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WorksheetsPCA-4
Total questions: 50
Worksheet time: 4hrs 10mins
You need to ensure reliability for your application and operations by supporting reliable task scheduling for compute on GCP. Leveraging Google best practices, what should you do?
Using the Cron service provided by App Engine, publish messages directly to a message-processing utility service running on Compute Engine instances.
Using the Cron service provided by App Engine, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.
Using the Cron service provided by Google Kubernetes Engine (GKE), publish messages directly to a message- processing utility service running on Compute Engine instances.
Using the Cron service provided by GKE, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.
Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company’s mobile and web-facing applications will be deployed on-premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling 900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection.
What actions will meet your company’s needs?
Compress and upload both archived files and files uploaded daily using the gsutil –m option.
Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.
Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish one Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily using the gsutil –m option.
Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily.
You are developing a globally scaled frontend for a legacy streaming backend data API. This API expects events in strict chronological order with no repeat data for proper processing.
Which products should you deploy to ensure guaranteed-once FIFO (first-in, first-out) delivery of data?
Cloud Pub/Sub alone
Cloud Pub/Sub to Cloud Dataflow
Cloud Pub/Sub to Stackdriver
Cloud Pub/Sub to Cloud SQL
Your company is planning to perform a lift and shift migration of their Linux RHEL 6.5+ virtual machines. The virtual machines are running in an on-premises VMware environment. You want to migrate them to Compute Engine following Google-recommended practices. What should you do?
A. 1. Define a migration plan based on the list of the applications and their dependencies.
2. Migrate all virtual machines into Compute Engine individually with Migrate for Compute Engine.
A. 1. Perform an assessment of virtual machines running in the current VMware environment.
2. Create images of all disks. Import disks on Compute Engine.
3. Create standard virtual machines where the boot disks are the ones you have imported.
1. Perform an assessment of virtual machines running in the current VMware environment.
2. Define a migration plan, prepare a Migrate for Compute Engine migration RunBook, and execute the migration.
1. Perform an assessment of virtual machines running in the current VMware environment.
2. Install a third-party agent on all selected virtual machines.
3. Migrate all virtual machines into Compute Engine.
You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud. What should you do?
Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use an HTTP load balancer in front of the instances.
Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use a network load balancer in front of the instances.
Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use an HTTP load balancer in front of the instances.
Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use a network load balancer in front of the instances.
Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?
Use OpenVPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
Configure a direct peering connection between the on-premises environment and Google Cloud.
Use Cloud VPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
Configure a Cloud Dedicated Interconnect connection between the on-premises environment and Google Cloud.
You are managing an application deployed on Cloud Run for Anthos, and you need to define a strategy for deploying new versions of the application. You want to evaluate the new code with a subset of production traffic to decide whether to proceed with the rollout. What should you do?
Deploy a new revision to Cloud Run with the new version. Configure traffic percentage between revisions.
Deploy a new service to Cloud Run with the new version. Add a Cloud Load Balancing instance in front of both services.
In the Google Cloud Console page for Cloud Run, set up continuous deployment using Cloud Build for the development branch. As part of the Cloud Build trigger, configure the substitution variable TRAFFIC_PERCENTAGE with the percentage of traffic you want directed to a new version.
In the Google Cloud Console, configure Traffic Director with a new Service that points to the new version of the application on Cloud Run. Configure Traffic Director to send a small percentage of traffic to the new version of the application.
You are monitoring Google Kubernetes Engine (GKE) clusters in a Cloud Monitoring workspace. As a Site Reliability Engineer (SRE), you need to triage incidents quickly. What should you do?
Navigate the predefined dashboards in the Cloud Monitoring workspace, and then add metrics and create alert policies.
Navigate the predefined dashboards in the Cloud Monitoring workspace, create custom metrics, and install alerting software on a Compute Engine instance.
Write a shell script that gathers metrics from GKE nodes, publish these metrics to a Pub/Sub topic, export the data to BigQuery, and make a Data Studio dashboard.
Create a custom dashboard in the Cloud Monitoring workspace for each incident, and then add metrics and create alert policies.
You are implementing a single Cloud SQL MySQL second-generation database that contains business-critical transaction data. You want to ensure that the minimum amount of data is lost in case of catastrophic failure. Which two features should you implement? (Choose two.)
