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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: 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 for observability and monitoring 1. Planning logging, metrics, and tracing strategies 2. Designing for debugging and troubleshooting - Designing high-performing applications and APIs 1. Selecting appropriate compute and deployment platforms 2. Designing for high availability and fault tolerance 3. Optimizing for latency and throughput
Topic 2: Configuring cloud-native applications for deployment	24%	- Deploying applications to Google Kubernetes Engine 1. Managing configurations and secrets 2. Configuring scaling, auto-scaling, and updates 3. Creating and managing workloads and services - Deploying applications to Cloud Run 1. Deploying from source code or containers 2. Configuring scaling, networking, and security 3. Integrating with event-driven services - Deploying to App Engine or Cloud Functions 1. Configuring serverless deployments 2. Managing versions and traffic splitting
Topic 3: Integrating applications with Google Cloud services	21%	- Integrating with data and storage services 1. Working with relational, NoSQL, and in-memory databases 2. Implementing messaging and event streaming 3. Using object storage and file storage solutions - Consuming Google Cloud APIs and services 1. Using client libraries, REST, and gRPC 2. Enabling and managing APIs 3. Integrating with AI/ML and generative AI services - Implementing application performance monitoring 1. Instrumenting code for metrics and traces 2. Using operations suite tools
Topic 4: Building and testing applications	23%	- Testing applications 1. Using AI-assisted development tools 2. Automating testing in CI/CD workflows 3. Writing unit, integration, and end-to-end tests - Building applications and containers 1. Implementing containerization best practices 2. Using Cloud Build and Artifact Registry 3. Configuring build pipelines and provenance - Setting up development environments 1. Using Cloud SDK, Cloud Code, Cloud Shell, and Cloud Workstations 2. Emulating Google Cloud services locally

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Google Certified Professional - Cloud Developer Sample Questions (Q94-Q99):

NEW QUESTION # 94
Your team is responsible for maintaining an application that aggregates news articles from many different sources. Your monitoring dashboard contains publicly accessible real-time reports and runs on a Compute Engine instance as a web application. External stakeholders and analysts need to access these reports via a secure channel without authentication. How should you configure this secure channel?

A. Use Cloud Scheduler to trigger Cloud Build every hour to create an export from the reports. Store the reports in a public Cloud Storage bucket.
B. Add an HTTP(S) load balancer in front of the monitoring dashboard. Configure Identity-Aware Proxy to secure the communication channel.
C. Add an HTTP(S) load balancer in front of the monitoring dashboard. Set up a Google-managed SSL certificate on the load balancer for traffic encryption.
D. Add a public IP address to the instance. Use the service account key of the instance to encrypt the traffic.

Answer: C

Explanation:
Explanation
https://cloud.google.com/load-balancing/docs/ssl-certificates/google-managed-certs

NEW QUESTION # 95
You work for an ecommerce company. Your company is migrating multiple applications to Google Cloud, and you are assisting with the migration of one of the applications. The application is currently deployed on a VM without any OS dependencies. You have created a Dockerfile and used it to upload a new image to Artifact Registry. You want to minimize the infrastructure and operational complexity. What should you do?

A. Deploy the image to Cloud Run.
B. Deploy the image to a Compute Engine instance.
C. Deploy the image to a GKE Standard cluster.
D. Deploy the image to a GKE Autopilot cluster.

Answer: A

Explanation:
https://services.google.com/fh/files/misc/globalmigrationcustomerebook_2022.pdf

NEW QUESTION # 96
You are deploying your application to a Compute Engine virtual machine instance. Your application is configured to write its log files to disk. You want to view the logs in Stackdriver Logging without changing the application code.
What should you do?

A. Install the Stackdriver Logging Agent and configure it to send the application logs.
B. Provide the log file folder path in the metadata of the instance to configure it to send the application logs.
C. Use a Stackdriver Logging Library to log directly from the application to Stackdriver Logging.
D. Change the application to log to /var/log so that its logs are automatically sent to Stackdriver Logging.

Answer: A

NEW QUESTION # 97
Your teammate has asked you to review the code below, which is adding a credit to an account balance in Cloud Datastore.
Which improvement should you suggest your teammate make?

A. Don't return the account entity from the function.
B. Get the entity with an ancestor query.
C. Get and put the entity in a transaction.
D. Use a strongly consistent transactional database.

Answer: B

Explanation:
Explanation/Reference:

NEW QUESTION # 98
Your API backend is running on multiple cloud providers. You want to generate reports for the network latency of your API.
Which two steps should you take? (Choose two.)

A. Use Zipkin collector to gather data.
B. Use Fluentd agent to gather data.
C. Use Stackdriver Profiler to generate report.
D. Use Stackdriver Trace to generate reports.
E. Use Stackdriver Debugger to generate report.

Answer: A,D

Explanation:
Explanation
https://cloud.google.com/trace/docs/zipkin
"receive traces from Zipkin clients and forward those traces to Cloud Trace for analysis."
https://cloud.google.com/trace/docs/quickstart#analysis_reports_window

NEW QUESTION # 99
......

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