topic2 #101- (failed or confused) Flashcards by CHUNG HWAN AHN

106. 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?

A. Deploy a new revision to Cloud Run with the new version. Configure traffic percentage between revisions.

B. Deploy a new service to Cloud Run with the new version. Add a Cloud Load Balancing instance in front of both services.

C. 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.

D. 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.

https://cloud.google.com/run/docs/rollouts-rollbacks-traffic-migration

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108. 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.)

A. Sharding

B. Read replicas

C. Binary logging

D. Automated backups

E. Semisynchronous replication

C, D

MySQL Binary Log (BinLog) is a record of all changes made to a MySQL database.

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110. 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?

A. App Engine
B. GKE On-Prem
C. Compute Engine
D. Google Kubernetes Engine

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111. 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?

A. 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.

B. 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.

C. Deploy the development and acceptance applications on a managed instance group and enable autoscaling.

D. Use regular Compute Engine instances for the production environment, and use preemptible VMs for the acceptance and development environments.

Today, you don’t need complicated CRON + CF. Auto shutdown by cron expression it’s a feature built in: https://cloud.google.com/compute/docs/instances/schedule-instance-start-stop

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113. 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?

A. Remove the default route on all VPCs. Move all approved instances into a new subnet that has a default route to an internet gateway.

B. 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.

C. Implement a Cloud NAT solution to remove the need for external IP addresses entirely.

D. Set an Organization Policy with a constraint on constraints/compute.vmExternalIpAccess. List the approved instances in the allowedValues list.

https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address#disableexternalip

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115. 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?

A. 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.

B. 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.

C. 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 permissions at the end of business.

D. 1. Create a Cloud VPN to the office network. 2. Configure Private Google Access for on-premises hosts.

https://cloud.google.com/vpc-service-controls/docs/overview

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114. 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?

A. Enable Virtual Private Cloud (VPC) flow logging.

B. Enable Firewall Rules Logging for the firewall rules you want to monitor.

C. Verify that your user account is assigned the compute.networkAdmin Identity and Access Management (IAM) role.

D. Install the Google Cloud SDK, and verify that there are no Firewall logs in the command line output.

Currently firewall logging is not enabled for any of your firewall rules. Enable firewall logging to obtain visibility into active firewall rule usage.

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118. 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?

A. 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.

B. 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.

C. 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.

D. Create a Cloud VPN connection from the new VPC to the data center, and apply a firewall rule that blocks the overlapping IP space.

https://cloud.google.com/nat/docs/troubleshooting#overlapping-ip-addresses

“Can I use Cloud NAT to connect a VPC network to another network to work around overlapping IP addresses? No, Cloud NAT cannot apply to any custom route whose next hop is not the default internet gateway. For example, Cloud NAT cannot apply to traffic sent to a next hop Cloud VPN tunnel, even if the destination is a publicly routable IP address.”

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116. 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?

A. Start a new rolling restart operation.

B. Start a new rolling replace operation.

C. Start a new rolling update. Select the Proactive update mode.

D. Start a new rolling update. Select the Opportunistic update mode.

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119. 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?

A. Create a Dataproc cluster using standard worker instances.

B. Create a Dataproc cluster using spot VM worker instances.

C. Manually deploy a Hadoop cluster on Compute Engine using standard instances.

D. Manually deploy a Hadoop cluster on Compute Engine using spot VM instances.

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120. Your company has a project in Google Cloud with three Virtual Private Clouds (VPCs). There is a Compute Engine instance on each VPC. Network subnets do not overlap and must remain separated. The network configuration is shown below. (VPC #1, VPC #2, VPC #3)

Instance #1 is an exception and must communicate directly with both Instance #2 and Instance #3 via internal IPs. How should you accomplish this?