Sharding
Read replicas
Binary logging
Automated backups
Semisynchronous replication
You are working at a sports association whose members range in age from 8 to 30. The association collects a large amount of health data, such as sustained injuries. You are storing this data in BigQuery.
Current legislation requires you to delete such information upon request of the subject. You want to design a solution that can accommodate such a request. What should you do?
Use a unique identifier for each individual. Upon a deletion request, delete all rows from BigQuery with this identifier.
When ingesting new data in BigQuery, run the data through the Data Loss Prevention (DLP) API to identify any personal information. As part of the DLP scan, save the result to Data Catalog. Upon a deletion request, query Data Catalog to find the column with personal information.
Create a BigQuery view over the table that contains all data. Upon a deletion request, exclude the rows that affect the subject’s data from this view. Use this view instead of the source table for all analysis tasks.
Use a unique identifier for each individual. Upon a deletion request, overwrite the column with the unique identifier with a salted SHA256 of its value.
Your company has announced that they will be outsourcing operations functions. You want to allow developers to easily stage new versions of a cloud-based application in the production environment and allow the outsourced operations team to autonomously promote staged versions to production. You want to minimize the operational overhead of the solution. Which Google Cloud product should you migrate to?
App Engine
GKE On-Prem
Compute Engine
Google Kubernetes Engine
Your company is running its application workloads on Compute Engine. The applications have been deployed in production, acceptance, and development environments. The production environment is business-critical and is used 24/7, while the acceptance and development environments are only critical during office hours. Your CFO has asked you to optimize these environments to achieve cost savings during idle times. What should you do?
Create a shell script that uses the gcloud command to change the machine type of the development and acceptance instances to a smaller machine type outside of office hours. Schedule the shell script on one of the production instances to automate the task.
Use Cloud Scheduler to trigger a Cloud Function that will stop the development and acceptance environments after office hours and start them just before office hours.
Deploy the development and acceptance applications on a managed instance group and enable autoscaling.
Use regular Compute Engine instances for the production environment, and use preemptible VMs for the acceptance and development environments.
You are moving an application that uses MySQL from on-premises to Google Cloud. The application will run on Compute Engine and will use Cloud SQL. You want to cut over to the Compute Engine deployment of the application with minimal downtime and no data loss to your customers. You want to migrate the application with minimal modification. You also need to determine the cutover strategy. What should you do?
1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on- premises MySQL server.
2. Stop the on-premises application.
3. Create a mysqldump of the on-premises MySQL server.
4. Upload the dump to a Cloud Storage bucket.
5. Import the dump into Cloud SQL.
6. Modify the source code of the application to write queries to both databases and read from its local database.
7. Start the Compute Engine application.
8. Stop the on-premises application.
1. Set up Cloud SQL proxy and MySQL proxy.
2. Create a mysqldump of the on-premises MySQL server.
3. Upload the dump to a Cloud Storage bucket.
4. Import the dump into Cloud SQL.
5. Stop the on-premises application.
6. Start the Compute Engine application.
1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on- premises MySQL server.
2. Stop the on-premises application.
3. Start the Compute Engine application, configured to read and write to the on-premises MySQL server.
4. Create the replication configuration in Cloud SQL.
5. Configure the source database server to accept connections from the Cloud SQL replica.
6. Finalize the Cloud SQL replica configuration.
7. When replication has been completed, stop the Compute Engine application.
8. Promote the Cloud SQL replica to a standalone instance
9. Restart the Compute Engine application, configured to read and write to the Cloud SQL standalone instance.
1. Stop the on-premises application.
2. Create a mysqldump of the on-premises MySQL server.
3. Upload the dump to a Cloud Storage bucket.
4. Import the dump into Cloud SQL.
5. Start the application on Compute Engine.
Your organization has decided to restrict the use of external IP addresses on instances to only approved instances. You want to enforce this requirement across all of your Virtual Private Clouds (VPCs). What should you do?
Remove the default route on all VPCs. Move all approved instances into a new subnet that has a default route to an internet gateway.
Create a new VPC in custom mode. Create a new subnet for the approved instances, and set a default route to the internet gateway on this new subnet.
