-system namespace of the cluster. You want a solution that uses the fewest possible services. What should you do?
- A. With Deployment Manager, create a Compute Engine instance with a startup script that uses kubectl to create the DaemonSet.
- B. In the cluster's definition in Deployment Manager, add a metadata that has kube-system as key and the DaemonSet manifest as value.
- C. Use the Deployment Manager Runtime Configurator to create a new Config resource that contains the DaemonSet definition.
- D. Add the cluster's API as a new Type Provider in Deployment Manager, and use the new type to create the DaemonSet.
正解：D
解説：
Explanation
Adding an API as a type provider
This page describes how to add an API to Google Cloud Deployment Manager as a type provider. To learn more about types and type providers, read the Types overview documentation.
A type provider exposes all of the resources of a third-party API to Deployment Manager as base types that you can use in your configurations. These types must be directly served by a RESTful API that supports Create, Read, Update, and Delete (CRUD).
If you want to use an API that is not automatically provided by Google with Deployment Manager, you must add the API as a type provider.
https://cloud.google.com/deployment-manager/docs/configuration/type-providers/creating-type-provider
質問 # 153
You are creating an application that will run on Google Kubernetes Engine. You have identified MongoDB as the most suitable database system for your application and want to deploy a managed MongoDB environment that provides a support SLA. What should you do?
- A. Create a Cloud Bigtable cluster and use the HBase API
- B. Download a MongoDB installation package, and run it on a Managed Instance Group
- C. Download a MongoDB installation package and run it on Compute Engine instances
- D. Deploy MongoDB Alias from the Google Cloud Marketplace
正解：D
解説：
https://console.cloud.google.com/marketplace/details/gc-launcher-for-mongodb-atlas/mongodb-atlas
質問 # 154
You are running an application on multiple virtual machines within a managed instance group and have autoscaling enabled. The autoscaling policy is configured so that additional instances are added to the group if the CPU utilization of instances goes above 80%. VMs are added until the instance group reaches its maximum limit of five VMs or until CPU utilization of instances lowers to 80%. The initial delay for HTTP health checks against the instances is set to 30 seconds. The virtual machine instances take around three minutes to become available for users. You observe that when the instance group autoscales, it adds more instances then necessary to support the levels of end-user traffic. You want to properly maintain instance group sizes when autoscaling. What should you do?
- A. Increase the initial delay of the HTTP health check to 200 seconds.
- B. Set the maximum number of instances to 1.
- C. Decrease the maximum number of instances to 3.
- D. Use a TCP health check instead of an HTTP health check.
正解：A
質問 # 155
You are hosting an application from Compute Engine virtual machines (VMs) in us-central1-a. You want to adjust your design to support the failure of a single Compute Engine zone, eliminate downtime, and minimize cost. What should you do?
- A. - Create Compute Engine resources in us-central1-b.
-Balance the load across both us-central1-a and us-central1-b. - B. - Perform regular backups of your application.
-Create a Cloud Monitoring Alert and be notified if your application becomes unavailable.
-Restore from backups when notified. - C. - Create a Managed Instance Group and specify us-central1-a as the zone.
-Configure the Health Check with a short Health Interval. - D. - Create an HTTP(S) Load Balancer.
-Create one or more global forwarding rules to direct traffic to your VMs.
正解：A
解説：
Choosing a region and zone You choose which region or zone hosts your resources, which controls where your data is stored and used. Choosing a region and zone is important for several reasons:
Handling failures
Distribute your resources across multiple zones and regions to tolerate outages. Google designs zones to be independent from each other: a zone usually has power, cooling, networking, and control planes that are isolated from other zones, and most single failure events will affect only a single zone. Thus, if a zone becomes unavailable, you can transfer traffic to another zone in the same region to keep your services running.
Similarly, if a region experiences any disturbances, you should have backup services running in a different region. For more information about distributing your resources and designing a robust system, see Designing Robust Systems. Decreased network latency To decrease network latency, you might want to choose a region or zone that is close to your point of service.
https://cloud.google.com/compute/docs/regions-zones#choosing_a_region_and_zone
質問 # 156
You have one GCP account running in your default region and zone and another account running in a non-default region and zone. You want to start a new Compute Engine instance in these two Google Cloud Platform accounts using the command line interface. What should you do?
- A. Create two configurations using gcloud config configurations create [NAME]. Run gcloud config configurations activate [NAME] to switch between accounts when running the commands to start the Compute Engine instances.
- B. Create two configurations using gcloud config configurations create [NAME]. Run gcloud configurations list to start the Compute Engine instances.
- C. Activate two configurations using gcloud configurations activate [NAME]. Run gcloud configurations list to start the Compute Engine instances.
- D. Activate two configurations using gcloud configurations activate [NAME]. Run gcloud config list to start the Compute Engine instances.