A. Create a cloud router to advertise subnet #2 and subnet #3 to subnet #1.

B. Add two additional NICs to Instance #1 with the following configuration: ג€¢ NIC1 ג—‹ VPC: VPC #2 ג—‹ SUBNETWORK: subnet #2 ג€¢ NIC2 ג—‹ VPC: VPC #3 ג—‹ SUBNETWORK: subnet #3 Update firewall rules to enable traffic between instances.

C. Create two VPN tunnels via CloudVPN: ג€¢ 1 between VPC #1 and VPC #2. ג€¢ 1 between VPC #2 and VPC #3. Update firewall rules to enable traffic between the instances.

D. Peer all three VPCs: ג€¢ Peer VPC #1 with VPC #2. ג€¢ Peer VPC #2 with VPC #3. Update firewall rules to enable traffic between the instances.

https://cloud.google.com/vpc/docs/multiple-interfaces-concepts

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123. 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?

A. Use a persistent disk for each instance.

B. Use a regional persistent disk for each instance.

C. Create a Cloud Filestore instance and mount it in each instance.

D. Create a Cloud Storage bucket and mount it in each instance using gcsfuse.

Cloud Storage FUSE is not POSIX compliant. For a POSIX file system product in Google Cloud, see Filestore. Firestore is fully managed network-attached storage system you can use with your Google Compute Engine and Kubernetes Engine instances

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124. 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?

A. Use the Service Mesh visualization in the Cloud Console to inspect the telemetry between the microservices.

B. 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.

C. 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.

D. Reinstall istio using the default istio profile in order to collect request latency. Evaluate the telemetry between the microservices in the Cloud Console.

https://cloud.google.com/service-mesh/docs/observability-overview

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129. 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?

A. 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.

B. 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.

C. 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.

D. 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.

Based on the description “You want to be able to configure each microservice with a specific number of replicas.”, It’s a hint to use either Deployment or StatefulSet based on the service type is stateless or stateful, since the option only has Deployment, thus Option C and D is out. 2. Based on the description “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.” the later part is the key point, which means the traffic direct to each service is based on some certain rules, in K8S this means URL, which is Ingress with external HTTP LB.

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130.[!!!] 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?

A. 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.

B. 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.

C. 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 role to the development team.

D. 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.

Compute admin has network admin roles included

A Shared VPC allows for separation of duties between teams while sharing network resources. The networking team can manage the Shared VPC, and the development team can create Compute Engine instances in the Shared VPC without the networking team having access to the sensitive data on the instances. The development team can be assigned the Compute Admin role for the Shared VPC service project, and the networking team can be assigned the Network Admin role for the Shared VPC host project.

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131. 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?

A. 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.

B. 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.

C. 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.

D. 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.

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134. 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?

A. 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.

B. Assign the development team group only the Project Viewer role on the Finance folder.

C. 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.

D. Assign the development team group only the Project Owner role on the Shopping folder.

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135. 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?

A. 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.

B. Use Istio’s fault injection on the particular microservice whose faulty behavior you want to simulate.

C. Destroy one of the nodes of the Kubernetes cluster to observe the behavior.

D. Configure Istio’s traffic management features to steer the traffic away from a crashing microservice.

https://istiobyexample.dev/fault-injection/

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140. 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?

A. Use kubectl autoscale deployment APP_NAME –max 6 –min 2 –cpu-percent 50 to configure Kubernetes autoscaling deployment.

B. Configure a Kubernetes autoscaling deployment based on the subscription/push_request_latencies metric.

C. Use the –enable-autoscaling flag when you create the Kubernetes cluster.

D. Configure a Kubernetes autoscaling deployment based on the subscription/num_undelivered_messages metric.

Study These Flashcards

https://cloud.google.com/kubernetes-engine/docs/samples/container-pubsub-horizontal-pod-autoscaler

141. 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?

A. Make sure a developer is tagging the code commit with the date and time of commit.

B. Make sure a developer is adding a comment to the commit that links to the deployment.

C. Make the container tag match the source code commit hash.

D. Make sure the developer is tagging the commits with latest.

Study These Flashcards

https://cloud.google.com/architecture/best-practices-for-building-containers#tagging_using_the_git_commit_hash

컨테이너에서 실행 중인 소프트웨어의 특정 버전을 즉시 알 수 있습니다. 지속적 배포 파이프라인에서 배포에 사용된 버전 번호의 업데이트를 자동화하세요.

