You want to enable your development team to deploy new features to an existing Cloud Run service in production. To minimize the risk associated with a new revision, you want to reduce the number of customers who might be affected by an outage without introducing any development or operational costs to your customers. You want to follow Google-recommended practices for managing revisions to a service. What should you do?

Gradually roll out the new revision and split customer traffic between the revisions to allow rollback in case a problem occurs.

Deploy your application to a second Cloud Run service, and ask your customers to use the second Cloud Run service.

Ask your customers to retry access to your service with exponential backoff to mitigate any potential problems after the new revision is deployed.

Gradually roll out the new revision and split customer traffic between the revisions to allow rollback in case a problem occurs.

Send all customer traffic to the new revision, and roll back to a previous revision if you witness any problems in production.

You have two Google Cloud projects: project-a with VPC vpc-a (10.0.0.0/16) and project-b with VPC vpc-b (10.8.0.0/16). Your frontend application resides in vpc-a and the backend API services ate deployed in vpc-b. You need to efficiently and cost-effectively enable communication between these Google Cloud projects. You also want to follow Google-recommended practices. What should you do?

Create VPC Network Peering between vpc-a and vpc-b.

Configure a Cloud Router in vpc-a and another Cloud Router in vpc-b.

Configure a Cloud Interconnect connection between vpc-a and vpc-b.

Create VPC Network Peering between vpc-a and vpc-b.

Create an OpenVPN connection between vpc-a and vpc-b.

You have a VM instance running in a VPC with single-stack subnets. You need to ensure that the VM instance has a fixed IP address so that other services hosted in the same VPC can communicate with the VM. You want to follow Google-recommended practices while minimizing cost. What should you do?

Promote the existing IP address of the VM to become a static external IP address.

Reserve a new static external IP address and assign the new IP address to the VM.

Promote the existing IP address of the VM to become a static external IP address.

Reserve a new static external IPv6 address and assign the new IP address to the VM.

Promote the existing IP address of the VM to become a static internal IP address.

Your company uses BigQuery to store and analyze data. Upon submitting your query in BigQuery, the query fails with a quotaExceeded error. You need to diagnose the issue causing the error. What should you do?Choose 2 answers

Search errors in Cloud Audit Logs to analyze the issue.

View errors in Cloud Monitoring to analyze the issue.

Search errors in Cloud Audit Logs to analyze the issue.

Configure Cloud Trace to analyze the issue.

View errors in Cloud Monitoring to analyze the issue.

Use the information schema views to analyze the underlying issue.

Use BigQuery Bl Engine to analyzetheissue.

Your web application is hosted on Cloud Run and needs to query a Cloud SOL database. Every morning during a traffic spike, you notice API quota errors in Cloud SOL 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 maximum number of Cloud Run instances.

Modify the minimum number of Cloud Run instances.

Set a minimum concurrent requests environment variable for the application.

Modify the maximum number of Cloud Run instances.

You are planning to migrate the following on-premises data management solutions to Google Cloud:* One MySQL cluster for your main database* Apache Kafka for your event streaming platform* One Cloud SOL for PostgreSOL database for your analytical and reporting needsYou want to implement Google-recommended solutions for the migration. You need to ensure that the new solutions provide global scalability and require minimal operational and infrastructure management. What should you do?

Migrate from MySQL to Cloud Spanner, from Kafka to Pub/Sub. and from Cloud SQL for PostgreSQL to BigQuery

Migrate from MySQL to Cloud SQL, from Kafka to Memorystore, and from Cloud SQL for PostgreSQL to Cloud SQL

Migrate from MySQL to Cloud Spanner, from Kafka to Memorystore, and from Cloud SOL for PostgreSQL to Cloud SQL

Migrate from MySQL to Cloud SOL, from Kafka to Pub/Sub, and from Cloud SOL for PostgreSQL to BigQuery.

Migrate from MySQL to Cloud Spanner, from Kafka to Pub/Sub. and from Cloud SQL for PostgreSQL to BigQuery

You need to deploy a single stateless web application with a web interface and multiple endpoints. For security reasons, the web application must be reachable from an internal IP address from your company's private VPC and on-premises network. You also need to update the web application multiple times per day with minimal effort and want to manage a minimal amount of cloud infrastructure. What should you do?

Deploy the web application on Google Kubernetes Engine standard edition with an internal ingress.

