View all detail and faqs for the Professional-Cloud-Developer exam
For this question, refer to the HipLocal case study.
How should HipLocal increase their API development speed while continuing to provide the QA team with a stable testing environment that meets feature requirements?
For this question refer to the HipLocal case study.
HipLocal wants to reduce the latency of their services for users in global locations. They have created read replicas of their database in locations where their users reside and configured their service to read traffic using those replicas. How should they further reduce latency for all database interactions with the least amount of effort?
You are developing an internal application that will allow employees to organize community events within your company. You deployed your application on a single Compute Engine instance. Your company uses Google Workspace (formerly G Suite), and you need to ensure that the company employees can authenticate to the application from anywhere. What should you do?
You are building a CI/CD pipeline that consists of a version control system, Cloud Build, and Container Registry. Each time a new tag is pushed to the repository, a Cloud Build job is triggered, which runs unit tests on the new code builds a new Docker container image, and pushes it into Container Registry. The last step of your pipeline should deploy the new container to your production Google Kubernetes Engine (GKE) cluster. You need to select a tool and deployment strategy that meets the following requirements:
• Zero downtime is incurred
• Testing is fully automated
• Allows for testing before being rolled out to users
• Can quickly rollback if needed
What should you do?
You are configuring a continuous integration pipeline using Cloud Build to automate the deployment of new container images to Google Kubernetes Engine (GKE). The pipeline builds the application from its source code, runs unit and integration tests in separate steps, and pushes the container to Container Registry. The application runs on a Python web server.
The Dockerfile is as follows:
FROM python:3.7-alpine -
COPY . /app -
WORKDIR /app -
RUN pip install -r requirements.txt
CMD [ "gunicorn", "-w 4", "main:app" ]
You notice that Cloud Build runs are taking longer than expected to complete. You want to decrease the build time. What should you do? (Choose two.)
You are developing an application that needs to store files belonging to users in Cloud Storage. You want each user to have their own subdirectory in Cloud Storage. When a new user is created, the corresponding empty subdirectory should also be created. What should you do?
You have a web application that publishes messages to Pub/Sub. You plan to build new versions of the application locally and need to quickly test Pub/Sub integration tor each new build. How should you configure local testing?
Your team is building an application for a financial institution. The application's frontend runs on Compute Engine, and the data resides in Cloud SQL and one Cloud Storage bucket. The application will collect data containing PII, which will be stored in the Cloud SQL database and the Cloud Storage bucket. You need to secure the PII data. What should you do?
You want to notify on-call engineers about a service degradation in production while minimizing development
time.
What should you do?
Your team is writing a backend application to implement the business logic for an interactive voice response (IVR) system that will support a payroll application. The IVR system has the following technical characteristics:
• Each customer phone call is associated with a unique IVR session.
• The IVR system creates a separate persistent gRPC connection to the backend for each session.
• If the connection is interrupted, the IVR system establishes a new connection, causing a slight latency for that call.
You need to determine which compute environment should be used to deploy the backend application. Using current call data, you determine that:
• Call duration ranges from 1 to 30 minutes.
• Calls are typically made during business hours.
• There are significant spikes of calls around certain known dates (e.g., pay days), or when large payroll changes occur.
You want to minimize cost, effort, and operational overhead. Where should you deploy the backend application?
