Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer Free Practice Exam Questions (2025 Updated)

Prepare effectively for your Google Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer certification with our extensive collection of free, high-quality practice questions. Each question is designed to mirror the actual exam format and objectives, complete with comprehensive answers and detailed explanations. Our materials are regularly updated for 2025, ensuring you have the most current resources to build confidence and succeed on your first attempt.

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Question # 6

(You have an application running inside a Compute Engine instance. You want to provide the application with secure access to a BigQuery dataset. You must ensure that credentials are only valid for a short period of time, and your application will only have access to the intended BigQuery dataset. You want to follow Google-recommended practices and minimize your operational costs. What should you do?)

Attach a custom service account to the instance, and grant the service account the BigQuery Data Viewer IAM role on the project.

Attach a new service account to the instance every hour, and grant the service account the BigQuery Data Viewer IAM role on the dataset.

Attach a custom service account to the instance, and grant the service account the BigQuery Data Viewer IAM role on the dataset.

Attach a new service account to the instance every hour, and grant the service account the BigQuery Data Viewer IAM role on the project.

Explanation:

Comprehensive and Detailed In Depth Explanation:

The core requirements are secure access to a specific BigQuery dataset from a Compute Engine instance, using short-lived credentials, adhering to Google's best practices, and minimizing operational overhead.

A. Project-level IAM role: Granting the BigQuery Data Viewer role at the project level gives the service account broad access to all BigQuery datasets within that project. This violates the principle of least privilege, a fundamental security best practice, as the application should only have access to the designated dataset.

B. Hourly new service account with dataset-level role: While this aims to achieve short-lived credentials, the operational burden of creating, attaching, and managing IAM policies for a new service account every hour is significant and not a Google-recommended practice for routine access. It introduces unnecessary complexity and potential for errors.

C. Custom service account with dataset-level IAM role: This is the recommended and most efficient approach. You create a dedicated Google Cloud service account specifically for this application. You then grant this service account the necessary IAM role (e.g., BigQuery Data Viewer, or a more specific custom role) directly on the target BigQuery dataset. When the Compute Engine instance runs as this service account, the Google Cloud client libraries automatically handle the acquisition and rotation of short-lived OAuth 2.0 access tokens from the instance's metadata server. This eliminates the need to manage long-lived credentials (like service account keys) and ensures the application only has access to the intended dataset. This adheres to the principle of least privilege and minimizes operational costs.

D. Hourly new service account with project-level role: This option combines the high operational overhead of frequently creating new service accounts with the security risk of granting overly permissive project-level access. It is not a recommended practice.

Therefore, the most secure, cost-effective, and operationally efficient solution is to create a custom service account, attach it to the Compute Engine instance, and grant it the appropriate BigQuery IAM role specifically on the target dataset. The platform handles the short-lived credentials automatically.

Google Cloud Documentation References:

Creating and enabling service accounts for instances: https://cloud.google.com/compute/docs/access/create-enable-service-accounts-for-instances - Explains how to create and associate service accounts with Compute Engine VMs.

Granting, changing, and revoking access to resources: https://cloud.google.com/iam/docs/granting-changing-revoking-access - Details how to manage IAM policies and grant roles to service accounts on specific resources (like BigQuery datasets).

BigQuery IAM roles: https://cloud.google.com/bigquery/docs/control-access - Provides information on the various IAM roles available for controlling access to BigQuery resources at different levels (project, dataset, table, etc.).

Best practices for using service accounts: https://cloud.google.com/iam/docs/best-practices-for-using-service-accounts - Emphasizes the importance of the principle of least privilege and avoiding the management of long-lived service account keys when possible (relying on the metadata server for short-lived tokens).

Question # 7

After a recent security incident, your startup company wants better insight into what is happening in the Google Cloud environment. You need to monitor unexpected firewall changes and instance creation. Your company prefers simple solutions. What should you do?

Use Cloud Logging filters to create log-based metrics for firewall and instance actions. Monitor the changes and set up reasonable alerts.

