Professional-Cloud-Developer Übungsmaterialien - Professional-Cloud-Developer Lernressourcen & Professional-Cloud-Developer Prüfungsfragen

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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
Build and test applications	- Manage development environments 1. Build application artifacts 2. Perform application testing 3. Implement CI/CD pipelines
Design scalable, available, and reliable cloud-native applications	- Design highly performant applications and APIs 1. Choose storage options for application data 2. Design resilient and scalable application architectures 3. Design secure applications
Manage application performance monitoring	- Monitor and troubleshoot applications 1. Configure logging and tracing 2. Optimize application performance 3. Analyze metrics and alerts
Integrate applications with Google Cloud services	- Integrate with data and storage services 1. Implement authentication and authorization 2. Use messaging and event-driven services 3. Integrate with Google Cloud APIs
Deploy applications	- Deploy applications to Google Cloud 1. Deploy applications using Cloud Run 2. Manage application rollout strategies 3. Deploy applications to Google Kubernetes Engine

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Professional-Cloud-Developer PrüfungGuide, Google Professional-Cloud-Developer Zertifikat - Google Certified Professional - Cloud Developer

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Google Certified Professional - Cloud Developer Professional-Cloud-Developer Prüfungsfragen mit Lösungen (Q351-Q356):

351. Frage
You have a container deployed on Google Kubernetes Engine. The container can sometimes be slow to launch, so you have implemented a liveness probe. You notice that the liveness probe occasionally fails on launch. What should you do?

A. Increase the initial delay for the liveness probe.
B. Add a readiness probe.
C. Add a startup probe.
D. Increase the CPU limit for the container.

Antwort: C

Begründung:
https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup- probes/#define-startup-probes The kubelet uses startup probes to know when a container application has started. If such a probe is configured, it disables liveness and readiness checks until it succeeds, making sure those probes don't interfere with the application startup. This can be used to adopt liveness checks on slow starting containers, avoiding them getting killed by the kubelet before they are up and running.

352. Frage
You recently deployed a Go application on Google Kubernetes Engine (GKE). The operations team has noticed that the application's CPU usage is high even when there is low production traffic. The operations team has asked you to optimize your application's CPU resource consumption. You want to determine which Go functions consume the largest amount of CPU. What should you do?

A. Create a custom dashboard in Cloud Monitoring to evaluate the CPU performance metrics of your application.
B. Connect to your GKE nodes using SSH. Run the top command on the shell to extract the CPU utilization of your application.
C. Modify your Go application to capture profiling data. Analyze the CPU metrics of your application in flame graphs in Profiler.
D. Deploy a Fluent Bit daemonset on the GKE cluster to log data in Cloud Logging. Analyze the logs to get insights into your application code's performance.

Antwort: C

Begründung:
https://cloud.google.com/profiler/docs/about-profiler
Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications. It attributes that information to the source code that generated it, helping you identify the parts of your application that are consuming the most resources, and otherwise illuminating your applications performance characteristics.
https://cloud.google.com/profiler/docs

353. Frage
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 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.
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 Cloud Logging logs and stream the Prometheus metrics to BigQuery. Run a recurring query to join the results, and send notifications using Cloud Tasks.
D. 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.

Antwort: A

354. Frage
You are a developer that works for a local concert venue. Customers use your company's website to purchase tickets for events. You need to provide customers with immediate confirmation when a selected seat has been reserved. How should you design the ticket ordering process?

A. Upload the seat reservation to a Cloud Storage bucket, which triggers an event to the backend service that processes the seat reservation.
B. Publish the seat reservation to a Pub/Sub topic. Configure the backend service to subscribe to the topic to process the seat reservation.
C. Add the seat reservation to a Cloud Tasks queue, which triggers Workflows to process the seat reservation.
D. Submit the seat reservation in an HTTP POST request to an Application Load Balancer.
Configure the Application Load Balancer to distribute the request to the backend service that processes the seat reservation.

Antwort: D

Begründung:
Submitting the seat reservation via an HTTP POST request to an Application Load Balancer provides immediate, synchronous processing and confirmation to the customer, which is essential for real-time seat reservations.

355. Frage
This architectural diagram depicts a system that streams data from thousands of devices. You want to ingest data into a pipeline, store the data, and analyze the data using SQL statements. Which Google Cloud services should you use for steps 1, 2, 3, and 4?

A. 1) App Engine
2) Pub/Sub
3) BigQuery
4) Firestore
B. 1) Pub/Sub
2) Dataflow
3) Firestore
4) BigQuery
C. 1) Dataflow
2) Pub/Sub
3) Firestore
4) BigQuery
D. 1) Pub/Sub
2) Dataflow
3) BigQuery
4) Firestore

Antwort: B

356. Frage
......

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Professional-Cloud-Developer Fragenkatalog: https://www.zertpruefung.ch/Professional-Cloud-Developer_exam.html

Außerdem sind jetzt einige Teile dieser ZertPruefung Professional-Cloud-Developer Prüfungsfragen kostenlos erhältlich: https://drive.google.com/open?id=1MXMaV1NLKHUenbsUpGFUqTrYt70pW_oG