[Q13-Q34] Associate-Cloud-Engineer Dumps Free Test Engine Player Verified Updated [Aug 14, 2026]

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Associate-Cloud-Engineer Dumps Free Test Engine Player Verified Updated [Aug 14, 2026]

Q&As with Explanations Verified & Correct Answers

Google Associate-Cloud-Engineer Exam Syllabus Topics:

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

NO.13 A Solutions Architect is reviewing an application that writes data to an Amazon DynamoDB table on a daily basis. Random table reads occur many times per second.
The company needs to allow thousands of low-latency reads and avoid any negative impact to the rest of the application.
What should the Solutions Architect do to meet the company’s goals?

Use DynamoDB Accelerator to cache reads.

Increase DynamoDB write capacity units.

Add Amazon SQS to decouple requests.

Implement Amazon Kinesis to decouple requests.

NO.14 Regarding audit logs, which of the following is a Google recommended best practice?

Export your audit logs to App Engine

Export your audit logs to Pub/Sub.

Flush your audit logs monthly so you can more easily notice security events.

Export your audit logs to Cloud Storage and store them for a long period of time.

NO.15 You need to monitor resources that are distributed over different projects in Google Cloud Platform. You want to consolidate reporting under the same Stackdriver Monitoring dashboard. What should you do?

Use Shared VPC to connect all projects, and link Stackdriver to one of the projects.

For each project, create a Stackdriver account. In each project, create a service account for that project and grant it the role of Stackdriver Account Editor in all other projects.

Configure a single Stackdriver account, and link all projects to the same account.

Configure a single Stackdriver account for one of the projects. In Stackdriver, create a Group and add the other project names as criteria for that Group.

NO.16 You are building an application that processes data files uploaded from thousands of suppliers. Your primary goals for the application are data security and the expiration of aged data. You need to design the application to:
*Restrict access so that suppliers can access only their own data.
*Give suppliers write access to data only for 30 minutes.
*Delete data that is over 45 days old.
You have a very short development cycle, and you need to make sure that the application requires minimal maintenance. Which two strategies should you use? (Choose two.)

Build a lifecycle policy to delete Cloud Storage objects after 45 days.

Use signed URLs to allow suppliers limited time access to store their objects.

Set up an SFTP server for your application, and create a separate user for each supplier.

Build a Cloud function that triggers a timer of 45 days to delete objects that have expired.

Develop a script that loops through all Cloud Storage buckets and deletes any buckets that are older than
45 days.

NO.17 Your auditor wants to view your organization’s use of data in Google Cloud. The auditor is most interested in auditing who accessed data in Cloud Storage buckets. You need to help the auditor access the data they need. What should you do?

Assign the appropriate permissions, and then use Cloud Monitoring to review metrics

Use the export logs API to provide the Admin Activity Audit Logs in the format they want

Turn on Data Access Logs for the buckets they want to audit, and Then build a query in the log viewer that filters on Cloud Storage

Assign the appropriate permissions, and then create a Data Studio report on Admin Activity Audit Logs

NO.18 You are responsible for a web application on Compute Engine. You want your support team to be notified automatically if users experience high latency for at least 5 minutes. You need a Google-recommended solution with no development cost. What should you do?

Create an alert policy to send a notification when the HTTP response latency exceeds the specified threshold.

Implement an App Engine service which invokes the Cloud Monitoring API and sends a notification in case of anomalies.

Use the Cloud Monitoring dashboard to observe latency and take the necessary actions when the response latency exceeds the specified threshold.

Export Cloud Monitoring metrics to BigQuery and use a Looker Studio dashboard to monitor your web applications latency.

NO.19 You have a batch workload that runs every night and uses a large number of virtual machines (VMs). It is fault-tolerant and can tolerate some of the VMs being terminated. The current cost of VMs is too high. What should you do?

Run a test using simulated maintenance events. If the test is successful, use Spot N2 Standard VMs when running future jobs.