145. 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?

A. Configure a Kubernetes lifecycle hook to prevent the container from starting if it is not approved for usage in the given environment.

B. Implement a corporate policy to prevent teams from deploying Docker images to an environment unless the Docker image was tested in an earlier environment.

C. Configure binary authorization policies for the development, staging, and production clusters. Create attestations as part of the continuous integration pipeline.

D. Create a Kubernetes admissions controller to prevent the container from starting if it is not approved for usage in the given environment.

Study These Flashcards

https://cloud.google.com/binary-authorization/docs/overview#policy_model

Binary Authorization을 사용하여 다음을 수행할 수 있습니다.

모니터: 실행 중인 포드에 연결된 컨테이너 이미지가 정의된 정책을 준수하는지 여부를 정기적으로 모니터링하도록 지속적 점증(CV)(미리보기)을 구성할 수 있습니다. 이미지가 정책을 준수하지 않으면 CV가 Cloud Logging에 로그 항목을 생성합니다.
시행: 지원되는 컨테이너 기반 플랫폼 중 하나에 배포되는 이미지가 정의된 정책을 준수하도록 Binary Authorization 시행을 구성할 수 있습니다. 정책을 준수하는 이미지는 배포가 허용되고, 그렇지 않으면 배포가 허용되지 않습니다.

148. 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?

A. 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.

B. Generate a new key in Cloud KMS. Create a dataset in BigQuery using the customer-managed key option and select the created key.

C. 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.

D. Import a key in Cloud KMS. Create a dataset in BigQuery using the customer-supplied key option and select the created key.

Study These Flashcards

https://cloud.google.com/bigquery/docs/customer-managed-encryption

Right, term collision with “customer supplied” key. However, “import key to KMS” does not mean CSEK.

Cloud KMS = Cloud Key Management Service
CSEK = customer-supplied Encryption Keys

150. 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?

A. Configure the GKE cluster as a private cluster, and configure Cloud NAT Gateway for the cluster subnet.

B. Configure the GKE cluster as a private cluster. Configure Private Google Access on the Virtual Private Cloud (VPC).

C. Configure the GKE cluster as a route-based cluster. Configure Private Google Access on the Virtual Private Cloud (VPC).

D. 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.

Study These Flashcards

151. Your company has a support ticketing solution that uses App Engine Standard. The project that contains the App Engine application already has a Virtual Private

Cloud (VPC) network fully connected to the company’s on-premises environment through a Cloud VPN tunnel. You want to enable the App Engine application to communicate with a database that is running in the company’s on-premises environment. What should you do?

A. Configure private Google access for on-premises hosts only.

B. Configure private Google access.

C. Configure private services access.

D. Configure serverless VPC access.

Study These Flashcards

https://cloud.google.com/vpc/docs/serverless-vpc-access#use_cases

서버리스 VPC 액세스를 사용하면 Cloud Run, App Engine, Cloud Functions와 같은 서버리스 환경에서 Virtual Private Cloud(VPC) 네트워크에 직접 연결할 수 있습니다.

#153. You have deployed an application on Anthos clusters (formerly Anthos GKE). According to the SRE practices at your company, you need to be alerted if request latency is above a certain threshold for a specified amount of time. What should you do? A. Install Anthos Service Mesh on your cluster. Use the Google Cloud Console to define a Service Level Objective (SLO), and create an alerting policy based on this SLO. B. Enable the Cloud Trace API on your project, and use Cloud Monitoring Alerts to send an alert based on the Cloud Trace metrics. C. Use Cloud Profiler to follow up the request latency. Create a custom metric in Cloud Monitoring based on the results of Cloud Profiler, and create an Alerting policy in case this metric exceeds the threshold. D. Configure Anthos Config Management on your cluster, and create a yaml file that defines the SLO and alerting policy you want to deploy in your cluster.