Deploy the web application on Cloud Run with Private Google Access configured

Deploy the web application to GKE Autopilot with Private Google Access configured

Deploy the web application on Cloud Run with Private Service Connect configured.

You use Cloud Logging lo capture application logs. You now need to use SOL to analyze the application logs in Cloud Logging, and you want to follow Google-recommended practices. What should you do?

Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.

Develop SQL queries by using Gemini for Google Cloud.

Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.

Create a schema for the storage bucket and run SQL queries for the data in the bucket.

Export logs to a storage bucket and create an external view in BigQuery.

Your company is running a critical workload on a single Compute Engine VM instance. Your company's disaster recovery policies require you to backup the entire instance's disk data every day. The backups must be retained for 7 days. You must configure a backup solution that complies with your company's security policies and requires minimal setup and configuration. What should you do?

Configure daily scheduled persistent disk snapshots with a retention period of 7 days.

Configure the instance to use persistent disk asynchronous replication.

Configure daily scheduled persistent disk snapshots with a retention period of 7 days.

Configure Cloud Scheduler to trigger a Cloud Function each day that creates a new machine image and deletes machine images that are older than 7 days.

Configure a bash script using gsutil to run daily through a cron job. Copy the disk's files to a Cloud Storage bucket with archive storage class and an object lifecycle rule to delete the objects after 7 days.

You want to deploy a new containerized application into Google Cloud by using a Kubernetes manifest. You want to have full control over the Kubernetes deployment, and at the same time, you want to minimize configuring infrastructure. What should you do?

Deploy the application on GKE Autopilot.

Deploy the application on GKE Standard.

Deploy the application on Cloud Functions.

Deploy the application on Cloud Run.

You have several hundred microservice applications running in a Google Kubernetes Engine (GKE) cluster. Each microservice is a deployment with resource limits configured for each container in the deployment. You've observed that the resource limits for memory and CPU are not appropriately set for many of the microservices. You want to ensure that each microservice has right sized limits for memory and CPU. What should you do?

Configure a Vertical Pod Autoscaler for each microservice.

Modify the cluster's node pool machine type and choose a machine type with more memory and CPU.

Configure a Horizontal Pod Autoscaler for each microservice.

Configure GKE cluster autoscaling.

Configure a Vertical Pod Autoscaler for each microservice.

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

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.

You are deploying an application on Google Cloud that requires a relational database for storage. To satisfy your company's security policies, your application must connect to your database through an encrypted and authenticated connection that requires minimal management and integrates with Identity and Access Management (IAM). What should you do?

Deploy a Cloud SOL database and configure IAM database authentication. Access the database through the Cloud SQL Auth Proxy.

Deploy a Cloud SQL database with the SSL mode set to encrypted only, configure SSL/TLS client certificates, and configure a database user and password.

Deploy a Cloud SOL database and configure IAM database authentication. Access the database through the Cloud SQL Auth Proxy.

Deploy a Cloud SQL database with the SSL mode set to encrypted only, configure SSL/TLS client certificates, and configure IAM database authentication.

Deploy a Cloud SQL database and configure a database user and password. Access the database through the Cloud SQL Auth Proxy.

Your preview application, deployed on a single-zone Google Kubernetes Engine (GKE) cluster in us-centrall, has gained popularity. You are now ready to make the application generally available. You need to deploy the application to production while ensuring high availability and resilience. You also want to follow Google-recommended practices. What should you do?

Use the gcloud container clusters create-auto command to create an autopilot cluster and deploy the application to it.

Use the gcloud container clusters create command with the options--enable-multi-networking and--enable- autoscaling to create an autoscaling zonal cluster and deploy the application to it.

Use the gcloud container clusters create-auto command to create an autopilot cluster and deploy the application to it.

Use the gcloud container clusters update command with the option---region us-centrall to update the cluster and deploy the application to it.

Use the gcloud container clusters update command with the option---node-locations us-centrall-a,us-centrall-b to update the cluster and deploy the application to the nodes.

You need to deploy a third-party software application onto a single Compute Engine VM instance. The application requires the highest speed read and write disk access for the internal database. You need to ensure the instance will recover on failure. What should you do?

Create an instance template. Set the disk type to be an SSD Persistent Disk. Launch the instance template as part of a stateful managed instance group.

Create an instance template. Set the disk type to be an SSD Persistent Disk. Launch the instance template as part of a stateless managed instance group.