正解：A
解説：
"Run gcloud configurations list to start the Compute Engine instances". How the heck are you expecting to "start" GCE instances doing "configuration list".
Each gcloud configuration has a 1 to 1 relationship with the region (if a region is defined). Since we have two different regions, we would need to create two separate configurations using gcloud config configurations create Ref: https://cloud.google.com/sdk/gcloud/reference/config/configurations/create Secondly, you can activate each configuration independently by running gcloud config configurations activate [NAME] Ref: https://cloud.google.com/sdk/gcloud/reference/config/configurations/activate Finally, while each configuration is active, you can run the gcloud compute instances start [NAME] command to start the instance in the configurations region. https://cloud.google.com/sdk/gcloud/reference/compute/instances/start
質問 # 157
Your developers have created an application that needs to be able to make calls to Cloud Storage and BigQuery. The code is going to run inside a container and will run on Kubernetes Engine and on-premises.
What's the best way for them to authenticate to the Google Cloud services?
- A. Create a service account, grant it the least viable privileges to the required services, generate and download a key. Use the key to authenticate inside the application.
- B. Use the default service account for Compute Engine which already has the required permissions.
- C. Use the default service account for App Engine which already has the required permissions.
- D. Create a service account, with editor permissions, generate and download a key. Use the key to authenticate inside the application.
正解：A
質問 # 158
You are analyzing Google Cloud Platform service costs from three separate projects. You want to use this information to create service cost estimates by service type, daily and monthly, for the next six months using standard query syntax. What should you do?
- A. Export your bill to a BigQuery dataset, and then write time window-based SQL queries for analysis.
- B. Export your bill to a Cloud Storage bucket, and then import into Cloud Bigtable for analysis.
- C. Export your bill to a Cloud Storage bucket, and then import into Google Sheets for analysis.
- D. Export your transactions to a local file, and perform analysis with a desktop tool.
正解：A
解説：
Explanation
"...we recommend that you enable Cloud Billing data export to BigQuery at the same time that you create a Cloud Billing account. " https://cloud.google.com/billing/docs/how-to/export-data-bigquery
https://medium.com/google-cloud/analyzing-google-cloud-billing-data-with-big-query-30bae1c2aae4
質問 # 159
You are managing several Google Cloud Platform (GCP) projects and need access to all logs for the past 60 days. You want to be able to explore and quickly analyze the log contents. You want to follow Google- recommended practices to obtain the combined logs for all projects. What should you do?
- A. Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days.
- B. Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days.
- C. Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days.
- D. Navigate to Stackdriver Logging and select resource.labels.project_id="*"
正解：C
解説：
* Navigate to Stackdriver Logging and select resource.labels.project_id=*. is not right.
Log entries are held in Stackdriver Logging for a limited time known as the retention period which is 30 days (default configuration). After that, the entries are deleted. To keep log entries longer, you need to export them outside of Stackdriver Logging by configuring log sinks.
Ref: https://cloud.google.com/blog/products/gcp/best-practices-for-working-with-google-cloud-audit-logging
* Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days. is not right.
While this works, it makes no sense to use Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery when Google provides a feature (export sinks) that does exactly the same thing and works out of the box.
Ref: https://cloud.google.com/logging/docs/export/configure_export_v2
* Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days. is not right.
You can export logs by creating one or more sinks that include a logs query and an export destination.
Supported destinations for exported log entries are Cloud Storage, BigQuery, and Pub/Sub.
Ref: https://cloud.google.com/logging/docs/export/configure_export_v2
Sinks are limited to exporting log entries from the exact resource in which the sink was created: a Google Cloud project, organization, folder, or billing account. If it makes it easier to exporting from all projects of an organication, you can create an aggregated sink that can export log entries from all the projects, folders, and billing accounts of a Google Cloud organization.
Ref: https://cloud.google.com/logging/docs/export/aggregated_sinks
Either way, we now have the data in Cloud Storage, but querying logs information from Cloud Storage is harder than Querying information from BigQuery dataset. For this reason, we should prefer Big Query over Cloud Storage.
* Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days. is the right answer.
You can export logs by creating one or more sinks that include a logs query and an export destination.
Supported destinations for exported log entries are Cloud Storage, BigQuery, and Pub/Sub.
Ref: https://cloud.google.com/logging/docs/export/configure_export_v2
Sinks are limited to exporting log entries from the exact resource in which the sink was created: a Google Cloud project, organization, folder, or billing account. If it makes it easier to exporting from all projects of an organication, you can create an aggregated sink that can export log entries from all the projects, folders, and billing accounts of a Google Cloud organization.
Ref: https://cloud.google.com/logging/docs/export/aggregated_sinks
Either way, we now have the data in a BigQuery Dataset. Querying information from a Big Query dataset is easier and quicker than analyzing contents in Cloud Storage bucket. As our requirement is to Quickly analyze the log contents, we should prefer Big Query over Cloud Storage.
