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You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A. Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.

B. Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Stackdriver Logging.

C. Install Kubernetes on Google Compute Engine (GCE) and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.

D. Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.

You support a stateless web-based API that is deployed on a single Compute Engine instance in the europe-west2-a zone. The Service Level Indicator (SLI) for service availability is below the specified Service Level Objective (SLO). A postmortem has revealed that requests to the API regularly time out. The time outs are due to the API having a high number of requests and running out memory. You want to improve service availability. What should you do?

A. Change the specified SLO to match the measured SLI

B. Move the service to higher-specification compute instances with more memory

C. Set up additional service instances in other zones and load balance the traffic between all instances

D. Set up additional service instances in other zones and use them as a failover in case the primary instance is unavailable

You are developing the deployment and testing strategies for your CI/CD pipeline in Google Cloud. You must be able to:

? Reduce the complexity of release deployments and minimize the duration of deployment rollbacks.

? Test real production traffic with a gradual increase in the number of affected users.

You want to select a deployment and testing strategy that meets your requirements. What should you do?

A. Recreate deployment and canary testing

B. Blue/green deployment and canary testing

C. Rolling update deployment and A/B testing

D. Rolling update deployment and shadow testing

You are implementing a CI/CD pipeline for your application in your company's multi-cloud environment. Your application is deployed by using custom Compute Engine images and the equivalent in other cloud providers. You need to implement a solution that will enable you to build and deploy the images to your current environment and is adaptable to future changes. Which solution stack should you use?

A. Cloud Build with Packer

B. Cloud Build with Google Cloud Deploy

C. Google Kubernetes Engine with Google Cloud Deploy

D. Cloud Build with kpt

You are designing a deployment technique for your applications on Google Cloud. As part of your deployment planning, you want to use live traffic to gather performance metrics for new versions of your applications. You need to test against the full production load before your applications are launched. What should you do?

A. Use A/B testing with blue/green deployment.

B. Use canary testing with continuous deployment.

C. Use canary testing with rolling updates deployment.

D. Use shadow testing with continuous deployment.