Implement a Cloud NAT solution to remove the need for external IP addresses entirely.
Set an Organization Policy with a constraint on constraints/compute.vmExternalIpAccess. List the approved instances in the allowedValues list.
Your company uses the Firewall Insights feature in the Google Network Intelligence Center. You have several firewall rules applied to Compute Engine instances. You need to evaluate the efficiency of the applied firewall ruleset. When you bring up the Firewall Insights page in the Google Cloud Console, you notice that there are no log rows to display. What should you do to troubleshoot the issue?
Enable Virtual Private Cloud (VPC) flow logging.
Enable Firewall Rules Logging for the firewall rules you want to monitor.
Verify that your user account is assigned the compute.networkAdmin Identity and Access Management (IAM) role.
Install the Google Cloud SDK, and verify that there are no Firewall logs in the command line output.
Your company has sensitive data in Cloud Storage buckets. Data analysts have Identity Access Management (IAM) permissions to read the buckets. You want to prevent data analysts from retrieving the data in the buckets from outside the office network. What should you do?
1. Create a VPC Service Controls perimeter that includes the projects with the buckets.
2. Create an access level with the CIDR of the office network.
1. Create a firewall rule for all instances in the Virtual Private Cloud (VPC) network for source range.
2. Use the Classless Inter-domain Routing (CIDR) of the office network.
1. Create a Cloud Function to remove IAM permissions from the buckets, and another Cloud Function to add IAM permissions to the buckets.
2. Schedule the Cloud Functions with Cloud Scheduler to add permissions at the start of business and remove permissionsatthe endofbusiness.
1. Create a Cloud VPN to the office network.
2. Configure Private Google Access for on-premises hosts.
You have developed a non-critical update to your application that is running in a managed instance group, and have created a new instance template with the update that you want to release. To prevent any possible impact to the application, you don't want to update any running instances. You want any new instances that are created by the managed instance group to contain the new update. What should you do?
Start a new rolling restart operation.
Start a new rolling replace operation.
Start a new rolling update. Select the Proactive update mode.
Start a new rolling update. Select the Opportunistic update mode
Your company is designing its application landscape on Compute Engine. Whenever a zonal outage occurs, the application should be restored in another zone as quickly as possible with the latest application data. You need to design the solution to meet this requirement. What should you do?
Create a snapshot schedule for the disk containing the application data. Whenever a zonal outage occurs, use the latest snapshot to restore the disk in the same zone.
Configure the Compute Engine instances with an instance template for the application, and use a regional persistent disk for the application data. Whenever a zonal outage occurs, use the instance template to spin up the application in another zone in the same region. Use the regional persistent disk for the application data.
Create a snapshot schedule for the disk containing the application data. Whenever a zonal outage occurs, use the latest snapshot to restore the disk in another zone within the same region.
Configure the Compute Engine instances with an instance template for the application, and use a regional persistent disk for the application data. Whenever a zonal outage occurs, use the instance template to spin up the application in another region. Use the regional persistent disk for the application data.
Your company has just acquired another company, and you have been asked to integrate their existing Google Cloud environment into your company’s data center. Upon investigation, you discover that some of the RFC 1918 IP ranges being used in the new company’s Virtual Private Cloud (VPC) overlap with your data center IP space. What should you do to enable connectivity and make sure that there are no routing conflicts when connectivity is established?
Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply new IP addresses so there is no overlapping IP space.
Create a Cloud VPN connection from the new VPC to the data center, and create a Cloud NAT instance to perform NAT on the overlapping IP space.
Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply a custom route advertisement to block the overlapping IP space.
Create a Cloud VPN connection from the new VPC to the data center, and apply a firewall rule that blocks the overlapping IP space.
You need to migrate Hadoop jobs for your company’s Data Science team without modifying the underlying infrastructure. You want to minimize costs and infrastructure management effort. What should you do?
Create a Dataproc cluster using standard worker instances.
Create a Dataproc cluster using preemptible worker instances.
Manually deploy a Hadoop cluster on Compute Engine using standard instances.
Manually deploy a Hadoop cluster on Compute Engine using preemptible instances.
You need to deploy an application on Google Cloud that must run on a Debian Linux environment. The application requires extensive configuration in order to operate correctly. You want to ensure that you can install Debian distribution updates with minimal manual intervention whenever they become available. What should you do?
