Google Cloud Developer Professional-Cloud-Developer

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Section 3: Deploying Apps

This topic evaluates the ability of the students to recommend the relevant deployment strategies with the help of the appropriate tools, such as Spinnaker, Cloud Build, Anthos Configuration Manager, and Tekton, for a certain compute environment (for instance, Google Kubernetes Engine, Compute Engine, etc.). The individuals should also possess the skills in deploying apps & services on Compute Engine; deploying apps & services to Google Kubernetes Engine (GKE); deploying Cloud Function. Lastly, they must have the proficiency in utilizing service accounts.

Reference: https://cloud.google.com/certification/cloud-developer

Google Professional Cloud Developer Certified Professional salary

The average salary of a Google Professional Cloud Developer Certified Expert in

• Europe - 145,347 EURO
• England - 135,632 POUND
• United State - 181,247 USD
• India - 27,42,327 INR

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Target Audience and Prerequisites

The Google Professional Cloud Developer certification exam is intended for those App Developers who are involved in designing and building applications to run on Google Cloud Platform. These specialists should be familiar with the Google Cloud Platform products, such as Cloud Storage, Compute Engine, Security Key Enforcement, as well as BigQuery.

There are no obligatory requirements that the candidates need to meet to become eligible for the qualifying test. Nevertheless, the target individuals are recommended to have three or more years of industry experience, including one or more years of experience in designing and managing solutions using Google Cloud. Besides that, the students need to develop a comprehensive understanding of the exam topics.

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Google Professional-Cloud-Developer Exam Syllabus Topics:

Google Certified Professional - Cloud Developer Sample Questions:

Question #1
You are designing a microservices architecture for a new application that will be deployed on Cloud Run. The application requires high-throughput communication between the internal microservices. You want to use the most effective, lowest latency communication protocol for this application. What should you do?

A. Use SOAP to build the microservices API, and use XML as the data format for communication across the microservices. Define SOAP data contracts for each microservice.
B. Implement the microservices with the REST API communication protocol. Use Apigee with rate- limiting to provide the best QoS for high-priority services.
C. Configure the Cloud Run service to use HTTP/2. Implement gRPC for communication between the microservices. Use streaming gRPCs when a large amount of data has to be sent.
D. Use HTTP REST to communicate across the microservices. Implement pagination and add indexing to your database.

Question #2
You are deploying new workloads on a GKE Autopilot mode cluster. You need to ensure that the Pods are scheduled on nodes that use Arm architecture CPUs. The cluster currently has no Arm- based CPUs. You want to minimize cluster operations. How should you ensure that the workloads on the GKE cluster will use Arm-based CPU nodes?

A. Deploy a new cluster in GKE Standard mode, and set up a node pool with Arm-based CPU nodes. Use nodeSelector in your manifest to ensure that Pods are scheduled in this node pool.
B. Apply Pod tolerations to request GKE to avoid scheduling Pods on nodes that do not have Arm- based CPUs.
C. Request the Scale-out compute class and the arm64 architecture in your manifest.
D. Apply node taints on node pools to tell GKE to only schedule your workloads on Arm-based CPU nodes.

Question #3
You are using the latest stable version of Python 3 to develop an API that stores data in a Cloud SQL database. You need to perform CRUD operations on the production database securely and reliably with minimal effort. What should you do?

A. 1. Use Cloud Composer to manage the connection to the Cloud SQL database from your Python application.
2. Grant an IAM role to the service account that includes the composer.worker permission.
B. 1. Use the Cloud SQL API to connect to the Cloud SQL database from your Python application.
2. Grant an IAM role to the service account that includes the cloudsql.instances.login permission.
C. 1. Use the Cloud SQL emulator to connect to the Cloud SQL database from Cloud Shell
2. Grant an IAM role to the user that includes the cloudsql.instances.login permission.
D. 1. Use the Cloud SQL connector library for Python to connect to the Cloud SQL database through a Cloud SQL Auth Proxy.
2. Grant an IAM role to the service account that includes the cloudsql.instances.connect permission.

Question #4
You are planning to add unit tests to your application. You need to be able to assert that published Pub/Sub messages are processed by your subscriber in order. You want the unit tests to be cost-effective and reliable. What should you do?

A. Use the Pub/Sub emulator.
B. Create a topic and subscription for each tester.
C. Implement a mocking framework.
D. Add a filter by tester to the subscription.

Question #5
You are in the final stage of migrating an on-premises data center to Google Cloud. You are quickly approaching your deadline, and discover that a web API is running on a server slated for decommissioning. You need to recommend a solution to modernize this API while migrating to Google Cloud. The modernized web API must meet the following requirements:
- Autoscales during high traffic periods at the end of each month
- Written in Python 3.x
- Developers must be able to rapidly deploy new versions in response to frequent code changes You want to minimize cost, effort, and operational overhead of this migration. What should you do?

A. Modernize and deploy the code on App Engine standard environment.
B. Modernize and deploy the code on App Engine flexible environment.
C. Ask the development team to re-write the application to run as a Docker container on Google Kubernetes Engine.
D. Deploy the modernized application to an n1-standard-1 Compute Engine instance.

Solutions: