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Google Professional-Cloud-Developer Exam is an important certification for individuals who want to demonstrate their proficiency in developing and deploying applications on Google Cloud Platform. By passing Professional-Cloud-Developer exam and becoming certified, individuals can validate their skills and knowledge in cloud development, which can help them advance their careers and achieve their professional goals.

Managing Application Performance Monitoring

Troubleshoot Application Performance: This one covers the skills of the test takers in using Cloud Debugger, creating and writing custom and log-based metrics, exporting the logs from GC, and using forums, Google Cloud support, and documentation, among others.
Manage Workloads for the Google Kubernetes Engine: The considerations for this topic include configuring monitoring & logging, viewing & analyzing logs, configuring workload auto-scaling, writing & exporting custom metrics, and analyzing the lifecycle events of a container.
Manage Compute Engine Virtual Machines: It covers the applicants’ skills in analyzing & viewing logs; debugging custom VM images with serial ports, sending logs to Cloud Logging from VMs, and inspecting resource usage over time.

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Google Professional-Cloud-Developer Certification is recognized globally and is highly valued in the cloud computing industry. Google Certified Professional - Cloud Developer certification provides a competitive edge to software developers and helps them to stand out in the job market. In addition, this certification also helps organizations to identify and hire skilled professionals who can develop and deploy applications on GCP. By becoming a Google Certified Professional - Cloud Developer, individuals can demonstrate their commitment to staying current with the latest cloud technologies and their ability to design, develop, and manage cloud applications on GCP.

Google Certified Professional - Cloud Developer Sample Questions (Q385-Q390):

NEW QUESTION # 385
Your team develops services that run on Google Kubernetes Engine. Your team's code is stored in Cloud Source Repositories. You need to quickly identify bugs in the code before it is deployed to production. You want to invest in automation to improve developer feedback and make the process as efficient as possible.
What should you do?

A. Use Cloud Build to automate building container images from code based on Git tags.
B. Use Spinnaker to automate deploying container images to the production environment.
C. Use Cloud Build to automate building container images from code based on forked versions.
D. Use Spinnaker to automate building container images from code based on Git tags.

Answer: D

Explanation:
Reference: https://spinnaker.io/docs/guides/tutorials/codelabs/kubernetes-v2-source-to-prod/

NEW QUESTION # 386
You are a developer at a large organization. Your team uses Git for source code management (SCM). You want to ensure that your team follows Google-recommended best practices to manage code to drive higher rates of software delivery. Which SCM process should your team use?

A. Each developer commits their code to the main branch before each product release, conducts testing, and rolls back if integration issues are detected.
B. Each developer creates a branch for their own work, commits their changes to their branch, and merges their code into the main branch after peer review.
C. Each group of developers creates a feature branch from the main branch for their work, commits their changes to their branch, and merges their code into the main branch before each major release.
D. Each group of developers copies the repository, commits their changes to their repository, and merges their code into the main repository before each product release.

Answer: B

NEW QUESTION # 387
You are developing a dashboard that aggregates temperature readings from thousands of IoT devices monitoring a city's ambient temperature. You expect a large amount of viewing traffic resulting in a large amount of data egress once the dashboard is live. The dashboard temperature display data doesn't need to be real-time and can tolerate a few seconds of lag. You decide to deploy Memorystore for Redis as the storage backend. You want to ensure that the dashboard will be highly available. How should you configure the service in Memorystore for Redis?

A. Update Memorystore for Redis to the latest version.
B. Configure Memorystore to use read replicas.
C. Use Private Service Access to enable low-latency network throughput.
D. Set up Serverless VPC Access to avoid receiving traffic over the internet.

Answer: B

Explanation:
Using read replicas in Memorystore for Redis enhances availability by providing redundancy. If the primary instance experiences downtime, read replicas can continue serving requests, ensuring that the dashboard remains accessible. Read replicas also help distribute read traffic, which can be beneficial for high-demand applications, even though Redis itself is an in-memory store with fast access.
- Updating to the latest version may improve performance or security but does not directly improve availability.
- Private Service Access and Serverless VPC Access are network configurations that reduce latency and secure connections but do not inherently improve availability.

NEW QUESTION # 388
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.

Answer: A

Explanation:
https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-

NEW QUESTION # 389

A. Grant your user account the roles/iam.serviceAccountUser role for the service-PROJECTA@gcf-admin- robot.iam.gserviceaccount.com service account.
B. Grant your user account the roles/storage.objectCreator role for the Cloud Storage bucket.
C. Grant the service-PROJECTA@gcf-admin-robot.iam.gserviceaccount.com service account the roles/ storage.objectCreator role for the Cloud Storage bucket.
D. Enable the Cloud Storage API in project B.
E. It is supposed to write an object in a Cloud Storage bucket owned by project B. However, the write call is failing with the error "403 Forbidden".
What should you do to correct the problem?

Answer: A

NEW QUESTION # 390
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