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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Building and testing applications	23%	- Testing applications 1. Writing unit, integration, and end-to-end tests 2. Using AI-assisted development tools 3. Automating testing in CI/CD workflows - Building applications and containers 1. Using Cloud Build and Artifact Registry 2. Implementing containerization best practices 3. Configuring build pipelines and provenance - Setting up development environments 1. Emulating Google Cloud services locally 2. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations
Configuring cloud-native applications for deployment	24%	- Deploying to App Engine or Cloud Functions 1. Managing versions and traffic splitting 2. Configuring serverless deployments - Deploying applications to Google Kubernetes Engine 1. Creating and managing workloads and services 2. Configuring scaling, auto-scaling, and updates 3. Managing configurations and secrets - Deploying applications to Cloud Run 1. Deploying from source code or containers 2. Integrating with event-driven services 3. Configuring scaling, networking, and security
Integrating applications with Google Cloud services	21%	- Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools - Consuming Google Cloud APIs and services 1. Integrating with AI/ML and generative AI services 2. Enabling and managing APIs 3. Using client libraries, REST, and gRPC - Integrating with data and storage services 1. Implementing messaging and event streaming 2. Working with relational, NoSQL, and in-memory databases 3. Using object storage and file storage solutions
Designing highly scalable, secure, and reliable cloud-native applications	32%	- Designing secure applications 1. Applying security best practices and compliance requirements 2. Securing data in transit and at rest 3. Implementing authentication and authorization mechanisms - Designing high-performing applications and APIs 1. Optimizing for latency and throughput 2. Designing for high availability and fault tolerance 3. Selecting appropriate compute and deployment platforms - Designing for observability and monitoring 1. Designing for debugging and troubleshooting 2. Planning logging, metrics, and tracing strategies

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Google Certified Professional - Cloud Developer Sample Questions (Q30-Q35):

NEW QUESTION # 30
Your application is built as a custom machine image. You have multiple unique deployments of the machine image. Each deployment is a separate managed instance group with its own template. Each deployment requires a unique set of configuration values. You want to provide these unique values to each deployment but use the same custom machine image in all deployments. You want to use out-of-the-box features of Compute Engine.
What should you do?

A. Place the unique configuration values in a Cloud Bigtable table.
B. Place the unique configuration values in the instance template startup script.
C. Place the unique configuration values in the instance template instance metadata.
D. Place the unique configuration values in the persistent disk.

Answer: C

Explanation:
https://cloud.google.com/compute/docs/instances/startup-scripts
A startup script is a file that contains commands that run when a virtual machine (VM) instance boots.

NEW QUESTION # 31
You want to view the memory usage of your application deployed on Compute Engine. What should you do?

A. Install the Stackdriver Client Library.
B. Use the Google Cloud Platform Console.
C. Use the Stackdriver Metrics Explorer.
D. Install the Stackdriver Monitoring Agent.

Answer: C

NEW QUESTION # 32
Your company stores their source code in a Cloud Source Repositories repository. Your company wants to build and test their code on each source code commit to the repository and requires a solution that is managed and has minimal operations overhead.
Which method should they use?

A. Use a Compute Engine virtual machine instance with an open source continuous integration tool, configured to watch for source code commits.
B. Use a source code commit trigger to push a message to a Cloud Pub/Sub topic that triggers an App Engine service to build the source code.
C. Use Cloud Build with a trigger configured for each source code commit.
D. Use Jenkins deployed via the Google Cloud Platform Marketplace, configured to watch for source code commits.

Answer: C

Explanation:
https://cloud.google.com/build/docs/automating-builds/create-manage-triggers#:~:text=A%20Cloud%20Build%2

NEW QUESTION # 33
Your company has a BigQuery dataset named "Master" that keeps information about employee travel and expenses. This information is organized by employee department. That means employees should only be able to view information for their department. You want to apply a security framework to enforce this requirement with the minimum number of steps.
What should you do?

A. Create a separate dataset for each department. Create a data pipeline for each department to copy appropriate information from the Master dataset to the specific dataset for the department.
Give employees the permission to this department-specific dataset.
B. Create a separate dataset for each department. Create a view with an appropriate WHERE clause to select records from a particular dataset for the specific department. Authorize this view to access records from your Master dataset. Give employees the permission to this department- specific dataset.
C. Create a dataset named Master dataset. Create a separate view for each department in the Master dataset. Give employees access to the specific view for their department.
D. Create a dataset named Master dataset. Create a separate table for each department in the Master dataset. Give employees access to the specific table for their department.

Answer: C

Explanation:
Create view is easy on one dataset with appropriate where clause. And give permission to department.
Create different dataset(option A) for department is create more steps where question denying it.

NEW QUESTION # 34
Case Study 2 - 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, and that they analyze and respond to any issues that occur.
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.
- Release cycles include development freezes to allow for QA testing.
- The application has no logging.
- Applications are manually deployed by infrastructure engineers during periods of slow traffic on weekday evenings.
- 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.
- Support 10x as many concurrent users.
- 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.
Develop standardized workflows and processes around application lifecycle management.
Define service level indicators (SLIs) and service level objectives (SLOs).
Technical Requirements
- Provide secure communications between the on-premises data center and cloud-hosted applications and infrastructure.
- The application must provide usage metrics and monitoring.
- APIs require authentication and authorization.
- Implement faster and more accurate validation of new features.
- Logging and performance metrics must provide actionable information to be able to provide debugging information and alerts.
- Must scale to meet user demand.
For this question, refer to the HipLocal case study.
A recent security audit discovers that HipLocal's database credentials for their Compute Engine- hosted MySQL databases are stored in plain text on persistent disks. HipLocal needs to reduce the risk of these credentials being stolen. What should they do?

A. Create a service account and download its key. Use the key to authenticate to Cloud Key Management Service (KMS) to obtain the database credentials.
B. Create a service account and grant it the roles/iam.serviceAccountUser role. Impersonate as this account and authenticate using the Cloud SQL Proxy.
C. Grant the roles/secretmanager.secretAccessor role to the Compute Engine service account.Store and access the database credentials with the Secret Manager API.
D. Create a service account and download its key. Use the key to authenticate to Cloud Key Management Service (KMS) to obtain a key used to decrypt the database credentials.

Answer: C

Explanation:
https://cloud.google.com/secret-manager/docs/best-practices

NEW QUESTION # 35
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