Create a Compute Engine instance template using the most recent Debian image. Create an instance from this template, and install and configure the application as part of the startup script. Repeat this process whenever a new Google-managed Debian image becomes available.
Create a Debian-based Compute Engine instance, install and configure the application, and use OS patch management to install available updates.
Create an instance with the latest available Debian image. Connect to the instance via SSH, and install and configure the application on the instance. Repeat this process whenever a new Googlemanaged Debian image becomes available.
Create a Docker container with Debian as the base image. Install and configure the application as part of the Docker image creation process. Host the container on Google Kubernetes Engine and restart the container whenever a new update is available.
You have an application that runs in Google Kubernetes Engine (GKE). Over the last 2 weeks, customers have reported that a specific part of the application returns errors very frequently. You currently have no logging or monitoring solution enabled on your GKE cluster. You want to diagnose the problem, but you have not been able to replicate the issue. You want to cause minimal disruption to the application. What should you do?
1. Update your GKE cluster to use Cloud Operations for GKE.
2. Use the GKE Monitoring dashboard to investigate logs from affected Pods.
1. Create a new GKE cluster with Cloud Operations for GKE enabled.
2. Migrate the affected Pods to the new cluster, and redirect traffic for those Pods to the new cluster.
3. Use the GKE Monitoring dashboard to investigate logs from affected Pods.
1. Update your GKE cluster to use Cloud Operations for GKE, and deploy Prometheus.
2. Set an alert to trigger whenever the application returns an error.
1. Create a new GKE cluster with Cloud Operations for GKE enabled, and deploy Prometheus.
2. Migrate the affected Pods to the new cluster, and redirect traffic for those Pods to the new cluster.
3. Set an alert to trigger whenever the application returns an error.
You need to deploy a stateful workload on Google Cloud. The workload can scale horizontally, but each instance needs to read and write to the same POSIX filesystem. At high load, the stateful workload needs to support up to 100 MB/s of writes. What should you do?
Use a persistent disk for each instance.
Use a regional persistent disk for each instance.
Create a Cloud Filestore instance and mount it in each instance.
Create a Cloud Storage bucket and mount it in each instance using gcsfuse.
Your company has an application deployed on Anthos clusters (formerly Anthos GKE) that is running multiple microservices. The cluster has both Anthos Service Mesh and Anthos Config Management configured. End users inform you that the application is responding very slowly. You want to identify the microservice that is causing the delay. What should you do?
Use the Service Mesh visualization in the Cloud Console to inspect the telemetry between the microservices.
Use Anthos Config Management to create a ClusterSelector selecting the relevant cluster. On the Google Cloud Console page for Google Kubernetes Engine, view the Workloads and filter on the cluster. Inspect the configurations of the filtered workloads.
Use Anthos Config Management to create a namespaceSelector selecting the relevant cluster namespace. On the Google Cloud Console page for Google Kubernetes Engine, visit the workloads and filter on the namespace. Inspect the configurations of the filtered workloads.
Reinstall istio using the default istio profile in order to collect request latency. Evaluate the telemetry between the microservices in the Cloud Console.
You are working at a financial institution that stores mortgage loan approval documents on Cloud Storage. Any change to these approval documents must be uploaded as a separate approval file, so you want to ensure that these documents cannot be deleted or overwritten for the next 5 years. What should you do?
Create a retention policy on the bucket for the duration of 5 years. Create a lock on the retention policy.
Create the bucket with uniform bucket-level access, and grant a service account the role of Object Writer. Use the service account to upload new files.
Use a customer-managed key for the encryption of the bucket. Rotate the key after 5 years.
Create the bucket with fine-grained access control, and grant a service account the role of Object Writer. Use the service account to upload new files.
Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?
Have each developer install a pre-commit hook on their workstation that tests the code and builds the container when committing on the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
Install a post-commit hook on the remote git repository that tests the code and builds the container when code is pushed to the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
Create a Cloud Build trigger based on the development branch that tests the code, builds the container, and stores it in Container Registry. Create a deployment pipeline that watches for new images and deploys the new image on the development cluster. Ensure only the deployment tool has access to deploy new versions.