A https://cloud.google.com/service-mesh/docs/observability/slo-overview Anthos Service Mesh를 사용하면 서비스에 SLO를 설정하고 해당 SLO를 기준으로 서비스를 모니터링하고 알림을 제공할 수 있습니다.

#154. Your company has a stateless web API that performs scientific calculations. The web API runs on a single Google Kubernetes Engine (GKE) cluster. The cluster is currently deployed in us-central1. Your company has expanded to offer your API to customers in Asia. You want to reduce the latency for users in Asia. What should you do? A. Create a second GKE cluster in asia-southeast1, and expose both APIs using a Service of type LoadBalancer. Add the public IPs to the Cloud DNS zone. B. Use a global HTTP(s) load balancer with Cloud CDN enabled. C. Create a second GKE cluster in asia-southeast1, and use kubemci to create a global HTTP(s) load balancer. D. Increase the memory and CPU allocated to the application in the cluster.

C https://cloud.google.com/blog/products/gcp/how-to-deploy-geographically-distributed-services-on-kubernetes-engine-with-kubemci ** "kubemci" has now been deprecated in favor of Ingress for Anthos. Ingress for Anthos is the recommended way to deploy multi-cluster ingress.

#156. Your company has a Google Cloud project that uses BigQuery for data warehousing. They have a VPN tunnel between the on-premises environment and Google Cloud that is configured with Cloud VPN. The security team wants to avoid data exfiltration by malicious insiders, compromised code, and accidental oversharing. What should they do? A. Configure Private Google Access for on-premises only. B. Perform the following tasks: 1. Create a service account. 2. Give the BigQuery JobUser role and Storage Reader role to the service account. 3. Remove all other IAM access from the project. C. Configure VPC Service Controls and configure Private Google Access. D. Configure Private Google Access.

C https://cloud.google.com/vpc-service-controls/docs/overview VPC 서비스 제어는 외부 주체 또는 내부 주체의 우발적이거나 표적화된 작업으로부터 보호하고, Cloud Storage 및 BigQuery와 같은 Google Cloud 서비스에서 불필요한 데이터 무단 반출 위험을 최소화하는 데 도움이 됩니다. VPC 서비스 제어를 사용하여 명시적으로 지정한 서비스의 리소스와 데이터를 보호하는 경계를 만들 수 있습니다.

#157. You are working at an institution that processes medical data. You are migrating several workloads onto Google Cloud. Company policies require all workloads to run on physically separated hardware, and workloads from different clients must also be separated. You created a sole-tenant node group and added a node for each client. You need to deploy the workloads on these dedicated hosts. What should you do? A. Add the node group name as a network tag when creating Compute Engine instances in order to host each workload on the correct node group. B. Add the node name as a network tag when creating Compute Engine instances in order to host each workload on the correct node. C. Use node affinity labels based on the node group name when creating Compute Engine instances in order to host each workload on the correct node group. D. Use node affinity labels based on the node name when creating Compute Engine instances in order to host each workload on the correct node.

D https://cloud.google.com/compute/docs/nodes/sole-tenant-nodes#default_affinity_labels 단독 테넌트 노드는 공유 단독 테넌트 노드 그룹을 사용하지 않는 한 VM이 다른 프로젝트의 VM과 호스트를 공유하지 않도록 보장합니다.

#159. A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run properly on Google Cloud Platform. What should you do? A. Help the engineer to convert his websocket code to use HTTP streaming B. Review the encryption requirements for websocket connections with the security team C. Meet with the cloud operations team and the engineer to discuss load balancer options D. Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.

C https://cloud.google.com/load-balancing/docs/https#websocket_support HTTP 또는 HTTPS를 백엔드에 대한 프로토콜로 사용하면 Google Cloud HTTP(S) 기반 부하 분산기는 기본적으로 WebSocket 프로토콜을 지원합니다.

