Question 1

Your company's user-feedback portal comprises a standard LAMP stack replicated across two zones. It is deployed in the us-central1 region and uses autoscaled managed instance groups on all layers, except the database. Currently, only a small group of select customers have access to the portal. The portal meets a99,99% availability SLA under these conditions. However next quarter, your company will be making the portal available to all users, including unauthenticated users. You need to develop a resiliency testing strategy to ensure the system maintains the SLA once they introduce additional user load.What should you do?

Options :

A : Capture existing users input, and replay captured user load until autoscale is triggered on all layers. At the same time, terminate all resources in one of the zones

B : Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce chaosto the system by terminating random resources on both zones

C : Expose the new system to a larger group of users, and increase group size each day until autoscale logic is triggered on all layers. At the same time, terminate random resources on both zones

D : Capture existing users input, and replay captured user load until resource utilization crosses 80%. Also, derive estimated number of users based on existing user-s usage of the app, and deploy enough resources to handle 200% of expected load

Answer: B

Question 2

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?

Options :

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.

Answer: D

Question 3

As a cloud architect, you are managing a project that consists of a single Virtual Private Cloud (VPC) and a single subnetwork located in the us-west1 region. Within this subnetwork, there is a Compute Engine instance hosting an application. Now, your development team intends to deploy a new instance within the same project, but in the europe-central2 region. They require access to the application and wish to adhere to Google's best practices. As a cloud architect, what guidance should you provide in this situation?

Options :

A : They should create a subnetwork in the same VPC, in europe-central2 region. Than, use Cloud VPN to connect these two subnetworks, and finally create a new instance in the new subnetwork and use the first instance-s private address as the endpoint.

B : They should create a VPC and a subnetwork in europe-central2 region. Than, expose the application with an internal load balancer, and finally create a new instance in the new subnetwork and use the load balancer-s address as the endpoint.

C : They should create a VPC and a subnetwork in europe-central2 region. Than, peer the 2 VPCs, and finally create a new instance in the new subnetwork and use the first instance-s private address as the endpoint.

D : They should create a subnetwork in the same VPC, in europe-central2 region. Than, create a new instance in the new subnetwork and use the first instance-s private address as the endpoint.

Answer: D

Question 4

In GCP, your ingestion services cannot keep up with the rate that new data is received. What can you do to ensure that data is not lost if ingestion services cannot keep up with the rate at which new data is received?

Options :

A : You can use Cloud Pub/Sub queue. Add data to a queue. Than, you can use Cloud Function to remove the data from the queue, transform and write it to another storage system.

B : You can use BigQuery dataset. Add data to a temporary table. Than, use Dataflow to process the data and writes it to another storage system.

C : You cannot prevent data loss.

D : You should change the capacity of your storage system.

Answer: A

Question 5

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?

Options :

A : Change the autoscaling metric to agent.googleapis.com/memory/percent_used.

B : Restart the affected instances on a staggered schedule.

C : SSH to each instance and restart the application process.

D : Increase the maximum number of instances in the autoscaling group.

Answer: A

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