Run a test using simulated maintenance events. If the test is successful, use N2 Standard VMs when running future jobs.

Run a test using a managed instance group. If the test is successful, use N2 Standard VMs in the managed instance group when running future jobs.

Run a test using N1 standard VMs instead of N2. If the test is successful, use N1 Standard VMs when running future jobs.

NO.20 You have a workload running on Compute Engine that is critical to your business. You want to ensure that the data on the boot disk of this workload is backed up regularly. You need to be able to restore a backup as quickly as possible in case of disaster. You also want older backups to be cleaned automatically to save on cost. You want to follow Google-recommended practices. What should you do?

Create a Cloud Function to create an instance template.

Create a snapshot schedule for the disk using the desired interval.

Create a cron job to create a new disk from the disk using gcloud.

Create a Cloud Task to create an image and export it to Cloud Storage.

NO.21 You’ve run a command to start up 2 new instances. However, you do not see the instances in the console. What command(s) would help you to identify the cause of the problem?

gcloud debug

gcloud config list

gcloud auth login

gcloud info

NO.22 You have just created a new project which will be used to deploy a globally distributed application. You will use Cloud Spanner for data storage. You want to create a Cloud Spanner instance. You want to perform the first step in preparation of creating the instance. What should you do?

Grant yourself the IAM role of Cloud Spanner Admin

Create a new VPC network with subnetworks in all desired regions

Configure your Cloud Spanner instance to be multi-regional

Enable the Cloud Spanner API

NO.23 An application requires block storage for file updates. The data is 500 GB and must continuously sustain 100 MiB/s of aggregate read/write operations.
Which storage option is appropriate for this application?

Amazon S3

Amazon EFS

Amazon EBS

Amazon Glacier

NO.24 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?

Create an export to the sink that saves logs from Cloud Audit to BigQuery.

Create an export to the sink that saves logs from Cloud Audit to a Coldline Storage bucket.

Write a custom script that uses logging API to copy the logs from Stackdriver logs to BigQuery.

Export these logs to Cloud Pub/Sub and write a Cloud Dataflow pipeline to store logs to Cloud SQL.

NO.25 You have recently joined a startup who is migrating their infrastructure from AWS to Google Cloud. A junior was assigned the task of migrating one of their web server with Amazon Linux OS from AWS to GCP in a public subnet of custom VPC. He was able to migrate the instance successfully but is unable to get SSH access of migrated instance. What are the possible steps to look for? (Multiple Answer)

Check if he has attached correct firewall rule with port udp:22 open to the instance.

Ask if he has added SSH key to the instance while launching phase.

Google Cloud does not support Amazon Linux images because of market competition.

Make sure the firewall is attached to the instance with tcp port 22 open.

NO.26 Your organization has three existing Google Cloud projects. You need to bill the Marketing department for only their Google Cloud services for a new initiative within their group. What should you do?

1.Verify that you ace assigned the Billing Administrator IAM role tor your organization’s Google Cloud Project for the Marketing department
2.Link the new project to a Marketing Billing Account

1.Verify that you are assigned the Billing Administrator IAM role for your organization’s Google Cloud account
2.Create a new Google Cloud Project for the Marketing department
3.Set the default key-value project labels to department marketing for all services in this project

1.Verify that you are assigned the Organization Administrator IAM role for your organization’s Google Cloud account
2.Create a new Google Cloud Project for the Marketing department
3. Link the new project to a Marketing Billing Account.

1.Verity that you are assigned the Organization Administrator IAM role for your organization’s Google Cloud account
2.Create a new Google Cloud Project for the Marketing department
3.Set the default key value project labels to department marketing for all services in this protect

NO.27 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?

Create a single budget for all projects and configure budget alerts on this budget.

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.

Create a budget per project and configure budget alerts on all of these budgets.

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.