#160 The application reliability team at your company this added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss. Which process should you implement? A. ג€¢ Append metadata to file body ג€¢ Compress individual files ג€¢ Name files with serverName ג€" Timestamp ג€¢ Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket. Otherwise, save files to existing bucket. B. ג€¢ Batch every 10,000 events with a single manifest file for metadata ג€¢ Compress event files and manifest file into a single archive file ג€¢ Name files using serverName ג€" EventSequence ג€¢ Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket. C. ג€¢ Compress individual files ג€¢ Name files with serverName ג€" EventSequence ג€¢ Save files to one bucket ג€¢ Set custom metadata headers for each object after saving D. ג€¢ Append metadata to file body ג€¢ Compress individual files ג€¢ Name files with a random prefix pattern ג€¢ Save files to one bucket

D https://cloud.google.com/storage/docs/request-rate?hl=ko#naming-convention

#161.(!!!) A recent audit revealed that a new network was created in your GCP project. In this network, a GCE instance has an SSH port open to the world. You want to discover this network's origin. What should you do? A. Search for Create VM entry in the Stackdriver alerting console B. Navigate to the Activity page in the Home section. Set category to Data Access and search for Create VM entry C. In the Logging section of the console, specify GCE Network as the logging section. Search for the Create Insert entry D. Connect to the GCE instance using project SSH keys. Identify previous logins in system logs, and match these with the project owners list

C B is wrong - Audit logs help you determine who did what, where, and when. Cloud Audit Logging returns two types of logs: ✑ Admin activity logs ✑ Data access logs: Contains log entries for operations that perform read-only operations do not modify any data, such as get, list, and aggregated list methods.

#167. You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes. What should you do? A. Add additional nodes to your Kubernetes Engine cluster using the following command: gcloud container clusters resize CLUSTER_Name ג€" -size 10 B. Add a tag to the instances in the cluster with the following command: gcloud compute instances add-tags INSTANCE - -tags enable- autoscaling max-nodes-10 C. Update the existing Kubernetes Engine cluster with the following command: gcloud alpha container clusters update mycluster - -enable- autoscaling - -min-nodes=1 - -max-nodes=10 D. Create a new Kubernetes Engine cluster with the following command: gcloud alpha container clusters create mycluster - -enable- autoscaling - -min-nodes=1 - -max-nodes=10 and redeploy your application

#162. You want to make a copy of a production Linux virtual machine in the US-Central region. You want to manage and replace the copy easily if there are changes on the production virtual machine. You will deploy the copy as a new instance in a different project in the US-East region. What steps must you take? A. Use the Linux dd and netcat commands to copy and stream the root disk contents to a new virtual machine instance in the US-East region. B. Create a snapshot of the root disk and select the snapshot as the root disk when you create a new virtual machine instance in the US-East region. C. Create an image file from the root disk with Linux dd command, create a new virtual machine instance in the US-East region D. Create a snapshot of the root disk, create an image file in Google Cloud Storage from the snapshot, and create a new virtual machine instance in the US-East region using the image file the root disk.

D https://cloud.google.com/compute/docs/instances/copy-vm-between-projects

#164. #164. You are helping the QA team to roll out a new load-testing tool to test the scalability of your primary cloud services that run on Google Compute Engine with Cloud Bigtable. Which three requirements should they include? (Choose three.) A. Ensure that the load tests validate the performance of Cloud Bigtable B. Create a separate Google Cloud project to use for the load-testing environment C. Schedule the load-testing tool to regularly run against the production environment D. Ensure all third-party systems your services use is capable of handling high load E. Instrument the production services to record every transaction for replay by the load-testing tool F. Instrument the load-testing tool and the target services with detailed logging and metrics collection

B F and (A or E) - B E F seem better?