Install Kibana on a compute Instance. Create a log sink to forward Cloud Audit Logs filtered for firewalls andcompute instances to Pub/Sub. Target the Pub/Sub topic to push messages to the Kibana instance. Analyze the logs on Kibana in real time.

Turn on Google Cloud firewall rules logging, and set up alerts for any insert, update, or delete events.

Create a log sink to forward Cloud Audit Logs filtered for firewalls and compute instances to Cloud Storage.Use BigQuery to periodically analyze log events in the storage bucket.

Question # 8

You are configuring service accounts for an application that spans multiple projects. Virtual machines (VMs) running in the web-applications project need access to BigQuery datasets in the crm-databases project. You want to follow Google-recommended practices to grant access to the service account in the web-applications project. What should you do?

Grant "project owner" for web-applications appropriate roles to crm-databases.

Grant "project owner" role to crm-databases and the web-applications project.

Grant "project owner" role to crm-databases and roles/bigquery.dataViewer role to web-applications.

Grant roles/bigquery.dataViewer role to crm-databases and appropriate roles to web-applications.

Question # 9

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?

– Create Compute Engine resources in us–central1–b.–Balance the load across both us–central1–a and us–central1–b.

– Create a Managed Instance Group and specify us–central1–a as the zone.–Configure the Health Check with a short Health Interval.

– Create an HTTP(S) Load Balancer.–Create one or more global forwarding rules to direct traffic to your VMs.

– Perform regular backups of your application.–Create a Cloud Monitoring Alert and be notified if your application becomes unavailable.–Restore from backups when notified.

Question # 10

Your company has developed a new application that consists of multiple microservices. You want to deploy the application to Google Kubernetes Engine (GKE), and you want to ensure that the cluster can scale as more applications are deployed in the future. You want to avoid manual intervention when each new application is deployed. What should you do?

Deploy the application on GKE, and add a HorizontalPodAutoscaler to the deployment.

Deploy the application on GKE, and add a VerticalPodAutoscaler to the deployment.

Create a GKE cluster with autoscaling enabled on the node pool. Set a minimum and maximum for the size of the node pool.

Create a separate node pool for each application, and deploy each application to its dedicated node pool.

Question # 11

Your organization has strict requirements to control access to Google Cloud projects. You need to enable your Site Reliability Engineers (SREs) to approve requests from the Google Cloud support team when an SRE opens a support case. You want to follow Google-recommended practices. What should you do?

Add your SREs to roles/iam.roleAdmin role.

Add your SREs to roles/accessapproval approver role.

Add your SREs to a group and then add this group to roles/iam roleAdmin role.

Add your SREs to a group and then add this group to roles/accessapproval approver role.

Question # 12

You have an application that looks for its licensing server on the IP 10.0.3.21. You need to deploy the licensing server on Compute Engine. You do not want to change the configuration of the application and want the application to be able to reach the licensing server. What should you do?

Reserve the IP 10.0.3.21 as a static internal IP address using gcloud and assign it to the licensing server.

Reserve the IP 10.0.3.21 as a static public IP address using gcloud and assign it to the licensing server.

Use the IP 10.0.3.21 as a custom ephemeral IP address and assign it to the licensing server.

Start the licensing server with an automatic ephemeral IP address, and then promote it to a static internal IP address.

Question # 13

You need to set up a policy so that videos stored in a specific Cloud Storage Regional bucket are moved to Coldline after 90 days, and then deleted after one year from their creation. How should you set up the policy?

Use Cloud Storage Object Lifecycle Management using Age conditions with SetStorageClass and Delete actions. Set the SetStorageClass action to 90 days and the Delete action to 275 days (365 – 90)

Use Cloud Storage Object Lifecycle Management using Age conditions with SetStorageClass and Delete actions. Set the SetStorageClass action to 90 days and the Delete action to 365 days.

Use gsutil rewrite and set the Delete action to 275 days (365-90).

Use gsutil rewrite and set the Delete action to 365 days.

