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| Section | Objectives |
|---|---|
| Deploying applications | - Containerization and deployment (Cloud Run, GKE) - Release management strategies - CI/CD pipelines |
| Integrating Google Cloud services | - Using managed services (Pub/Sub, Firestore, Cloud SQL) - API integration and service-to-service communication |
| Designing cloud-native applications | - Microservices design principles - Application architecture design - Scalability and resiliency patterns |
| Ensuring application performance and reliability | - Performance optimization - Monitoring and logging (Cloud Monitoring, Cloud Logging) - Fault tolerance and incident response |
| Building and testing applications | - Unit and integration testing strategies - Debugging and troubleshooting applications - Application development on Google Cloud |
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NEW QUESTION # 313
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?
Answer: B
Explanation:
The pipeline steps in the image show that the Docker image is built, but there is no step to push the built image to Artifact Registry. Cloud Run requires the container image to be in a registry (such as Artifact Registry or Container Registry) before it can be deployed. Adding a step to push the container image to Artifact Registry after it is built will make the image available for deployment, allowing the final step to deploy the application to Cloud Run successfully.
NEW QUESTION # 314
Elizabeth would rather not answer phone calls using her iMac. Where in macOS can Elizabeth turn off iPhone Cellular Calls?
Answer: C
Explanation:
Explanation/Reference: https://discussions.apple.com/thread/6836476
NEW QUESTION # 315
Your company uses Cloud Logging to manage large volumes of log data. You need to build a real-time log analysis architecture that pushes logs to a third-party application for processing. What should you do?
Answer: B
NEW QUESTION # 316
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Company Overview
HipLocal is a community application designed to facilitate communication between people in close proximity. It is used for event planning and organizing sporting events, and for businesses to connect with their local communities. HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon. Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive Statement
We are the number one local community app; it's time to take our local community services global. Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10000 miles away from each other.
Solution Concept
HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers. They want to hire and train a new team to support these regions in their time zones. They will need to ensure that the application scales smoothly and provides clear uptime data.
Existing Technical Environment
HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform.
The HipLocal team understands their application well, but has limited experience in global scale applications.
Their existing technical environment is as follows:
* Existing APIs run on Compute Engine virtual machine instances hosted in GCP.
* State is stored in a single instance MySQL database in GCP.
* Data is exported to an on-premises Teradata/Vertica data warehouse.
* Data analytics is performed in an on-premises Hadoop environment.
* The application has no logging.
* There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.
Business Requirements
HipLocal's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are:
* Expand availability of the application to new regions.
* Increase the number of concurrent users that can be supported.
* Ensure a consistent experience for users when they travel to different regions.
* Obtain user activity metrics to better understand how to monetize their product.
* Ensure compliance with regulations in the new regions (for example, GDPR).
* Reduce infrastructure management time and cost.
* Adopt the Google-recommended practices for cloud computing.
Technical Requirements
* The application and backend must provide usage metrics and monitoring.
* APIs require strong authentication and authorization.
* Logging must be increased, and data should be stored in a cloud analytics platform.
* Move to serverless architecture to facilitate elastic scaling.
* Provide authorized access to internal apps in a secure manner.
HipLocal's data science team wants to analyze user reviews.
How should they prepare the data?
Answer: D
NEW QUESTION # 317
Your operations team has asked you to create a script that lists the Cloud Bigtable, Memorystore, and Cloud SQL databases running within a project. The script should allow users to submit a filter expression to limit the results presented. How should you retrieve the data?
Answer: B
Explanation:
https://cloud.google.com/sdk/gcloud/reference/topic/filters
Most gcloud commands return a list of resources on success. By default they are pretty-printed on the standard output. The --format=NAME[ATTRIBUTES](PROJECTION) and --filter=EXPRESSION flags along with projections can be used to format and change the default output to a more meaningful result. Use the --format flag to change the default output format of a command. For details run $ gcloud topic formats.
NEW QUESTION # 318
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