Google Professional Cloud Developer Exam Practice Test Instant Access

Question 1

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 do9

AUpdate your microservices lo log HTTP request methods and URL paths to STDOUT Use the logs router to send container logs to Cloud Logging. Create fillers in Cloud Logging to evaluate the latency of user requests across different methods and URL paths.

BInstall tcpdiimp on your GKE nodes. Run tcpdunm-- 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

CInstrument your microservices by installing the Open Telemetry 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

DConfigure GKE workload metrics using kubect1. 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 : D

Question 2

You are a developer at a financial institution You use Cloud Shell to interact with Google Cloud services. User data is currently stored on an ephemeral disk however a recently passed regulation mandates that you can no longer store sensitive information on an ephemeral disk. You need to implement a new storage solution for your user data You want to minimize code changes Where should you store your user data'?

AStore user data on a Cloud Shell home disk and log in at least every 120 days to prevent its deletion

BStore user data on a persistent disk in a Compute Engine instance

CStore user data m BigQuery tables

DStore user data in a Cloud Storage bucket

Answer : B

Question 3

You need to containerize a web application that will be hosted on Google Cloud behind a global load balancer with SSL certificates. You don't have the time to develop authentication at the application level, and you want to offload SSL encryption and management from your application. You want to configure the architecture using managed services where possible What should you do?

AHost the application on Compute Engine, and configure Cloud Endpoints for your application.

BHost the application on Google Kubernetes Engine and use Identity-Aware Proxy (IAP) with Cloud Load Balancing and Google-managed certificates.

CHost the application on Google Kubernetes Engine, and deploy an NGINX Ingress Controller to handle authentication.

DHost the application on Google Kubernetes Engine, and deploy cert-manager to manage SSL certificates.

Answer : B

Question 4

You are a developer at a large organization. You are deploying a web application to Google Kubernetes Engine (GKE). The DevOps team has built a CI/CD pipeline that uses Cloud Deploy to deploy the application to Dev Test, and Prod clusters in GKE. After Cloud Deploy successfully deploys the application to the Dev cluster you want to automatically promote it to the Test Cluster. How should you configure this process following Google-recommended best practices?

A1 Create a Cloud Build trigger that listens for SUCCEEDED Pub/Sub messages from the clouddeploy-operations topic.
2 Configure Cloud Build to include a step that promotes the application to the Test cluster

B1 Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster
2 Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the cloud-builds topic

C1 Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster
2 Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the clouddeploy operations topic

D1 Create a Cloud Build pipeline that uses the gke-deploy builder
2 Create a Cloud Build trigger that listens to SUCCEEDED Pub/Sub messages from the cloud-builds topic
3 Configure this pipeline to run a deployment step to the Test cluster

Answer : B

Question 5

You have an application running on Google Kubernetes Engine (GKE). The application is currently using a logging library and is outputting to standard output You need to export the logs to Cloud Logging, and you need the logs to include metadata about each request. You want to use the simplest method to accomplish this. What should you do?

AChange your application s logging library to the Cloud Logging library and configure your application to export logs to Cloud Logging

BUpdate your application to output logs in CSV format, and add the necessary metadata to the CSV.

CInstall the Fluent Bit agent on each of your GKE nodes, and have the agent export all logs from /var/ log.

DUpdate your application to output logs in JSON format, and add the necessary metadata to the JSON

Answer : B

Question 6

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?

AAdd a startup probe.

BIncrease the initial delay for the liveness probe.

CIncrease the CPU limit for the container.

DAdd a readiness probe.

Answer : B

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

Question 7

You are monitoring a web application that is written in Go and deployed in Google Kubernetes Engine. You notice an increase in CPU and memory utilization. You need to determine which source code is consuming the most CPU and memory resources. What should you do?

ADownload, install, and start the Snapshot Debugger agent in your VM. Take debug snapshots of the functions that take the longest time. Review the call stack frame, and identify the local variables at that level in the stack.

BImport the Cloud Profiler package into your application, and initialize the Profiler agent. Review the generated flame graph in the Google Cloud console to identify time-intensive functions.

CImport OpenTelemetry and Trace export packages into your application, and create the trace provider.
Review the latency data for your application on the Trace overview page, and identify where bottlenecks are occurring.

DCreate a Cloud Logging query that gathers the web application's logs. Write a Python script that calculates the difference between the timestamps from the beginning and the end of the application's longest functions to identity time-intensive functions.

Answer : B