Question # 14

You are managing a Data Warehouse on BigQuery. An external auditor will review your company's processes, and multiple external consultants will need view access to the data. You need to provide them with view access while following Google-recommended practices. What should you do?

Grant each individual external consultant the role of BigQuery Editor

Grant each individual external consultant the role of BigQuery Viewer

Create a Google Group that contains the consultants and grant the group the role of BigQuery Editor

Create a Google Group that contains the consultants, and grant the group the role of BigQuery Viewer

Question # 15

You are planning to migrate your on-premises VMs to Google Cloud. You need to set up a landing zone in Google Cloud before migrating the VMs. You must ensure that all VMs in your production environment can communicate with each other through private IP addresses. You need to allow all VMs in your Google Cloud organization to accept connections on specific TCP ports. You want to follow Google-recommended practices, and you need to minimize your operational costs. What should you do?

Create individual VPCs per Google Cloud project. Peer all the VPCs together. Apply organization policies on the organization level.

Create individual VPCs for each Google Cloud project. Peer all the VPCs together. Apply hierarchical firewall policies on the organization level.

Create a host VPC project with each production project as its service project. Apply organization policies on the organization level.

Create a host VPC project with each production project as its service project. Apply hierarchical firewall policies on the organization level.

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

The goal is to create a landing zone facilitating private IP communication across production projects and apply organization-wide firewall rules, following best practices and minimizing operational costs.

Network Structure:Individual VPCs with Peering (A, B): While VPC Peering allows private connectivity, managing a full mesh or complex peering topology across many projects becomes operationally complex and can hit peering limits. It's not the recommended pattern for centralized connectivity in a landing zone.

Shared VPC (C, D): This is the Google-recommended practice for scenarios where resources from multiple projects need to communicate privately within a common VPC network. A central host project owns the network, and service projects use it. This simplifies network administration and connectivity.

Firewall Rules:Organization Policies (A, C): These enforce organizational constraints (e.g., disable external IPs, restrict locations) but do not define specific network firewall rules (like allowing TCP ports).

Hierarchical Firewall Policies (B, D): These allow defining firewall rules at the Organization or Folder level, which are inherited by resources in descendant projects/folders. This is the mechanism to apply consistent firewall rules (like allowing specific TCP ports) across all VMs in the organization (or a specific folder) efficiently, without managing rules in each individual VPC or project.

Combining Shared VPC for the network structure (best practice for cross-project private communication and central management) with Hierarchical Firewall Policies (for applying organization-wide firewall rules) meets all requirements efficiently and follows Google recommendations.

[References:, , Shared VPC Overview: "Shared VPC allows an organization to connect resources from multiple projects to a common Virtual Private Cloud (VPC) network..." - https://cloud.google.com/vpc/docs/shared-vpc , Hierarchical firewall policies: "Hierarchical firewall policies let you create and enforce a consistent firewall policy across your organization... They can be configured to explicitly deny traffic, or allow traffic..." - https://cloud.google.com/firewall/docs/hierarchical-firewall-policies, Google Cloud security foundations guide: Often recommends Shared VPC and centralized firewall management (using Hierarchical Firewalls or traditional firewalls with tags in the host project) as part of a secure landing zone. - (Conceptual reference, specific document may vary), , , ]

Question # 16

You are working for a startup that was officially registered as a business 6 months ago. As your customer base grows, your use of Google Cloud increases. You want to allow all engineers to create new projects without asking them for their credit card information. What should you do?

Create a Billing account, associate a payment method with it, and provide all project creators with permission to associate that billing account with their projects.

Grant all engineer’s permission to create their own billing accounts for each new project.

Apply for monthly invoiced billing, and have a single invoice tor the project paid by the finance team.

Create a billing account, associate it with a monthly purchase order (PO), and send the PO to Google Cloud.