Create a Cloud Build trigger based on the development branch to build a new container image and store it in Container Registry. Rely on Vulnerability Scanning to ensure the code tests succeed. As the final step of the Cloud Build process, deploy the new container image on the development cluster. Ensure only Cloud Build has access to deploy new versions.
Your operations team has asked you to help diagnose a performance issue in a production application that runs on Compute Engine. The application is dropping requests that reach it when under heavy load. The process list for affected instances shows a single application process that is consuming all available CPU, and autoscaling has reached the upper limit of instances. There is no abnormal load on any other related systems, including the database. You want to allow production traffic to be served again as quickly as possible. Which action should you recommend?
Change the autoscaling metric to agent.googleapis.com/memory/percent_used.
Restart the affected instances on a staggered schedule.
SSH to each instance and restart the application process.
Increase the maximum number of instances in the autoscaling group.
You are implementing the infrastructure for a web service on Google Cloud. The web service needs to receive and store the data from 500,000 requests per second. The data will be queried later in real time, based on exact matches of a known set of attributes. There will be periods where the web service will not receive any requests. The business wants to keep costs low. Which web service platform and database should you use for the application?
Cloud Run and BigQuery
Cloud Run and Cloud Bigtable
A Compute Engine autoscaling managed instance group and BigQuery
A Compute Engine autoscaling managed instance group and Cloud Bigtable
You are developing an application using different microservices that should remain internal to the cluster. You want to be able to configure each microservice with a specific number of replicas. You also want to be able to address a specific microservice from any other microservice in a uniform way, regardless of the number of replicas the microservice scales to. You need to implement this solution on Google Kubernetes Engine. What should you do?
Deploy each microservice as a Deployment. Expose the Deployment in the cluster using a Service, and use the Service DNS name to address it from other microservices within the cluster.
Deploy each microservice as a Deployment. Expose the Deployment in the cluster using an Ingress, and use the Ingress IP address to address the Deployment from other microservices within the cluster.
Deploy each microservice as a Pod. Expose the Pod in the cluster using a Service, and use the Service DNS name to address the microservice from other microservices within the cluster.
Deploy each microservice as a Pod. Expose the Pod in the cluster using an Ingress, and use the Ingress IP address name to address the Pod from other microservices within the cluster.
Your company has a networking team and a development team. The development team runs applications on Compute Engine instances that contain sensitive data. The development team requires administrative permissions for Compute Engine. Your company requires all network resources to be managed by the networking team. The development team does not want the networking team to have access to the sensitive data on the instances. What should you do?
1. Create a project with a standalone VPC and assign the Network Admin role to the networking team.
2. Create a second project with a standalone VPC and assign the Compute Admin role to the development team.
3. Use Cloud VPN to join the two VPCs.
1. Create a project with a standalone Virtual Private Cloud (VPC), assign the Network Admin role to the networking team, and assign the Compute Admin role to the development team.
1. Create a project with a Shared VPC and assign the Network Admin role to the networking team.
2. Create a second project without a VPC, configure it as a Shared VPC service project, and assign the Compute Admin roleto the development team.
1. Create a project with a standalone VPC and assign the Network Admin role to the networking team.
2. Create a second project with a standalone VPC and assign the Compute Admin role to the development team.
3. Use VPC Peering to join the two VPCs.
Your company wants you to build a highly reliable web application with a few public APIs as the backend. You don’t expect a lot of user traffic, but traffic could spike occasionally. You want to leverage Cloud Load Balancing, and the solution must be cost-effective for users. What should you do?
Store static content such as HTML and images in Cloud CDN. Host the APIs on App Engine and store the user data in Cloud SQL.
Store static content such as HTML and images in a Cloud Storage bucket. Host the APIs on a zonal Google Kubernetes Engine cluster with worker nodes in multiple zones, and save the user data in Cloud Spanner.
Store static content such as HTML and images in Cloud CDN. Use Cloud Run to host the APIs and save the user data in Cloud SQL.
Store static content such as HTML and images in a Cloud Storage bucket. Use Cloud Functions to host the APIs and save the user data in Firestore
Your company sends all Google Cloud logs to Cloud Logging. Your security team wants to monitor the logs. You want to ensure that the security team can react quickly if an anomaly such as an unwanted firewall change or server breach is detected. You want to follow Google-recommended practices. What should you do?
