Get ready for Google Cloud Developer certification with 254 unique test questions & insights into best practices!
What you will learn
Designing cloud-native applications for high scalability, availability, and reliability
Building and testing applications to ensure quality
Deploying applications efficiently across platforms
Integrating various Google Cloud services for enhanced functionality
Managing and monitoring application performance to maintain optimal operation
Description
Are you gearing up for the Google Professional Cloud Developer certification exam? Welcome to the ideal place to evaluate your preparedness through our specially designed practice exams.
Our tests assess your proficiency in building scalable and highly available applications utilizing Google’s robust tools and adhering to the industry’s best practices.
Succeeding in this exam will spotlight your expertise in cloud-native applications. It will showcase your ability to employ the right tools for development, leverage managed services, and utilize cutting-edge databases.
Why is this significant? Because it amplifies your career prospects. Professionals with these skills are in high demand in today’s industry.
In this course, we present a collection of practice tests comprising both essential knowledge questions that every cloud development professional must know, and specialized queries. Here’s what we offer:
- 254 unique, high-quality test questions.
- Detailed explanations for both correct and incorrect answers.
- Insights into best practices, enriched with references to official guidelines.
- Importantly, our materials do not include outdated ‘Case Studies’ questions, which have been officially excluded from the exam by Google
Our content is carefully curated to enhance your understanding and prime you for success with our well-constructed materials.
So, don’t hesitate. Embark on this journey and put your knowledge to the test with our practice exams!
Quality speaks for itself..
SAMPLE QUESTION:
You recently developed a new service on Cloud Run. The new service authenticates using a custom service, and then writes transactional information to a Cloud Spanner database. You need to verify that your application can support up to 5,000 read transactions and 1,000 write transactions per second while identifying any bottlenecks that may occur. Your test infrastructure must also be able to autoscale.
What should you do?
A. Build a test harness to generate requests and deploy it to Cloud Run. Analyze the VPC Flow Logs using Cloud Logging.
B. Create a Google Kubernetes Engine cluster running the Locust or JMeter images to dynamically generate load tests. Analyze the results using Cloud Trace.
C. Create a Cloud Task to generate a test load. Use Cloud Scheduler to run 60,000 Cloud Task transactions per minute for 10 minutes. Analyze the results using Cloud Monitoring.
D. Create a Compute Engine instance that uses a LAMP stack image from the Marketplace, and use Apache Bench to generate load tests against the service. Analyze the results using Cloud Trace.
What’s your guess? Scroll below for the answer..
Explanation
Incorrect Answers:
A. Build a test harness to generate requests and deploy it to Cloud Run. Analyze the VPC Flow Logs using Cloud Logging.
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Deploying a test harness to Cloud Run would not be an ideal approach for load testing, and VPC Flow Logs are more suited to network monitoring rather than application performance analysis.
C. Create a Cloud Task to generate a test load. Use Cloud Scheduler to run 60,000 Cloud Task transactions per minute for 10 minutes. Analyze the results using Cloud Monitoring.
Using Cloud Task and Cloud Scheduler might not be flexible enough to simulate the required number of read and write transactions per second, especially if the load needs to be varied dynamically to test different scenarios.
D. Create a Compute Engine instance that uses a LAMP stack image from the Marketplace, and use Apache Bench to generate load tests against the service. Analyze the results using Cloud Trace.
A single Compute Engine instance using Apache Bench might not be able to generate enough load to reach the required number of transactions per second. Additionally, the LAMP stack image from the Marketplace is unrelated to the requirements of testing a Cloud Run service.
Correct Answer:
B. Create a Google Kubernetes Engine cluster running the Locust or JMeter images to dynamically generate load tests. Analyze the results using Cloud Trace.
To verify that your application can support up to 5,000 read and 1,000 write transactions per second, and to identify any bottlenecks that may occur, you can use a load testing tool such as Locust or JMeter to generate load tests on your Cloud Run service. These tools allow you to simulate a high number of concurrent requests and help you determine the maximum number of requests your service can handle.
You can run the load testing tool on a Google Kubernetes Engine (GKE) cluster, which will provide the autoscaling feature. This way, you can manage the high number of requests, and use Cloud Trace to analyze the results. This analysis will give you insights into performance and help you identify any bottlenecks.
Links:
Links to Documentation
Welcome to the best practice exams to help you prepare for your Google Professional Cloud Developer exam.
• You can retake the exams as many times as you want
• This is a huge original question bank
• You get support from instructor if you have questions
• Each question has a detailed explanation
• Mobile-compatible with the Udemy app
• 30-days money-back guarantee if you’re not satisfied
We hope that by now you’re convinced! And there are a lot more questions inside the course.
Happy learning and best of luck for your Google Professional Cloud Developer exam!