Create an instance template. Set the disk type to be Hyperdisk Extreme. Launch the instance template as part of a stateful managed instance group.

Create an instance template. Set the disk type to be Hyperdisk Extreme. Launch the instance template as part of a stateless managed instance group.

Your company was recently impacted by a service disruption that caused multiple Dataflow jobs to get stuck, resulting in significant downtime in downstream applications and revenue loss. You were able to resolve the issue by identifying and fixing an error you found in the code. You need to design a solution with minimal management effort to identify when jobs are stuck in the future to ensure that this issue does not occur again. What should you do?

Set up Cloud Monitoring alerts on the data freshness metric for the Dataflow jobs to receive a notification when a certain threshold is reached.

Set up Error Reporting to identify stack traces that indicate slowdowns in Dataflow jobs. Set up alerts based on these log entries.

Use the Personalized Service Health dashboard to identify issues with Dataflow jobs across regions.

Update the Dataflow job configurations to send messages to a Pub/Sub topic when there are delays. Configure a backup Dataflow job to process jobs that are delayed. Use Cloud Tasks to trigger an alert when messages are pushed to the Pub/Sub topic.

Set up Cloud Monitoring alerts on the data freshness metric for the Dataflow jobs to receive a notification when a certain threshold is reached.

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 dataset.

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.

You are migrating your company's on-premises compute resources to Google Cloud. You need to deploy batch processing jobs that run every night. The jobs require significant CPU and memory for several hours but can tolerate interruptions. You must ensure that the deployment is cost-effective. What should you do?

Use Spot VMs on Compute Engine.

Containerize the batch processing jobs and deploy them on Compute Engine.

Use custom machine types on Compute Engine.

Use the M1 machine series on Compute Engine.

Use Spot VMs on Compute Engine.

You are managing the security configuration of your company's Google Cloud organization. The Operations team needs specific permissions on both a Google Kubernetes Engine (GKE) cluster and a Cloud SQL instance. Two predefined Identity and Access Management (IAM) roles exist that contain a subset of the permissions needed by the team. You need to configure the necessary IAM permissions for this team while following Google-recommended practices. What should you do?

Create a custom IAM role that includes only the required permissions from the predefined roles.

Grant the team the two predefined IAM roles.

Create a custom IAM role that combines the permissions from the two relevant predefined roles.

Create a custom IAM role that includes only the required permissions from the predefined roles.

Grant the team the IAM roles of Kubernetes Engine Admin and Cloud SQL Admin.

Your digital media company stores a large number of video files on-premises. Each video file ranges from 100 MB to 100 GB. You are currently storing 150 TB of video data in your on-premises network, with no room for expansion. You need to migrate all infrequently accessed video files older than one year to Cloud Storage to ensure that on-premises storage remains available for new files. You must also minimize costs and control bandwidth usage. What should you do?

Use Storage Transfer Service to move the data from the selected on-premises file storage systems to a Cloud Storage bucket.

Create a Cloud Storage bucket. Establish an Identity and Access Management (IAM) role with write permissions to the bucket. Use the gsutil tool to directly copy files over the network to Cloud Storage.

Set up a Cloud Interconnect connection between the on-premises network and Google Cloud. Establish a private endpoint for Filestore access. Transfer the data from the existing Network File System (NFS) to Filestore.

Use Transfer Appliance to request an appliance. Load the data locally, and ship the appliance back to Google for ingestion into Cloud Storage.

Use Storage Transfer Service to move the data from the selected on-premises file storage systems to a Cloud Storage bucket.

You are developing an internet of things (IoT) application that captures sensor data from multiple devices that have already been set up. You need to identify the global data storage product your company should use to store this data. You must ensure that the storage solution you choose meets your requirements of sub-millisecond latency. What should you do?

Store the IoT data in Bigtable.

Store the IoT data in Spanner. Use caches to speed up the process and avoid latencies.

Store the IoT data in Bigtable.

Capture IoT data in BigQuery datasets.

Store the IoT data in Cloud Storage. Implement caching by using Cloud CDN.

You are managing an application deployed on Cloud Run. The development team has released a new version of the application. You want to deploy and redirect traffic to this new version of the application. To ensure traffic to the new version of the application is served with no startup time, you want to ensure that there are two idle instances available for incoming traffic before adjusting the traffic flow. You also want to minimize administrative overhead. What should you do?

Configure revision autoscaling for the new revision and set the minimum number of instances to 2.