Question # 17

An application generates daily reports in a Compute Engine virtual machine (VM). The VM is in the project corp-iot-insights. Your team operates only in the project corp-aggregate-reports and needs a copy of the daily exports in the bucket corp-aggregate-reports-storage. You want to configure access so that the daily reports from the VM are available in the bucket corp-aggregate-reports-storage and use as few steps as possible while following Google-recommended practices. What should you do?

Move both projects under the same folder.

Grant the VM Service Account the role Storage Object Creator on corp-aggregate-reports-storage.

Create a Shared VPC network between both projects. Grant the VM Service Account the role Storage Object Creator on corp-iot-insights.

Make corp-aggregate-reports-storage public and create a folder with a pseudo-randomized suffix name. Share the folder with the IoT team.

Question # 18

You are deploying an application to Cloud Run. Your application requires the use of an API that runs on Google Kubernetes Engine (GKE). You need to ensure that your Cloud Run service can privately reach the API on GKE, and you want to follow Google-recommended practices. What should you do?

Deploy an ingress resource on the GKE cluster to expose the API to the internet. Use Cloud Armor to filter for IP addresses that can connect to the API. On the Cloud Run service, configure the application to fetch its public IP address and update the Cloud Armor policy on startup to allow this IP address to call the API on ports 80 and 443.

Create an egress firewall rule on the VPC to allow connections to 0.0.0.0/0 on ports 80 and 443.

Create an ingress firewall rule on the VPC to allow connections from 0.0.0.0/0 on ports 80 and 443.

Deploy an internal Application Load Balancer to expose the API on GKE to the VPC. Configure Cloud DNS with the IP address of the internal Application Load Balancer. Deploy a Serverless VPC Access connector to allow the Cloud Run service to call the API through the FQDN on Cloud DNS.

Explanation:

The requirement is for private communication between a Cloud Run service and a GKE API, following best practices.

Option A exposes the GKE API to the public internet, which violates the "privately reach" requirement. Relying on dynamic IP allowlisting with Cloud Armor is complex and less secure than private networking.

Options B and C configure overly permissive firewall rules (allowing all egress or ingress) and do not establish the necessary private network path between Cloud Run (which normally runs outside your VPC) and the GKE cluster within your VPC.

Option D describes the standard Google-recommended pattern for this scenario:

Internal Application Load Balancer (ILB): Expose the GKE service (API) using an ILB. This gives the service a private IP address accessible only within the VPC network (or connected networks).

Cloud DNS: Create a private DNS zone and record pointing a fully qualified domain name (FQDN) to the ILB's private IP address. This allows services to reach the API via a stable name instead of an IP.

Serverless VPC Access Connector: This connector creates a bridge allowing serverless services like Cloud Run to send traffic into your VPC network.

Cloud Run Configuration: Configure the Cloud Run service to use the VPC Access connector. The application code can then call the GKE API using its private FQDN registered in Cloud DNS.

This setup ensures traffic flows entirely over private networks (within the VPC via the ILB and through the VPC Access connector), meeting the private communication requirement securely and reliably.

[References:, Serverless VPC Access: "Serverless VPC Access lets your serverless environment send requests to your VPC network..." - https://cloud.google.com/vpc/docs/serverless-vpc-access, Internal Application Load Balancer Overview: "Google Cloud internal Application Load Balancers are regional, proxy-based Layer 7 load balancers that enable you to run and scale your services behind an internal IP address..." - https://cloud.google.com/load-balancing/docs/internal, Connecting from Cloud Run to a VPC network: Documentation often outlines patterns using VPC Access Connectors and Internal Load Balancers or Private Service Connect. - https://cloud.google.com/run/docs/configuring/connecting-vpc, GKE Internal Load Balancing: How to expose GKE services internally. - https://cloud.google.com/kubernetes-engine/docs/how-to/internal-load-balancing, , , ]

Question # 19

Several employees at your company have been creating projects with Cloud Platform and paying for it with their personal credit cards, which the company reimburses. The company wants to centralize all these projects under a single, new billing account. What should you do?

Contact cloud-billing@google.com with your bank account details and request a corporate billing account for your company.

