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Google Professional Cloud Developer Exam
- Topic 1: Designing Highly Scalable, Available, And Reliable Cloud-Native Applications/ Geographic Distribution Of Google Cloud Services
- Topic 2: Operating System Versions And Base Runtimes Of Services/ Oogle-Recommended Practices And Documentation
- Topic 3: Security Mechanisms That Protect Services And Resources/ Choosing Data Storage Options Based On Use Case Considerations
- Topic 4: Defining Database Schemas For Google-Managed Databases/ Re-Architecting Applications From Local Services To Google Cloud Platform
- Topic 5: Defining A Key Structure For High Write Applications Using Cloud Storage/ Using Cloud Storage To Run A Static Website
- Topic 6: Google-Recommended Practices And Documentation/ Deploying And Securing An API With Cloud Endpoints Setting Up Your Development Environment, Considerations/ Building And Testing Applications
- Topic 7: Reviewing Test Results Of Continuous Integration Pipeline/ Developing Unit Tests For All Code Written
- Topic 8: Developing An Integration Pipeline Using Services/ Emulating GCP Services For Local Application Development Eploying Applications And Services On Compute Engine/ Deploying An Application To App Engine
- Topic 9: Launching A Compute Instance Using GCP Console And Cloud SDK/ Creating An Autoscaled Managed Instance Group Using An Instance Template
- Topic 10: Implementing Appropriate Deployment Strategies Based On The Target Compute Environment/ Creating A Load Balancer For Compute Engine Instances
- Topic 11: Deploying Applications And Services On Google Kubernetes Engine/ Deploying Applications And Services On Google Kubernetes Engine
- Topic 12: Automating Resource Provisioning With Deployment Manager/ Creating An Instance With A Startup Script That Installs Software
- Topic 13: Integrating An Application With Data And Storage Services/ Writing An SQL Query To Retrieve Data From Relational Databases
- Topic 14: Reading And Updating An Entity In A Cloud Datastore Transaction From An Application/ Using Apis To Read/Write To Data Services
- Topic 15: Configuring Compute Services Network Settings/ Configuring A Cloud Pub/Sub Push Subscription To Call An Endpoint
- Topic 16: Publishing And Consuming From Data Ingestion Sources/ Authenticating Users By Using Oauth2 Web Flow And Identity Aware Proxy
Free Google Professional Cloud Developer Exam Actual Questions
The questions for Professional Cloud Developer were last updated On Apr. 11, 2024
You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests Your load tests must meet the following requirements:
* Load is initiated from multiple parallel threads
* User traffic to the API originates from multiple source IP addresses.
* Load can be scaled up using additional test instances
You want to follow Google-recommended best practices How should you configure the load testing'?
You are supporting a business-critical application in production deployed on Cloud Run. The application is reporting HTTP 500 errors that are affecting the usability of the application. You want to be alerted when the number of errors exceeds 15% of the requests within a specific time window. What should you do?
You have an application running in a production Google Kubernetes Engine (GKE) cluster. You use Cloud Deploy to automatically deploy your application to your production GKE cluster. As part of your development process: you are planning to make frequent changes to the applications source code and need to select the tools to test the changes before pushing them to your remote source code repository. Your toolset must meet the following requirements:
* Test frequent local changes automatically.
* Local deployment emulates production deployment.
Which tools should you use to test building and running a container on your laptop using minimal resources'?
You are deploying a Python application to Cloud Run using Cloud Build. The Cloud Build pipeline is shown below:
You want to optimize deployment times and avoid unnecessary steps What should you do?
You are a lead developer working on a new retail system that runs on Cloud Run and Firestore. A web UI requirement is for the user to be able to browse through alt products. A few months after go-live, you notice that Cloud Run instances are terminated with HTTP 500: Container instances are exceeding memory limits errors during busy times
This error coincides with spikes in the number of Firestore queries
You need to prevent Cloud Run from crashing and decrease the number of Firestore queries. You want to use a solution that optimizes system performance What should you do?
- Select Question Types you want
- Set your Desired Pass Percentage
- Allocate Time (Hours : Minutes)
- Create Multiple Practice tests with Limited Questions
- Customer Support
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