NO.28 A team of data scientists infrequently needs to use a Google Kubernetes Engine (GKE) cluster that you manage. They require GPUs for some long-running, non-restartable jobs. You want to minimize cost. What should you do?

Enable node auto-provisioning on the GKE cluster.

Create a VerticalPodAutscaler for those workloads.

Create a node pool with preemptible VMs and GPUs attached to those VMs.

Create a node pool of instances with GPUs, and enable autoscaling on this node pool with a minimum size of 1.

NO.29 Your organization has a dedicated person who creates and manages all service accounts for Google Cloud projects. You need to assign this person the minimum role for projects. What should you do?

Add the user to roles/iam.roleAdmin role.

Add the user to roles/iam.securityAdmin role.

Add the user to roles/iam.serviceAccountUser role.

Add the user to roles/iam.serviceAccountAdmin role.

NO.30 You’ve deployed a microservice called myapp1 to a Google Kubernetes Engine cluster using the YAML file specified below:

You need to refactor this configuration so that the database password is not stored in plain text. You want to follow Google-recommended practices. What should you do?

Store the database password inside the Docker image of the container, not in the YAML file.

Store the database password inside a Secret object. Modify the YAML file to populate the DB_PASSWORD environment variable from the Secret.

Store the database password inside a ConfigMap object. Modify the YAML file to populate the DB_PASSWORD environment variable from the ConfigMap.

Store the database password in a file inside a Kubernetes persistent volume, and use a persistent volume claim to mount the volume to the container.

NO.31 Your web application is hosted on Cloud Run and needs to query a Cloud SQL database. Every morning during a traffic spike, you notice API quota errors in Cloud SQL logs. The project has already reached the maximum API quota. You want to make a configuration change to mitigate the issue. What should you do?

Modify the minimum number of Cloud Run instances.

Use traffic splitting.

Modify the maximum number of Cloud Run instances.

Set a minimum concurrent requests environment variable for the application.

NO.32 You created an instance of SQL Server 2017 on Compute Engine to test features in the new version. You want to connect to this instance using the fewest number of steps.
What should you do?

Install a RDP client on your desktop. Verify that a firewall rule for port 3389 exists.

Install a RDP client in your desktop. Set a Windows username and password in the GCP Console.
Use the credentials to log in to the instance.

Set a Windows password in the GCP Console. Verify that a firewall rule for port 22 exists.
Click the RDP button in the GCP Console and supply the credentials to log in.

Set a Windows username and password in the GCP Console. Verify that a firewall rule for port
3389 exists.
Click the RDP button in the GCP Console, and supply the credentials to log in.

NO.33 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?

Navigate to Stackdriver Logging and select resource.labels.project_id=”*”

Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days.

Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days.

Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days.

* 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
Reference: https://cloud.google.com/blog/products/gcp/best-practices-for-working-with-google-cloud-audit- logging

NO.34 Your company has a 3-tier solution running on Compute Engine. The configuration of the current infrastructure is shown below.

Each tier has a service account that is associated with all instances within it. You need to enable communication on TCP port 8080 between tiers as follows:
* Instances in tier #1 must communicate with tier #2.
* Instances in tier #2 must communicate with tier #3.
What should you do?

1. Create an ingress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.2.0/24)* Protocols: allow all2. Create an ingress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.1.0/24)* Protocols: allow all

1. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #2 service account* Source filter: all instances with tier #1 service account* Protocols: allow TCP:80802. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #3 service account* Source filter: all instances with tier #2 service account* Protocols: allow TCP: 8080

1. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #2 service account* Source filter: all instances with tier #1 service account* Protocols: allow all2. Create an ingress firewall rule with the following settings:* Targets: all instances with tier #3 service account* Source filter: all instances with tier #2 service account* Protocols: allow all

1. Create an egress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.2.0/24)* Protocols: allow TCP: 80802. Create an egress firewall rule with the following settings:* Targets: all instances* Source filter: IP ranges (with the range set to 10.0.1.0/24)* Protocols: allow TCP: 8080