Schedule a cron job with Cloud Scheduler. The scheduled job queries the logs every minute for the relevant events.
Export logs to BigQuery, and trigger a query in BigQuery to process the log data for the relevant events.
Export logs to a Pub/Sub topic, and trigger Cloud Function with the relevant log events.
Export logs to a Cloud Storage bucket, and trigger Cloud Run with the relevant log events.
You have deployed several instances on Compute Engine. As a security requirement, instances cannot have a public IP address. There is no VPN connection between Google Cloud and your office, and you need to connect via SSH into a specific machine without violating the security requirements. What should you do?
Configure Cloud NAT on the subnet where the instance is hosted. Create an SSH connection to the Cloud NAT IP address to reach the instance.
Add all instances to an unmanaged instance group. Configure TCP Proxy Load Balancing with the instance group as a backend. Connect to the instance using the TCP Proxy IP.
Configure Identity-Aware Proxy (IAP) for the instance and ensure that you have the role of IAP-secured Tunnel User. Use the gcloud command line tool to ssh into the instance.
Create a bastion host in the network to SSH into the bastion host from your office location. From the bastion host, SSH into the desired instance.
Your company is using Google Cloud. You have two folders under the Organization: Finance and Shopping. The members of the development team are in a Google Group. The development team group has been assigned the Project Owner role on the Organization. You want to prevent the development team from creating resources in projects in the Finance folder. What should you do?
Assign the development team group the Project Viewer role on the Finance folder, and assign the development team group the Project Owner role on the Shopping folder.
Assign the development team group only the Project Viewer role on the Finance folder.
Assign the development team group the Project Owner role on the Shopping folder, and remove the development team group Project Owner role from the Organization.
Assign the development team group only the Project Owner role on the Shopping folder.
You are developing your microservices application on Google Kubernetes Engine. During testing, you want to validate the behavior of your application in case a specific microservice should suddenly crash. What should you do?
Add a taint to one of the nodes of the Kubernetes cluster. For the specific microservice, configure a pod anti-affinity label that has the name of the tainted node as a value.
Use Istio’s fault injection on the particular microservice whose faulty behavior you want to simulate.
Destroy one of the nodes of the Kubernetes cluster to observe the behavior.
Configure Istio’s traffic management features to steer the traffic away from a crashing microservice
Your company is developing a new application that will allow globally distributed users to upload pictures and share them with other selected users. The application will support millions of concurrent users. You want to allow developers to focus on just building code without having to create and maintain the underlying infrastructure. Which service should you use to deploy the application?
App Engine
Cloud Endpoints
Compute Engine
Google Kubernetes Engine
Your company provides a recommendation engine for retail customers. You are providing retail customers with an API where they can submit a user ID and the API returns a list of recommendations for that user. You are responsible for the API lifecycle and want to ensure stability for your customers in case the API makes backward-incompatible changes. You want to follow Google-recommended practices. What should you do?
Create a distribution list of all customers to inform them of an upcoming backward-incompatible change at least one month before replacing the old API with the new API.
Create an automated process to generate API documentation, and update the public API documentation as part of the CI/CD process when deploying an update to the API.
Use a versioning strategy for the APIs that increases the version number on every backward-incompatible change.
Use a versioning strategy for the APIs that adds the suffix “DEPRECATED” to the current API version number on every backward-incompatible change. Use the current version number for the new API.
Your company has developed a monolithic, 3-tier application to allow external users to upload and share files. The solution cannot be easily enhanced and lacks reliability. The development team would like to re-architect the application to adopt microservices and a fully managed service approach, but they need to convince their leadership that the effort is worthwhile. Which advantage(s) should they highlight to leadership?
The new approach will be significantly less costly, make it easier to manage the underlying infrastructure, and automatically manage the CI/CD pipelines.
The monolithic solution can be converted to a container with Docker. The generated container can then be deployed into a Kubernetes cluster.
The new approach will make it easier to decouple infrastructure from application, develop and release new features, manage the underlying infrastructure, manage CI/CD pipelines and perform A/B testing, and scale the solution if necessary.
The process can be automated with Migrate for Compute Engine.
