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.
Your API backend is running on multiple cloud providers. You want to generate reports for the network latency of your API. Which two steps should you take? (Choose two.)
A. Use Zipkin collector to gather data.
B. Use Fluentd agent to gather data.
C. Use Stackdriver Trace to generate reports.
D. Use Stackdriver Debugger to generate report.
E. Use Stackdriver Profiler to generate report.
You are using Cloud Build to build a Docker image. You need to modify the build to execute unit and run
integration tests. When there is a failure, you want the build history to clearly display the stage at which the
build failed.
What should you do?
A. Add RUN commands in the Dockerfile to execute unit and integration tests.
B. Create a Cloud Build build config file with a single build step to compile unit and integration tests.
C. Create a Cloud Build build config file that will spawn a separate cloud build pipeline for unit and integration tests.
D. Create a Cloud Build build config file with separate cloud builder steps to compile and execute unit and integration tests.
Your company stores their source code in a Cloud Source Repositories repository. Your company wants to build and test their code on each source code commit to the repository and requires a solution that is managed and has minimal operations overhead.
Which method should they use?
A. Use Cloud Build with a trigger configured for each source code commit.
B. Use Jenkins deployed via the Google Cloud Platform Marketplace, configured to watch for source code commits.
C. Use a Compute Engine virtual machine instance with an open source continuous integration tool, configured to watch for source code commits.
D. Use a source code commit trigger to push a message to a Cloud Pub/Sub topic that triggers an App Engine service to build the source code.
You deployed a new application to Google Kubernetes Engine and are experiencing some performance degradation. Your logs are being written to Cloud Logging, and you are using a Prometheus sidecar model for capturing metrics. You need to correlate the metrics and data from the logs to troubleshoot the performance issue and send real-time alerts while minimizing costs. What should you do?
A. Create custom metrics from the Cloud Logging logs, and use Prometheus to import the results using the Cloud Monitoring REST API.
B. Export the Cloud Logging logs and the Prometheus metrics to Cloud Bigtable. Run a query to join the results, and analyze in Google Data Studio.
C. Export the Cloud Logging logs and stream the Prometheus metrics to BigQuery. Run a recurring query to join the results, and send notifications using Cloud Tasks.
D. Export the Prometheus metrics and use Cloud Monitoring to view them as external metrics. Configure Cloud Monitoring to create log-based metrics from the logs, and correlate them with the Prometheus data.
You are developing an application hosted on Google Cloud that uses a MySQL relational database schema. The application will have a large volume of reads and writes to the database and will require backups and ongoing capacity planning. Your team does not have time to fully manage the database but can take on small administrative tasks. How should you host the database?
A. Configure Cloud SQL to host the database, and import the schema into Cloud SQL.
B. Deploy MySQL from the Google Cloud Marketplace to the database using a client, and import the schema.
C. Configure Bigtable to host the database, and import the data into Bigtable.
D. Configure Cloud Spanner to host the database, and import the schema into Cloud Spanner.
E. Configure Firestore to host the database, and import the data into Firestore.
Your team has created an application that is hosted on a Google Kubernetes Engine (GKE) cluster You need to connect the application to a legacy REST service that is deployed in two GKE clusters in two different regions. You want to connect your application to the legacy service in a way that is resilient and requires the fewest number of steps You also want to be able to run probe-based health checks on the legacy service on a separate port How should you set up the connection?
A. Use Traffic Director with a sidecar proxy to connect the application to the service.
B. Use a proxyless Traffic Director configuration to connect the application to the service.
C. Configure the legacy service's firewall to allow health checks originating from the proxy.
D. Configure the legacy service's firewall to allow health checks originating from the application.
E. Configure the legacy service's firewall to allow health checks originating from the Traffic Director control plane.
You are porting an existing Apache/MySQL/PHP application stack from a single machine to Google Kubernetes Engine. You need to determine how to containerize the application. Your approach should follow Google-recommended best practices for availability. What should you do?
A. Package each component in a separate container. Implement readiness and liveness probes.
B. Package the application in a single container. Use a process management tool to manage each component.
C. Package each component in a separate container. Use a script to orchestrate the launch of the components.
D. Package the application in a single container. Use a bash script as an entrypoint to the container, and then spawn each component as a background job.
Your company just experienced a Google Kubernetes Engine (GKE) API outage due to a zone failure. You want to deploy a highly available GKE architecture that minimizes service interruption to users in the event of a future zone failure. What should you do?
A. Deploy Zonal clusters
B. Deploy Regional clusters
C. Deploy Multi-Zone clusters
D. Deploy GKE on-premises clusters
You are developing a flower ordering application Currently you have three microservices.
?Order Service (receives the orders).
?Order Fulfillment Service (processes the orders).
?Notification Service (notifies the customer when the order is filled).
You need to determine how the services will communicate with each other. You want incoming orders to be processed quickly and you need to collect order information for fulfillment. You also want to make sure orders are not lost between
your services and are able to communicate asynchronously. How should the requests be processed?
A.
B.
C.
D.
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