PCD practice questions 321–330

1. Question 321 · 357 in bank

   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?

   • APackage each component in a separate container. Implement readiness and liveness probes.
   • BPackage the application in a single container. Use a process management tool to manage each component.
   • CPackage each component in a separate container. Use a script to orchestrate the launch of the components.
   • DPackage 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.

   Show answer

   Answer: A

   Explanation

   A. Package each component in a separate container. Implement readiness and liveness probes. This is the recommended approach for containerizing an application for use on Kubernetes. By packaging each component in a separate container, you can ensure that each component is isolated and can be managed independently. You can then use readiness and liveness probes to monitor the health and availability of each component, which will help ensure the overall availability of the application.

   Source: Adapted from community discussion — omermahgoub

   References

   • Google Cloud documentation
   • Google Cloud documentation

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2. Question 322 · 357 in bank

   You are developing an application that will be launched on Compute Engine instances into multiple distinct projects, each corresponding to the environments in your software development process (development, QA, staging, and production). The instances in each project have the same application code but a different configuration. During deployment, each instance should receive the application's configuration based on the environment it serves. You want to minimize the number of steps to configure this flow. What should you do?

   • AWhen creating your instances, configure a startup script using the gcloud command to determine the project name that indicates the correct environment.
   • BIn each project, configure a metadata key ג€environmentג€ whose value is the environment it serves. Use your deployment tool to query the instance metadata and configure the application based on the ג€environmentג€ value.
   • CDeploy your chosen deployment tool on an instance in each project. Use a deployment job to retrieve the appropriate configuration file from your version control system, and apply the configuration when deploying the application on each instance.
   • DDuring each instance launch, configure an instance custom-metadata key named ג€environmentג€ whose value is the environment the instance serves. Use your deployment tool to query the instance metadata, and configure the application based on the ג€environmentג€ value.

   Show answer

   Answer: B

   Explanation

   Option A, configuring a startup script using the gcloud command to determine the project name, is not a feasible solution because it requires additional steps to be taken during instance launch. Option C, deploying a deployment tool on an instance in each project and using a deployment job to retrieve the appropriate configuration file, is not a feasible solution because it requires additional steps to be taken during instance launch and involves the use of a separate deployment tool. Option D, configuring an instance custom-metadata key named "environment" during each instance launch, is not a feasible solution because it requires additional steps to be taken during instance launch.

   Source: Adapted from community discussion — omermahgoub

   References

   • Google Cloud documentation
   • Google Cloud documentation
   • Google Cloud documentation

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3. Question 323 · 357 in bank

   You are developing an ecommerce application that stores customer, order, and inventory data as relational tables inside Cloud Spanner. During a recent load test, you discover that Spanner performance is not scaling linearly as expected. Which of the following is the cause?

   • AThe use of 64-bit numeric types for 32-bit numbers.
   • BThe use of the STRING data type for arbitrary-precision values.
   • CThe use of Version 1 UUIDs as primary keys that increase monotonically.
   • DThe use of LIKE instead of STARTS_WITH keyword for parameterized SQL queries.

   Show answer

   Answer: C

   Explanation

   In Cloud Spanner, the use of Version 1 UUIDs as primary keys that increase monotonically can cause performance issues because they are not evenly distributed. This can lead to hot regions, where a disproportionate number of requests are sent to a specific node or range of nodes, causing those nodes to become overloaded and leading to decreased performance. To improve performance, you should consider using primary keys that are more evenly distributed, such as hash-based keys or random integers.

   Source: Adapted from community discussion — omermahgoub

   References

   • Google Cloud documentation
   • Google Cloud documentation

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4. Question 324 · 357 in bank

   You are developing an application that reads credit card data from a Pub/Sub subscription. You have written code and completed unit testing. You need to test the Pub/Sub integration before deploying to Google Cloud. What should you do?

   • ACreate a service to publish messages, and deploy the Pub/Sub emulator. Generate random content in the publishing service, and publish to the emulator.
   • BCreate a service to publish messages to your application. Collect the messages from Pub/Sub in production, and replay them through the publishing service.
   • CCreate a service to publish messages, and deploy the Pub/Sub emulator. Collect the messages from Pub/Sub in production, and publish them to the emulator.
   • DCreate a service to publish messages, and deploy the Pub/Sub emulator. Publish a standard set of testing messages from the publishing service to the emulator.

   Show answer

   Answer: D

   References

   • Google Cloud documentation

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5. Question 325 · 357 in bank

   You have developed a Python application that you want to containerize and deploy to Cloud Run. You have developed a Cloud Build pipeline with the following steps:

   

   After triggering the pipeline, you notice in the Cloud Build logs that the final step of the pipeline fails and the container is unable to be deployed to Cloud Run. What is the cause of this issue, and how should you resolve it?

   • AThe final step uses a Cloud Run instance name that does not match the container name. Update the deployment step so that the Cloud Run instance name matches the container name, and rerun the pipeline.
   • BThe Docker container image has not been pushed to Artifact Registry. Add a step to the pipeline to push the application container image to Artifact Registry, and rerun the pipeline.
   • CCloud Run does not allow unauthenticated invocations. Remove the --allow-unauthenticated parameter to enforce authentication on the application, and rerun the pipeline.
   • DUnit tests in the pipeline are failing. Update the application code so that all unit tests pass, and rerun the pipeline.

   Show answer

   Answer: B

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6. Question 326 · 357 in bank

   You are designing an application that will subscribe to and receive messages from a single Pub/Sub topic and insert corresponding rows into a database. Your application runs on Linux and leverages preemptible virtual machines to reduce costs. You need to create a shutdown script that will initiate a graceful shutdown. What should you do?