Your team is developing a web application that will be deployed on Google Kubernetes Engine (GKE). Your CTO expects a successful launch and you need to ensure your application can handle the expected load of tens of thousands of users. You want to test the current deployment to ensure the latency of your application stays below a certain threshold. What should you do?
Use a load testing tool to simulate the expected number of concurrent users and total requests to your application, and inspect the results.
Enable autoscaling on the GKE cluster and enable horizontal pod autoscaling on your application deployments. Send curl requests to your application, and validate if the auto scaling works.
Replicate the application over multiple GKE clusters in every Google Cloud region. Configure a global HTTP(S) load balancer to expose the different clusters over a single global IP address.
Use Cloud Debugger in the development environment to understand the latency between the different microservices
Your company has a Kubernetes application that pulls messages from Pub/Sub and stores them in Filestore. Because the application is simple, it was deployed as a single pod. The infrastructure team has analyzed Pub/Sub metrics and discovered that the application cannot process the messages in real time. Most of them wait for minutes before being processed. You need to scale the elaboration process that is I/O-intensive. What should you do?
Use kubectl autoscale deployment APP_NAME --max 6 --min 2 --cpu-percent 50 to configure Kubernetes autoscaling deployment.
Configure a Kubernetes autoscaling deployment based on the subscription/push_request_latencies metric.
Use the --enable-autoscaling flag when you create the Kubernetes cluster.
Configure a Kubernetes autoscaling deployment based on the subscription/num_undelivered_messages metric.
Your company is developing a web-based application. You need to make sure that production deployments are linked to source code commits and are fully auditable. What should you do?
Make sure a developer is tagging the code commit with the date and time of commit.
Make sure a developer is adding a comment to the commit that links to the deployment.
Make the container tag match the source code commit hash.
Make sure the developer is tagging the commits with latest.
An application development team has come to you for advice. They are planning to write and deploy an HTTP(S) API using Go 1.12. The API will have a very unpredictable workload and must remain reliable during peaks in traffic. They want to minimize operational overhead for this application. Which approach should you recommend?
Develop the application with containers, and deploy to Google Kubernetes Engine.
Develop the application for App Engine standard environment.
Use a Managed Instance Group when deploying to Compute Engine.
Develop the application for App Engine flexible environment, using a custom runtime.
Your company is designing its data lake on Google Cloud and wants to develop different ingestion pipelines to collect unstructured data from different sources. After the data is stored in Google Cloud, it will be processed in several data pipelines to build a recommendation engine for end users on the website. The structure of the data retrieved from the source systems can change at any time. The data must be stored exactly as it was retrieved for reprocessing purposes in case the data structure is incompatible with the current processing pipelines. You need to design an architecture to support the use case after you retrieve the data. What should you do?
Send the data through the processing pipeline, and then store the processed data in a BigQuery table for reprocessing.
Store the data in a BigQuery table. Design the processing pipelines to retrieve the data from the table.
Send the data through the processing pipeline, and then store the processed data in a Cloud Storage bucket for reprocessing.
Store the data in a Cloud Storage bucket. Design the processing pipelines to retrieve the data from the bucket.
You are responsible for the Google Cloud environment in your company. Multiple departments need access to their own projects, and the members within each department will have the same project responsibilities. You want to structure your Google Cloud environment for minimal maintenance and maximum overview of IAM permissions as each department's projects start and end. You want to follow Google-recommended practices. What should you do?
Grant all department members the required IAM permissions for their respective projects.
Create a Google Group per department and add all department members to their respective groups. Create a folder per department and grant the respective group the required IAM permissions at the folder level. Add the projects under the respective folders.
Create a folder per department and grant the respective members of the department the required IAM permissions at the folder level. Structure all projects for each department under the respective folders.
Create a Google Group per department and add all department members to their respective groups. Grant each group the required IAM permissions for their respective projects.
Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster. You have separate clusters for development, staging, and production. You have discovered that the team is able to deploy a Docker image to the production cluster without first testing the deployment in development and then staging. You want to allow the team to have autonomy but want to prevent this from happening. You want a Google Cloud solution that can be implemented quickly with minimal effort. What should you do?
Configure a Kubernetes lifecycle hook to prevent the container from starting if it is not approved for usage in the given environment.