Ensure the checkbox 'Serve this revision immediately' is unchecked when deploying the new revision. Before changing the traffic rules, use a traffic simulation tool to send load to the new revision.

Configure service autoscaling and set the minimum number of instances to 2.

Configure revision autoscaling for the new revision and set the minimum number of instances to 2.

Configure revision autoscaling for the existing revision and set the minimum number of instances to 2.

You are deploying an application to Google Kubernetes Engine (GKE). The application needs to make API calls to a private Cloud Storage bucket. You need to configure your application Pods to authenticate to the Cloud Storage API, but your organization policy prevents the usage of service account keys. You want to follow Google-recommended practices. What should you do?

Create the GKE cluster with Workload Identity Federation. Create a Google service account and a Kubernetes ServiceAccount, and configure both service accounts to use Workload Identity Federation. Attach the Kubernetes ServiceAccount to the application Pods and configure the Google service account to access the bucket with Identity and Access Management (IAM).

Create the GKE cluster and deploy the application. Request a security exception to create a Google service account key. Set the constraints/iam.serviceAccountKeyExpiryHours organization policy to 8 hours.

Create the GKE cluster and deploy the application. Request a security exception to create a Google service account key. Set the constraints/iam.serviceAccountKeyExpiryHours organization policy to 24 hours.

Create the GKE cluster with Workload Identity Federation. Configure the default node service account to access the bucket. Deploy the application into the cluster so the application can use the node service account permissions. Use Identity and Access Management (IAM) to grant the service account access to the bucket.

Create the GKE cluster with Workload Identity Federation. Create a Google service account and a Kubernetes ServiceAccount, and configure both service accounts to use Workload Identity Federation. Attach the Kubernetes ServiceAccount to the application Pods and configure the Google service account to access the bucket with Identity and Access Management (IAM).

Your company is migrating its workloads to Google Cloud due to an expiring data center contract. The on-premises environment and Google Cloud are not connected. You have decided to follow a lift-and-shift approach, and you plan to modernize the workloads in a future project. Several old applications connect to each other through hard-coded internal IP addresses. You want to migrate these workloads quickly without modifying the application code. You also want to maintain all functionality. What should you do?

Create a VPC with the same CIDR ranges as your on-premises network. When migrating individual workloads, assign each workload the same static internal IP address.

Create a VPC with non-overlapping CIDR ranges compared to your on-premises network. When migrating individual workloads, assign each workload a new static internal IP address.

Migrate your DNS server first. Configure Cloud DNS with a forwarding zone to your migrated DNS server. Then migrate all other workloads with ephemeral internal IP addresses.

Migrate all workloads to a single VPC subnet. Configure Cloud NAT for the subnet and manually assign a static IP address to the Cloud NAT gateway.

Create a VPC with the same CIDR ranges as your on-premises network. When migrating individual workloads, assign each workload the same static internal IP address.

Your company uses a multi-cloud strategy that includes Google Cloud. You want to centralize application logs in a third-party software-as-a-service (SaaS) tool from all environments. You need to integrate logs originating from Cloud Logging, and you want to ensure the export occurs with the least amount of delay possible. What should you do?

Create a Cloud Logging sink and configure Pub/Sub as the destination. Configure the SaaS tool to subscribe to the Pub/Sub topic to retrieve the logs.

Use a Cloud Scheduler cron job to trigger a Cloud Function that queries Cloud Logging and sends the logs to the SaaS tool.

Create a Cloud Logging sink and configure Pub/Sub as the destination. Configure the SaaS tool to subscribe to the Pub/Sub topic to retrieve the logs.

Create a Cloud Logging sink and configure Cloud Storage as the destination. Configure the SaaS tool to read the Cloud Storage bucket to retrieve the logs.

Create a Cloud Logging sink and configure BigQuery as the destination. Configure the SaaS tool to query BigQuery to retrieve the logs.

You manage a VPC network in Google Cloud with a subnet that is rapidly approaching its private IP address capacity. You expect the number of Compute Engine VM instances in the same region to double within a week. You need to implement a Google-recommended solution that minimizes operational costs and does not require downtime. What should you do?

Use the Google Cloud CLI tool to expand the primary IP range of your subnet.

Create a second VPC with the same subnet IP range, and connect this VPC to the existing VPC by using VPC Network Peering.

Delete the existing subnet, and create a new subnet with double the IP range available.

Use the Google Cloud CLI tool to expand the primary IP range of your subnet.