#170. One of your primary business objectives is being able to trust the data stored in your application. You want to log all changes to the application data. How can you design your logging system to verify authenticity of your logs? A. Write the log concurrently in the cloud and on premises B. Use a SQL database and limit who can modify the log table C. Digitally sign each timestamp and log entry and store the signature D. Create a JSON dump of each log entry and store it in Google Cloud Storage

#174. You are working with a data warehousing team that performs data analysis. The team needs to process data from external partners, but the data contains personally identifiable information (PII). You need to process and store the data without storing any of the PIIE data. What should you do? A. Create a Dataflow pipeline to retrieve the data from the external sources. As part of the pipeline, use the Cloud Data Loss Prevention (Cloud DLP) API to remove any PII data. Store the result in BigQuery. B. Create a Dataflow pipeline to retrieve the data from the external sources. As part of the pipeline, store all non-PII data in BigQuery and store all PII data in a Cloud Storage bucket that has a retention policy set. C. Ask the external partners to upload all data on Cloud Storage. Configure Bucket Lock for the bucket. Create a Dataflow pipeline to read the data from the bucket. As part of the pipeline, use the Cloud Data Loss Prevention (Cloud DLP) API to remove any PII data. Store the result in BigQuery. D. Ask the external partners to import all data in your BigQuery dataset. Create a dataflow pipeline to copy the data into a new table. As part of the Dataflow bucket, skip all data in columns that have PII data

#175. You want to allow your operations team to store logs from all the production projects in your Organization, without including logs from other projects. All of the production projects are contained in a folder. You want to ensure that all logs for existing and new production projects are captured automatically. What should you do? A. Create an aggregated export on the Production folder. Set the log sink to be a Cloud Storage bucket in an operations project. B. Create an aggregated export on the Organization resource. Set the log sink to be a Cloud Storage bucket in an operations project. C. Create log exports in the production projects. Set the log sinks to be a Cloud Storage bucket in an operations project. D. Create log exports in the production projects. Set the log sinks to be BigQuery datasets in the production projects, and grant IAM access to the operations team to run queries on the datasets.

#178. Your company has an application running on Google Cloud that is collecting data from thousands of physical devices that are globally distributed. Data is published to Pub/Sub and streamed in real time into an SSD Cloud Bigtable cluster via a Dataflow pipeline. The operations team informs you that your Cloud Bigtable cluster has a hotspot, and queries are taking longer than expected. You need to resolve the problem and prevent it from happening in the future. What should you do? A. Advise your clients to use HBase APIs instead of NodeJS APIs. B. Delete records older than 30 days. C. Review your RowKey strategy and ensure that keys are evenly spread across the alphabet. D. Double the number of nodes you currently have.

C https://cloud.google.com/bigtable/docs/schema-design#row-keys

#179. Your company has a Google Cloud project that uses BigQuery for data warehousing. There are some tables that contain personally identifiable information (PII). Only the compliance team may access the PII. The other information in the tables must be available to the data science team. You want to minimize cost and the time it takes to assign appropriate access to the tables. What should you do? A. 1. From the dataset where you have the source data, create views of tables that you want to share, excluding PII. 2. Assign an appropriate project-level IAM role to the members of the data science team. 3. Assign access controls to the dataset that contains the view. B. 1. From the dataset where you have the source data, create materialized views of tables that you want to share, excluding PII. 2. Assign an appropriate project-level IAM role to the members of the data science team. 3. Assign access controls to the dataset that contains the view. C. 1. Create a dataset for the data science team. 2. Create views of tables that you want to share, excluding PII. 3. Assign an appropriate project-level IAM role to the members of the data science team. 4. Assign access controls to the dataset that contains the view. 5. Authorize the view to access the source dataset. D. 1. Create a dataset for the data science team. 2. Create materialized views of tables that you want to share, excluding PII. 3. Assign an appropriate project-level IAM role to the members of the data science team. 4. Assign access controls to the dataset that contains the view. 5. Authorize the view to access the source dataset.

