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How to Prepare For Google Professional Cloud Developer Exam
Preparation Guide for Google Professional Cloud Developer Exam
Introduction
Google has designed different Role Based Certifications for the IT professionals to validate their skillset one among them is Google Professional Cloud Developer. This program gives Google cloud professionals a way to demonstrate their skills. The evaluation relies on a meticulous exam using industry standard methodology to validate aspirants proficiency standards to meet Google's proficiency standards.
According to Google, a Google Certified Professional Cloud Developer facilitate organizations to influence Google Cloud technologies. With a thorough understanding of cloud developer and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.
In this guide, we will cover the Google Professional Cloud Developer Exam, Google Professional Cloud Developer Certified Professionals salary and all aspects of the Google Professional Cloud Developer Certification.
Reference: https://cloud.google.com/certification/cloud-developer
Google Professional-Cloud-Developer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Manage application performance monitoring | - Monitor and troubleshoot applications
|
| Design scalable, available, and reliable cloud-native applications | - Design highly performant applications and APIs
|
| Deploy applications | - Deploy applications to Google Cloud
|
| Build and test applications | - Manage development environments
|
| Integrate applications with Google Cloud services | - Integrate with data and storage services
|
Google Certified Professional - Cloud Developer Sample Questions:
You recently developed a web application to transfer log data to a Cloud Storage bucket daily.
Authenticated users will regularly review logs from the prior two weeks for critical events. After that, logs will be reviewed once annually by an external auditor. Data must be stored for a period of no less than 7 years. You want to propose a storage solution that meets these requirements and minimizes costs. What should you do? (Choose two.)
- A. Run a scheduled job to set the storage class to Coldline for objects older than 14 days.
- B. Create a JSON Web Token (JWT) for users needing access to the Coldline storage buckets.
- C. Create a lifecycle management policy to set the storage class to Nearline for objects older than
14 days. - D. Use the Bucket Lock feature to set the retention policy on the data.
- E. Create a lifecycle management policy to set the storage class to Coldline for objects older than 14 days.
Correct Answer: D,E 🗳️
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You work at a rapidly growing financial technology startup. You manage the payment processing application written in Go and hosted on Cloud Run in the Singapore region (asia-southeast1). The payment processing application processes data stored in a Cloud Storage bucket that is also located in the Singapore region.
The startup plans to expand further into the Asia Pacific region. You plan to deploy the Payment Gateway in Jakarta, Hong Kong, and Taiwan over the next six months. Each location has data residency requirements that require customer data to reside in the country where the transaction was made. You want to minimize the cost of these deployments. What should you do?
- A. Create a Cloud Storage bucket in each region, and create three Cloud Run services of the payment processing application in the Singapore region.
- B. Create three Cloud Storage buckets in the Asia multi-region, and create three Cloud Run services of the payment processing application in the Singapore region.
- C. Create a Cloud Storage bucket in each region, and create a Cloud Run service of the payment processing application in each region.
- D. Create three Cloud Storage buckets in the Asia multi-region, and create three Cloud Run revisions of the payment processing application in the Singapore region.
Correct Answer: C 🗳️
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Case Study 1 - HipLocal
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 wants to reduce the number of on-call engineers and eliminate manual scaling.
Which two services should they choose? (Choose two.)
- A. Use serverless Google Cloud Functions.
- B. Use Google App Engine services.
- C. Use Google Kubernetes Engine for automated deployments.
- D. Use Knative to build and deploy serverless applications.
- E. Use a large Google Compute Engine cluster for deployments.
Correct Answer: C,D 🗳️
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Your company needs a database solution that stores customer purchase history and meets the following requirements:
- Customers can query their purchase immediately after submission.
- Purchases can be sorted on a variety of fields.
- Distinct record formats can be stored at the same time.
Which storage option satisfies these requirements?
- A. Firestore in Datastore mode using a global query
- B. Cloud Storage using an object read
- C. Cloud SQL using a SQL SELECT statement
- D. Firestore in Native mode
Correct Answer: D 🗳️
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Your team develops services that run on Google Cloud. You want to process messages sent to a Pub/Sub topic, and then store them. Each message must be processed exactly once to avoid duplication of data and any data conflicts. You need to use the cheapest and most simple solution. What should you do?
- A. Process the messages with a Cloud Function, and write the results to a BigQuery location where you can run a job to deduplicate the data.
- B. Process the messages with a Dataflow streaming pipeline using Apache Beam's PubSubIO package, and write the output to storage.
- C. Retrieve the messages with a Dataflow streaming pipeline, store them in Cloud Bigtable, and use another Dataflow streaming pipeline to deduplicate messages.
- D. Process the messages with a Dataproc job, and write the output to storage.
Correct Answer: B 🗳️
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