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Preparation Guide for Google Professional Cloud Developer Exam
Introduction
Google has designed different Role Based Certifications for the IT professionals to validate their skillset one among them is Google Professional Cloud Developer. This program gives Google cloud professionals a way to demonstrate their skills. The evaluation relies on a meticulous exam using industry standard methodology to validate aspirants proficiency standards to meet Google's proficiency standards.
According to Google, a Google Certified Professional Cloud Developer facilitate organizations to influence Google Cloud technologies. With a thorough understanding of cloud developer and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.
In this guide, we will cover the Google Professional Cloud Developer Exam, Google Professional Cloud Developer Certified Professionals salary and all aspects of the Google Professional Cloud Developer Certification.
NEW QUESTION # 289
You are reviewing and updating your Cloud Build steps to adhere to best practices. Currently, your build steps include:
1. Pull the source code from a source repository.
2. Build a container image
3. Upload the built image to Artifact Registry.
You need to add a step to perform a vulnerability scan of the built container image, and you want the results of the scan to be available to your deployment pipeline running in Google Cloud. You want to minimize changes that could disrupt other teams' processes. What should you do?
Answer: B
Explanation:
https://cloud.google.com/container-analysis/docs/automated-scanning-
howto#view_the_image_vulnerabilities
NEW QUESTION # 290
You recently developed a new application. You want to deploy the application on Cloud Run without a Dockerfile. Your organization requires that all container images are pushed to a centrally managed container repository. How should you build your container using Google Cloud services? (Choose two.)
Answer: A,C
Explanation:
For example, use buildpacks to build the source code of your Cloud Run service into a container image.
https://cloud.google.com/docs/buildpacks/build-application
https://cloud.google.com/blog/products/containers-kubernetes/google-cloud-now-supports- buildpacks If no Dockerfile is present in the source code directory, Google Cloud's buildpacks automatically detects the language you are using and fetches the dependencies of the code to make a production-ready container image, using a secure base image managed by Google.
https://cloud.google.com/run/docs/deploying-source-code
NEW QUESTION # 291
Your service adds text to images that it reads from Cloud Storage. During busy times of the year, requests to Cloud Storage fail with an HTTP 429 "Too Many Requests" status code.
How should you handle this error?
Answer: C
Explanation:
A Cloud Storage JSON API usage limit was exceeded. If your application tries to use more than its limit, additional requests will fail. Throttle your client's requests, and/or use truncated exponential backoff.
https://cloud.google.com/storage/docs/json_api/v1/status-codes
NEW QUESTION # 292
Your application is deployed on hundreds of Compute Engine instances in a managed instance group (MIG) in multiple zones. You need to deploy a new instance template to fix a critical vulnerability immediately but must avoid impact to your service. What setting should be made to the MIG after updating the instance template?
Answer: D
Explanation:
Explanation
https://cloud.google.com/compute/docs/instance-groups/rolling-out-updates-to-managed-instance-groups#type Alternatively, if an automated update is potentially too disruptive, you can choose to perform an opportunistic update. The MIG applies an opportunistic update only when you manually initiate the update on selected instances or when new instances are created. New instances can be created when you or another service, such as an autoscaler, resizes the MIG. Compute Engine does not actively initiate requests to apply opportunistic updates on existing instances.
NEW QUESTION # 293
Your team is trying to reduce their cloud spend, and you want to evaluate your GKE Autopilot cluster costs. When reviewing the manifests, you see that resource requests are currently not specified. Your application is stateless and fault-tolerant, and there are no specific hardware or memory requirements on nodes. You want to modify the cluster to be scalable and cost-effective as quickly as possible while maintaining a cluster with sufficient computing resources. What should you do?
Answer: B
Explanation:
Running Pods as Spot Pods with the cloud.google.com/gke-spot=true label reduces costs significantly for stateless, fault-tolerant workloads while maintaining scalability and sufficient resources in your GKE Autopilot cluster.
NEW QUESTION # 294
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