C https://cloud.google.com/bigquery/docs/share-access-views?hl=en Authorized views should be created in a different dataset from the source data. That way, data owners can give users access to the authorized view without simultaneously granting access to the underlying data. The source data dataset and authorized view dataset must be in the same regional location.

#183. Your company recently acquired a company that has infrastructure in Google Cloud. Each company has its own Google Cloud organization. Each company is using a Shared Virtual Private Cloud (VPC) to provide network connectivity for its applications. Some of the subnets used by both companies overlap. In order for both businesses to integrate, the applications need to have private network connectivity. These applications are not on overlapping subnets. You want to provide connectivity with minimal re-engineering. What should you do? A. Set up VPC peering and peer each Shared VPC together. B. Migrate the projects from the acquired company into your company's Google Cloud organization. Re-launch the instances in your companies Shared VPC. C. Set up a Cloud VPN gateway in each Shared VPC and peer Cloud VPNs. D. Configure SSH port forwarding on each application to provide connectivity between applications in the different Shared VPCs.

C VPC peering is generally possible even if there are overlapping subnets between the two VPCs. However, there are some considerations to keep in mind if there's overlapping subnets: 1. You will not be able to route traffic between the overlapping subnets. If needed, you will have to use a different method (such as a Cloud VPN connection or a Cloud Router) to connect the VPCs. 2. You will need to ensure that the overlapping subnets are not used by any resources in either VPC. This means that you will need to either modify the existing network configuration to avoid using the overlapping subnets, or you will need to create new subnets that do not overlap. 3. You may need to update any existing firewall rules or routes that refer to the overlapping subnets to ensure that they are still valid after the VPCs are peered.

#185. Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster. When releasing new versions of the application via a rolling deployment, the team has been causing outages. The root cause of the outages is misconfigurations with parameters that are only used in production. You want to put preventive measures for this in the platform to prevent outages. What should you do? A. Configure liveness and readiness probes in the Pod specification. B. Configure health checks on the managed instance group. C. Create a Scheduled Task to check whether the application is available. D. Configure an uptime alert in Cloud Monitoring.

A A: Configuring the right liveness and readiness probes prevents outages when rolling out a new ReplicaSet of a Deployment, because Pods are only getting traffic when they are considered ready. B: With GKE, you do not deal with MIGs. C: Does not use GKE tools and is therefore not the best option. D: Does alert you but does not prevent the outage.

#187. Your company has a Google Cloud project that uses BigQuery for data warehousing on a pay-per-use basis. You want to monitor queries in real time to discover the most costly queries and which users spend the most. What should you do? A. 1. In the BigQuery dataset that contains all the tables to be queried, add a label for each user that can launch a query. 2. Open the Billing page of the project. 3. Select Reports. 4. Select BigQuery as the product and filter by the user you want to check. B. 1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery. 2. Perform a BigQuery query on the generated table to extract the information you need. C. 1. Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. 2. Develop a Dataflow pipeline to compute the cost of queries split by users. D. 1. Activate billing export into BigQuery. 2. Perform a BigQuery query on the billing table to extract the information you need.

B https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring

#188. Your company and one of its partners each have a Google Cloud project in separate organizations. Your company's project (prj-a) runs in Virtual Private Cloud (vpc-a). The partner's project (prj-b) runs in vpc-b. There are two instances running on vpc-a and one instance running on vpc-b. Subnets defined in both VPCs are not overlapping. You need to ensure that all instances communicate with each other via internal IPs, minimizing latency and maximizing throughput. What should you do? A. Set up a network peering between vpc-a and vpc-b. B. Set up a VPN between vpc-a and vpc-b using Cloud VPN. C. Configure IAP TCP forwarding on the instance in vpc-b, and then launch the following gcloud command from one of the instances in vpc-a gcloud: gcloud compute start-iap-tunnel INSTANCE_NAME_IN_VPC_8 22 \ --local-host-port=localhost:22 D. 1. Create an additional instance in vpc-a. 2. Create an additional instance in vpc-b. 3. Install OpenVPN in newly created instances. 4. Configure a VPN tunnel between vpc-a and vpc-b with the help of OpenVPN.