Create a ticket with Google Support and wait for their call to share your credit card details over the phone.

In the Google Platform Console, go to the Resource Manage and move all projects to the root Organization.

In the Google Cloud Platform Console, create a new billing account and set up a payment method.

Question # 20

You have production and test workloads that you want to deploy on Compute Engine. Production VMs need to be in a different subnet than the test VMs. All the VMs must be able to reach each other over internal IP without creating additional routes. You need to set up VPC and the 2 subnets. Which configuration meets these requirements?

Create a single custom VPC with 2 subnets. Create each subnet in a different region and with a different CIDR range.

Create a single custom VPC with 2 subnets. Create each subnet in the same region and with the same CIDR range.

Create 2 custom VPCs, each with a single subnet. Create each subnet is a different region and with a different CIDR range.

Create 2 custom VPCs, each with a single subnet. Create each subnet in the same region and with the same CIDR range.

Question # 21

Your company is seeking a scalable solution to retain and explore application logs hosted on Compute Engine. You must be able to analyze your logs with SQL queries, and you want to be able to create charts to identify patterns and trends in your logs over time. You want to follow Google-recommended practices and minimize your operational costs. What should you do?

Use a custom script to push your application logs to Cloud SQL for exploration.

Ingest your application logs to Cloud Logging by using Ops Agent, and explore your logs in Logs Explorer.

Ingest your application logs to Cloud Logging by using Ops Agent, and explore your logs with Log Analytics.

Use a custom script to push your application logs to BigQuery for exploration.

Question # 22

You are building a multi-player gaming application that will store game information in a database. As the popularity of the application increases, you are concerned about delivering consistent performance. You need to ensure an optimal gaming performance for global users, without increasing the management complexity. What should you do?

Use Cloud SQL database with cross-region replication to store game statistics in the EU, US, and APAC regions.

Use Cloud Spanner to store user data mapped to the game statistics.

Use BigQuery to store game statistics with a Redis on Memorystore instance in the front to provide global consistency.

Store game statistics in a Bigtable database partitioned by username.

Question # 23

You need to extract text from audio files by using the Speech-to-Text API. The audio files are pushed to a Cloud Storage bucket. You need to implement a fully managed, serverless compute solution that requires authentication and aligns with Google-recommended practices. You want to automate the call to the API by submitting each file to the API as the audio file arrives in the bucket. What should you do?

Run a Kubernetes job to scan the bucket regularly for incoming files, and call the Speech-to-Text API for each unprocessed file.

Create an App Engine standard environment triggered by Cloud Storage bucket events to submit the file URI to the Google Speech-to-Text API.

Run a Python script by using a Linux cron job in Compute Engine to scan the bucket regularly for incoming files, and call the Speech-to-Text API for each unprocessed file.

Create a Cloud Function triggered by Cloud Storage bucket events to submit the file URI to the Google Speech-to-Text API.

Question # 24

The sales team has a project named Sales Data Digest that has the ID acme-data-digest You need to set up similar Google Cloud resources for the marketing team but their resources must be organized independently of the sales team. What should you do?

Grant the Project Editor role to the Marketing learn for acme data digest

Create a Project Lien on acme-data digest and then grant the Project Editor role to the Marketing team

Create another protect with the ID acme-marketing-data-digest for the Marketing team and deploy the resources there

Create a new protect named Meeting Data Digest and use the ID acme-data-digest Grant the Project Editor role to the Marketing team.

Question # 25

You are building a backend service for an ecommerce platform that will persist transaction data from mobile and web clients. After the platform is launched, you expect a large volume of global transactions. Your business team wants to run SQL queries to analyze the data. You need to build a highly available and scalable data store for the platform. What should you do?

Create a multi-region Cloud Spanner instance with an optimized schema.

Create a multi-region Firestore database with aggregation query enabled.

Create a multi-region Cloud SQL for PostgreSQL database with optimized indexes.

Create a multi-region BigQuery dataset with optimized tables.

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Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer Free Practice Exam Questions (2025 Updated)

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