Also, You can control storage costs and optimize storage usage by setting the default table expiration for newly created tables in a dataset. If you set the property when the dataset is created, any table created in the dataset is deleted after the expiration period. If you set the property after the dataset is created, only new tables are deleted after the expiration period.
For example, if you set the default table expiration to 7 days, older data is automatically deleted after 1 week.
Ref: https://cloud.google.com/bigquery/docs/best-practices-storage
質問 # 160
You are asked to set up application performance monitoring on Google Cloud projects A, B, and C as a single pane of glass. You want to monitor CPU, memory, and disk. What should you do?
- A. Enable API and then share charts from project A, B, and C.
- B. Enable API and then give the metrics.reader role to projects A, B, and C.
- C. Enable API and then use default dashboards to view all projects in sequence.
- D. Enable API, create a workspace under project A, and then add project B and C.
正解：D
解説：
https://cloud.google.com/monitoring/settings/multiple-projects
https://cloud.google.com/monitoring/workspaces
質問 # 161
You are deploying a production application on Compute Engine. You want to prevent anyone from accidentally destroying the instance by clicking the wrong button. What should you do?
- A. Enable Preemptibility on the instance.
- B. Disable the flag "Delete boot disk when instance is deleted."
- C. Disable Automatic restart on the instance.
- D. Enable delete protection on the instance.
正解：D
解説：
Preventing Accidental VM Deletion This document describes how to protect specific VM instances from deletion by setting the deletionProtection property on an Instance resource. To learn more about VM instances, read the Instances documentation. As part of your workload, there might be certain VM instances that are critical to running your application or services, such as an instance running a SQL server, a server used as a license manager, and so on. These VM instances might need to stay running indefinitely so you need a way to protect these VMs from being deleted. By setting the deletionProtection flag, a VM instance can be protected from accidental deletion. If a user attempts to delete a VM instance for which you have set the deletionProtection flag, the request fails. Only a user that has been granted a role with compute.instances.create permission can reset the flag to allow the resource to be deleted. https://cloud.google.com/compute/docs/instances/preventing-accidental-vm-deletion
質問 # 162
You are building an archival solution for your data warehouse and have selected Cloud Storage to archive your data. Your users need to be able to access this archived data once a quarter for some regulatory requirements. You want to select a cost-efficient option. Which storage option should you use?
- A. Regional Storage
- B. Coldline Storage
- C. Nearline Storage
- D. Multi-Regional Storage
正解：B
解説：
Coldline Storage is a very-low-cost, highly durable storage service for storing infrequently accessed data.
Coldline Storage is ideal for data you plan to read or modify at most once a quarter. Since we have a requirement to access data once a quarter and want to go with the most cost-efficient option, we should select Coldline Storage.
Ref: https://cloud.google.com/storage/docs/storage-classes#coldline
質問 # 163
You deployed an App Engine application using gcloud app deploy, but it did not deploy to the intended project. You want to find out why this happened and where the application deployed. What should you do?
- A. Go to Cloud Shell and run gcloud config list to review the Google Cloud configuration used for deployment.
- B. Check the app.yaml file for your application and check project settings.
- C. Check the web-application.xml file for your application and check project settings.
- D. Go to Deployment Manager and review settings for deployment of applications.
正解：B
解説：
Reference:
https://cloud.google.com/endpoints/docs/openapi/troubleshoot-aeflex-deployment
質問 # 164
You need to verify that a Google Cloud Platform service account was created at a particular time.
What should you do?
- A. Filter the Activity log to view the Data Access category. Filter the Resource type to Service Account.
- B. Filter the Activity log to view the Data Access category. Filter the Resource type to Google Project.
- C. Filter the Activity log to view the Configuration category. Filter the Resource type to Google Project.
- D. Filter the Activity log to view the Configuration category. Filter the Resource type to Service Account.
正解：D
解説：
You don't need data access logs and configuration counts as creation.
質問 # 165
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 a route on the VPC to route all traffic to the instance over the VPN tunnel.
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. - B. Create a deny-all egress firewall rule on the VPC network.
- C. Create the instance with Private Google Access enabled.
- D. Create the instance without a public IP address.
正解：C
解説：
Reference:
https://cloud.google.com/vpc
質問 # 166
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Google Associate Cloud Engineer認定は、業界で非常に評価されており、候補者に競争力を提供します。この認定は、個人がGoogleクラウドプラットフォームで効果的に取り組むために必要なスキルと知識を持っていることを示しています。さらに、この認定は、Google Professional Cloud ArchitectやGoogle Professional Cloud Developerなどの高度なクラウド認定を追求したい個人向けの足がかりです。
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