Implement a corporate policy to prevent teams from deploying Docker images to an environment unless the Docker image was tested in an earlier environment.
Configure binary authorization policies for the development, staging, and production clusters. Create attestations as part of the continuous integration pipeline.
Create a Kubernetes admissions controller to prevent the container from starting if it is not approved for usage in the given environment.
Your company wants to migrate their 10-TB on-premises database export into Cloud Storage. You want to minimize the time it takes to complete this activity, the overall cost, and database load. The bandwidth between the on-premises environment and Google Cloud is 1 Gbps. You want to follow Google-recommended practices. What should you do?
Develop a Dataflow job to read data directly from the database and write it into Cloud Storage.
Use the Data Transfer Service to transfer the data from on-permises to Google cloud storage
Use a commercial partner ETL solution to extract the data from the on-premises database and upload it into Cloud Storage.
Compress the data and upload it with gsutil -m to enable multi-threaded copy.
Your company has an enterprise application running on Compute Engine that requires high availability and high performance. The application has been deployed on two instances in two zones in the same region in active-passive mode. The application writes data to a persistent disk. In the case of a single zone outage, that data should be immediately made available to the other instance in the other zone.
You want to maximize performance while minimizing downtime and data loss. What should you do?
1. Attach a persistent SSD disk to the first instance.
2. Create a snapshot every hour.
3. In case of a zone outage, recreate a persistent SSD disk in the second instance where data is coming from the created snapshot.
1. Create a Cloud Storage bucket.
2. Mount the bucket into the first instance with gcs-fuse.
3. In case of a zone outage, mount the Cloud Storage bucket to the second instance with gcs-fuse.
1. Attach a regional SSD persistent disk to the first instance.
2. In case of a zone outage, force-attach the disk to the other instance.
1. Attach a local SSD to the first instance disk. 2. Execute an rsync command every hour where the target is a persistent SSD disk attached to the second instance. 3. In case of a zone outage, use the second instance.
You are designing a Data Warehouse on Google Cloud and want to store sensitive data in BigQuery. Your company requires you to generate the encryption keys outside of Google Cloud. You need to implement a solution. What should you do?
Generate a new key in Cloud Key Management Service (Cloud KMS). Store all data in Cloud Storage using the customer- managed key option and select the created key. Set up a Dataflow pipeline to decrypt the data and to store it in a new BigQuery dataset.
Generate a new key in Cloud KMS. Create a dataset in BigQuery using the customer-managed key option and select the created key.
Import a key in Cloud KMS. Store all data in Cloud Storage using the customer-managed key option and select the created key. Set up a Dataflow pipeline to decrypt the data and to store it in a new BigQuery dataset.
Import a key in Cloud KMS. Create a dataset in BigQuery using the customer-supplied key option and select the created key.
Your organization has stored sensitive data in a Cloud Storage bucket. For regulatory reasons, your company must be able to rotate the encryption key used to encrypt the data in the bucket. The data will be processed in Dataproc. You want to follow Google-recommended practices for security. What should you do?
Create a key with Cloud Key Management Service (KMS). Encrypt the data using the encrypt method of Cloud KMS.
Create a key with Cloud Key Management Service (KMS). Set the encryption key on the bucket to the Cloud KMS key.
Generate a GPG key pair. Encrypt the data using the GPG key. Upload the encrypted data to the bucket.
Generate an AES-256 encryption key. Encrypt the data in the bucket using the customer-supplied encryption keys feature.
Your team needs to create a Google Kubernetes Engine (GKE) cluster to host a newly built application that requires access to third-party services on the internet. Your company does not allow any Compute Engine instance to have a public IP address on Google Cloud. You need to create a deployment strategy that adheres to these guidelines. What should you do?
Configure the GKE cluster as a private cluster, and configure Cloud NAT Gateway for the cluster subnet.
Configure the GKE cluster as a private cluster. Configure Private Google Access on the Virtual Private Cloud (VPC).
Configure the GKE cluster as a route-based cluster. Configure Private Google Access on the Virtual Private Cloud (VPC).
Create a Compute Engine instance, and install a NAT Proxy on the instance. Configure all workloads on GKE to pass through this proxy to access third-party services on the Internet.
