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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
Designing cloud-native applications	- Scalability and resiliency patterns - Microservices design principles - Application architecture design
Deploying applications	- Containerization and deployment (Cloud Run, GKE) - CI/CD pipelines - Release management strategies
Ensuring application performance and reliability	- Fault tolerance and incident response - Monitoring and logging (Cloud Monitoring, Cloud Logging) - Performance optimization
Building and testing applications	- Debugging and troubleshooting applications - Application development on Google Cloud - Unit and integration testing strategies
Integrating Google Cloud services	- API integration and service-to-service communication - Using managed services (Pub/Sub, Firestore, Cloud SQL)

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Google Certified Professional - Cloud Developer Sample Questions (Q209-Q214):

NEW QUESTION # 209
You are developing an online gaming platform as a microservices application on Google Kubernetes Engine (GKE). Users on social media are complaining about long loading times for certain URL requests to the application. You need to investigate performance bottlenecks in the application and identify which HTTP requests have a significantly high latency span in user requests. What should you do?

A. Update your microservices to log HTTP request methods and URL paths to STDOUT. Use the logs router to send container logs to Cloud Logging. Create filters in Cloud Logging to evaluate the latency of user requests across different methods and URL paths.
B. Install tcpdump on your GKE nodes. Run tcpdump to capture network traffic over an extended period of time to collect data. Analyze the data files using Wireshark to determine the cause of high latency.
C. Instrument your microservices by installing the OpenTelemetry tracing package. Update your application code to send traces to Trace for inspection and analysis. Create an analysis report on Trace to analyze user requests.
D. Configure GKE workload metrics using kubectl. Select all Pods to send their metrics to Cloud Monitoring. Create a custom dashboard of application metrics in Cloud Monitoring to determine performance bottlenecks of your GKE cluster.

Answer: C

Explanation:
https://cloud.google.com/trace/docs/setup#when-to-instrument

NEW QUESTION # 210
You deployed a new application to Google Kubernetes Engine and are experiencing some performance degradation. Your logs are being written to Cloud Logging, and you are using a Prometheus sidecar model for capturing metrics. You need to correlate the metrics and data from the logs to troubleshoot the performance issue and send real-time alerts while minimizing costs. What should you do?

A. Export the Cloud Logging logs and the Prometheus metrics to Cloud Bigtable. Run a query to join the results, and analyze in Google Data Studio.
B. Create custom metrics from the Cloud Logging logs, and use Prometheus to import the results using the Cloud Monitoring REST API.
C. Export the Prometheus metrics and use Cloud Monitoring to view them as external metrics. Configure Cloud Monitoring to create log-based metrics from the logs, and correlate them with the Prometheus data.
D. Export the Cloud Logging logs and stream the Prometheus metrics to BigQuery. Run a recurring query to join the results, and send notifications using Cloud Tasks.

Answer: C

Explanation:
Reference:
https://cloud.google.com/blog/products/operations/troubleshoot-gke-faster-with-monitoring-data-in-your-logs

NEW QUESTION # 211
You are building a Workflow to process complex data analytics for your application. You plan to use the Workflow to execute a Cloud Run job while following Google-recommended practices.
What should you do?

A. Determine the entry point of the Cloud Run job, and send an HTTP request from the Workflow.
B. Create a Pub/Sub topic, and subscribe the Cloud Run job to the topic.
C. Use the Cloud Run Admin API connector to execute the Cloud Run job within the Workflow.
D. Configure an Eventarc trigger to invoke the Cloud Run job, and include the trigger in a step of the Workflow.

Answer: C

Explanation:
Using the Cloud Run Admin API connector within Workflows is the Google-recommended way to directly execute a Cloud Run job from a Workflow, providing secure and managed integration.

NEW QUESTION # 212
You recently joined a new team that has a Cloud Spanner database instance running in production. Your manager has asked you to optimize the Spanner instance to reduce cost while maintaining high reliability and availability of the database. What should you do?

A. Use Cloud Monitoring to monitor the CPU utilization, and reduce Spanner processing units by small increments until you find the minimum capacity required.
B. Use Snapshot Debugger to check for application errors, and reduce Spanner processing units by small increments until you find the minimum capacity required.
C. Use Cloud Trace to monitor the requests per sec of incoming requests to Spanner, and reduce Spanner processing units by small increments until you find the minimum capacity required.
D. Use Cloud Logging to check for error logs, and reduce Spanner processing units by small increments until you find the minimum capacity required.

Answer: A

Explanation:
https://cloud.google.com/spanner/docs/compute-
capacity#increasing_and_decreasing_compute_capacity

NEW QUESTION # 213
Your application is deployed in a Google Kubernetes Engine (GKE) cluster. When a new version of your application is released, your CI/CD tool updates the spec.template.spec.containers[0].image value to reference the Docker image of your new application version. When the Deployment object applies the change, you want to deploy at least 1 replica of the new version and maintain the previous replicas until the new replica is healthy.
Which change should you make to the GKE Deployment object shown below?

A. Set the Deployment strategy to RollingUpdate with maxSurge set to 0, maxUnavailable set to 1.
B. Set the Deployment strategy to RollingUpdate with maxSurge set to 1, maxUnavailable set to 0.
C. Set the Deployment strategy to Recreate with maxSurge set to 0, maxUnavailable set to 1.
D. Set the Deployment strategy to Recreate with maxSurge set to 1, maxUnavailable set to 0.

Answer: D

NEW QUESTION # 214
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