   • AWrite a shutdown script that uses inter-process signals to notify the application process to disconnect from the database.
   • BWrite a shutdown script that broadcasts a message to all signed-in users that the Compute Engine instance is going down and instructs them to save current work and sign out.
   • CWrite a shutdown script that writes a file in a location that is being polled by the application once every five minutes. After the file is read, the application disconnects from the database.
   • DWrite a shutdown script that publishes a message to the Pub/Sub topic announcing that a shutdown is in progress. After the application reads the message, it disconnects from the database.

   Show answer

   Answer: A

   Explanation

   The best answer is A. Write a shutdown script that uses inter-process signals to notify the application process to disconnect from the database. Here's why: Inter-process Signals: Signals are a standard mechanism in Unix-like systems for communicating between processes. They are a reliable and efficient way to notify the application process that a shutdown is imminent. Graceful Shutdown: Using signals allows the application to gracefully disconnect from the database, ensuring data integrity and preventing potential data loss. The application can handle the signal, perform necessary cleanup tasks, and then exit gracefully.

   Source: Adapted from community discussion — thewalker

   References

   • Google Cloud documentation
   • Google Cloud documentation

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7. Question 327 · 357 in bank

   You have an application deployed in production. When a new version is deployed, some issues don't arise until the application receives traffic from users in production. You want to reduce both the impact and the number of users affected. Which deployment strategy should you use?

   • ABlue/green deployment
   • BCanary deployment
   • CRolling deployment
   • DRecreate deployment

   Show answer

   Answer: B

   Explanation

   Agree it should be B (canary deployment) Blue/green will affect all users, as well as recreate. The rolling update has other purposes, so Canary is the best for scenario described.

   Source: Adapted from community discussion — emmet

   References

   • Google Cloud documentation
   • Google Cloud documentation

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8. Question 328 · 357 in bank

   You work for a web development team at a small startup. Your team is developing a Node.js application using Google Cloud services, including Cloud Storage and Cloud Build. The team uses a Git repository for version control. Your manager calls you over the weekend and instructs you to make an emergency update to one of the company's websites, and you're the only developer available. You need to access Google Cloud to make the update, but you don't have your work laptop. You are not allowed to store source code locally on a non-corporate computer. How should you set up your developer environment?

   • AUse a text editor and the Git command line to send your source code updates as pull requests from a public computer.
   • BUse a text editor and the Git command line to send your source code updates as pull requests from a virtual machine running on a public computer.
   • CUse Cloud Shell and the built-in code editor for development. Send your source code updates as pull requests.
   • DUse a Cloud Storage bucket to store the source code that you need to edit. Mount the bucket to a public computer as a drive, and use a code editor to update the code. Turn on versioning for the bucket, and point it to the team's Git repository.

   Show answer

   Answer: C

   Explanation

   C is the answer. https://cloud.google.com/shell/docs loud Shell is an interactive shell environment for Google Cloud that lets you learn and experiment with Google Cloud and manage your projects and resources from your web browser. With Cloud Shell, the Google Cloud CLI and other utilities you need are pre-installed, fully authenticated, up-to-date, and always available when you need them. Cloud Shell comes with a built-in code editor with an integrated Cloud Code experience, allowing you to develop, build, debug, and deploy your cloud-based apps entirely in the cloud.

   Source: Adapted from community discussion — zellck

   References

   • Google Cloud documentation

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9. Question 329 · 357 in bank

   Select 2

   Your team develops services that run on Google Kubernetes Engine. You need to standardize their log data using Google-recommended practices and make the data more useful in the fewest number of steps. What should you do? (Choose two.)

   • ACreate aggregated exports on application logs to BigQuery to facilitate log analytics.
   • BCreate aggregated exports on application logs to Cloud Storage to facilitate log analytics.
   • CWrite log output to standard output (stdout) as single-line JSON to be ingested into Cloud Logging as structured logs.
   • DMandate the use of the Logging API in the application code to write structured logs to Cloud Logging.
   • EMandate the use of the Pub/Sub API to write structured data to Pub/Sub and create a Dataflow streaming pipeline to normalize logs and write them to BigQuery for analytics.

   Show answer

   Answer: AC

   Explanation

   A & C: Option A to “make the data more useful”, as BigQuery will allow us to use big data analysis capabilities on the stored logs: https://cloud.google.com/logging/docs/export/aggregated_sinks#supported-destinations Option C to “to standardize their log data” creating structured logs: https://cloud.google.com/kubernetes-engine/docs/concepts/about-logs#best_practices Option D is also a viable solution but C is preferred, considering the “fewest number of steps” requirement. Choosing C and D together makes no sense, as both aim to achieve the same goal.

   Source: Adapted from community discussion — wanrltw

   References

   • Google Cloud documentation
   • Google Cloud documentation
   • Google Cloud documentation
   • Google Cloud documentation

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10. Question 330 · 357 in bank

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

    • AUse canary deployment
    • BUse blue/green deployment
    • CUse rolling updates deployment
    • DUse A/B testing with traffic mirroring during deployment

    Show answer

    Answer: D

    Explanation

    Correct answer is A: Canary deployment is a technique to reduce the risk of introducing a software update in production by slowly rolling out the change to a small subset of users before making it available to everybody. This deployment technique is one where the SRE of an application development team relies on a router or load balancer to target individual routes. They target a small fragment of the overall user base with the newer version of the application. Once this new set of users are have used the application important metrics will be collected and analyzed to decide whether the new update is good for a full scale rolled to all the users or whether it needs to be rolled back for further troubleshooting.

    Source: Adapted from community discussion — ESP_SAP

    References

    • Google Cloud documentation

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PCD practice, question 321. 357 questions available.