Permit additional traffic from the expected range of private IP addresses to reach your VMs by configuring firewall rules.

Your company is modernizing its applications and refactoring them to containerized microservices. You need to deploy the infrastructure on Google Cloud so that teams can deploy their applications. The applications cannot be exposed publicly. You want to minimize management and operational overhead. What should you do?

Provision a Google Kubernetes Engine (GKE) Autopilot cluster.

Provision a Standard zonal Google Kubernetes Engine (GKE) cluster.

Provision a fleet of Compute Engine instances and install Kubernetes.

Provision a Google Kubernetes Engine (GKE) Autopilot cluster.

Provision a Standard regional Google Kubernetes Engine (GKE) cluster.

You are deploying a web application using Compute Engine. You created a managed instance group (MIG) to host the application. You want to follow Google-recommended practices to implement a secure and highly available solution. What should you do?

Use an Application Load Balancer for the MIG and an A record in your DNS public zone with the load balancer's IP address.

Use a proxy Network Load Balancer for the MIG and an A record in your DNS private zone with the load balancer's IP address.

Use a proxy Network Load Balancer for the MIG and a CNAME record in your DNS public zone with the load balancer's IP address.

Use an Application Load Balancer for the MIG and a CNAME record in your DNS private zone with the load balancer's IP address.

Use an Application Load Balancer for the MIG and an A record in your DNS public zone with the load balancer's IP address.

You are migrating your on-premises workload to Google Cloud. Your company is implementing its Cloud Billing configuration and requires access to a granular breakdown of its Google Cloud costs. You need to ensure that the Cloud Billing datasets are available in BigQuery so you can conduct a detailed analysis of costs. What should you do?

Enable Cloud Billing data export to BigQuery when you create a Cloud Billing account.

Enable the BigQuery API and ensure that the BigQuery User IAM role is selected. Change the BigQuery dataset to select a data location.

Create a Cloud Billing account. Enable the BigQuery Data Transfer Service API to export pricing data.

Enable Cloud Billing data export to BigQuery when you create a Cloud Billing account.

Enable Cloud Billing on the project and link a Cloud Billing account. Then view the billing data table in the BigQuery dataset.

Your company's developers use an automation that you recently built to provision Linux VMs in Compute Engine within a Google Cloud project to perform various tasks. You need to manage the Linux account lifecycle and access for these users. You want to follow Google-recommended practices to simplify access management while minimizing operational costs. What should you do?

Enable OS Login for all VMs. Use IAM roles to grant user permissions.

Enable OS Login for all VMs. Write custom startup scripts to update user permissions.

Require your developers to create public SSH keys. Make the owner of the public key the root user.

Require your developers to create public SSH keys. Write custom startup scripts to update user permissions.

You are managing a stateful application deployed on Google Kubernetes Engine (GKE) that can only have one replica. You recently discovered that the application becomes unstable at peak times. You have identified that the application needs more CPU than what has been configured in the manifest at these peak times. You want Kubernetes to allocate the application sufficient CPU resources during these peak times, while ensuring cost efficiency during off-peak periods. What should you do?

Configure a Vertical Pod Autoscaler on the Deployment.

Enable cluster autoscaling on the GKE cluster.

Configure a Vertical Pod Autoscaler on the Deployment.

Configure a Horizontal Pod Autoscaler on the Deployment.

Enable node auto-provisioning on the GKE cluster.

You host your website on Compute Engine. The number of global users visiting your website is rapidly expanding. You need to minimize latency and support user growth in multiple geographical regions. You also want to follow Google-recommended practices and minimize operational costs. Which two actions should you take?(Choose 2 answers)

Deploy your VMs in multiple Google Cloud regions closest to your users' geographical locations.

Use an external Application Load Balancer in Global mode.

Deploy all of your VMs in a single Google Cloud region with the largest available CIDR range.

Deploy your VMs in multiple Google Cloud regions closest to your users' geographical locations.

Use an external Application Load Balancer in Regional mode.

Use an external Application Load Balancer in Global mode.

Google Associate Cloud Engineer Practice Test 8 - Free Online Exam Questions 281-315

Your company requires that Google Cloud products are created with a specific configuration to comply with your company's security policies You need to implement a mechanism that will allow software engineers at your company to deploy and update Google Cloud products in a preconfigured and approved manner. What should you do?

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Google Associate Cloud Engineer Practice Test 8

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