A https://cloud.google.com/vpc/docs/vpc-peering Cloud VPC Network Peering allows internal IP address connectivity across two Virtual Private Cloud (VPC) networks regardless of whether they belong to the same project or the same organization.

#190. You have a Compute Engine application that you want to autoscale when total memory usage exceeds 80%. You have installed the Cloud Monitoring agent and configured the autoscaling policy as follows: ✑ Metric identifier: agent.googleapis.com/memory/percent_used ✑ Filter: metric.label.state = 'used' ✑ Target utilization level: 80 ✑ Target type: GAUGE You observe that the application does not scale under high load. You want to resolve this. What should you do? A. Change the Target type to DELTA_PER_MINUTE. B. Change the Metric identifier to agent.googleapis.com/memory/bytes_used. C. Change the filter to metric.label.state = 'used' AND metric.label.state = 'buffered' AND metric.label.state = 'cached' AND metric.label.state = 'slab'. D. Change the filter to metric.label.state = 'free' and the Target utilization to 20.

C https://cloud.google.com/monitoring/api/metrics_agent#agent-memory

#192. Your company has an application running on App Engine that allows users to upload music files and share them with other people. You want to allow users to upload files directly into Cloud Storage from their browser session. The payload should not be passed through the backend. What should you do? A. 1. Set a CORS configuration in the target Cloud Storage bucket where the base URL of the App Engine application is an allowed origin. 2. Use the Cloud Storage Signed URL feature to generate a POST URL. B. 1. Set a CORS configuration in the target Cloud Storage bucket where the base URL of the App Engine application is an allowed origin. 2. Assign the Cloud Storage WRITER role to users who upload files. C. 1. Use the Cloud Storage Signed URL feature to generate a POST URL. 2. Use App Engine default credentials to sign requests against Cloud Storage. D. 1. Assign the Cloud Storage WRITER role to users who upload files. 2. Use App Engine default credentials to sign requests against Cloud Storage.

A https://cloud.google.com/storage/docs/cross-origin#server-side-support

#194. Your company is planning to migrate their Windows Server 2022 from their on-premises data center to Google Cloud. You need to bring the licenses that are currently in use in on-premises virtual machines into the target cloud environment. What should you do? A. 1. Create an image of the on-premises virtual machines and upload into Cloud Storage. 2. Import the image as a virtual disk on Compute Engine. B. 1. Create standard instances on Compute Engine. 2. Select as the OS the same Microsoft Windows version that is currently in use in the on-premises environment. C. 1. Create an image of the on-premises virtual machine. 2. Import the image as a virtual disk on Compute Engine. 3. Create a standard instance on Compute Engine, selecting as the OS the same Microsoft Windows version that is currently in use in the on-premises environment. 4. Attach a data disk that includes data that matches the created image. D. 1. Create an image of the on-premises virtual machines. 2. Import the image as a virtual disk on Compute Engine using --os=windows-2022-dc-v. 3. Create a sole-tenancy instance on Compute Engine that uses the imported disk as a boot disk.

#196. 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 and the overall cost. The bandwidth between the on-premises environment and Google Cloud is 1 Gbps. You want to follow Google-recommended practices. What should you do? A. Develop a Dataflow job to read data directly from the database and write it into Cloud Storage. B. Use the Data Transfer appliance to perform an offline migration. C. Use a commercial partner ETL solution to extract the data from the on-premises database and upload it into Cloud Storage. D. Upload the data with gcloud storage cp.

D https://cloud.google.com/transfer-appliance/docs/4.0/overview#suitability Transfer Appliance는 다음과 같은 경우 데이터 전송 요구사항에 적합합니다. -기존 Google Cloud 고객인 경우 -데이터가 Transfer Appliance를 사용할 수 있는 위치에 있는 경우 -네트워크를 통해 데이터를 업로드하는 데 1주일 넘게 소요되는 경우

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