Your team is developing a Cloud Function triggered by Cloud Storage Events. You want to accelerate testing and development of your Cloud Function while following Google-recommended best practices. What should you do?

Install the Functions Frameworks library, and configure the Cloud Function on localhost. Make a copy of the function, and make edits to the new version Test the new version using cur1.

Make a copy of the Cloud Function, and rewrite the code to be HTTP-triggered Edit and test the new version by triggering the HTTP endpoint. Send mock requests to the new function to evaluate the functionality.

Make a copy of the Cloud Function in the Google Cloud Console Use the Cloud console's in-line editor to make source code changes to the new function Modify your web application to call the new function and test the new version in production.

Create a new Cloud Function that is triggered when Cloud Audit Logs detects the cloudfunctions. functions. sourceCodeSet operation in the original Cloud Function Send mock requests to the new function to evaluate the functionality.

Your team recently deployed an application on Google Kubernetes Engine (GKE). You are monitoring your application and want to be alerted when the average memory consumption of your containers is under 20% or above 80% How should you configure the alerts?

In Cloud Monitoring, create an alerting policy to notify you if the average memory consumption is outside the defined range

Create a Cloud Function that consumes the Monitoring API. Create a schedule to trigger the Cloud Function hourly and alert you if the average memory consumption is outside the defined range

In Cloud Monitoring, create an alerting policy to notify you if the average memory consumption is outside the defined range

Create a Cloud Function that runs on a schedule, executes kubect1 top on all the workloads on the cluster, and sends an email alert if the average memory consumption is outside the defined range

Write a script that pulls the memory consumption of the instance at the OS level and sends an email alert if the average memory consumption is outside the defined range

You are developing a new application. You want the application to be triggered only when a given file is updated in your Cloud Storage bucket. Your trigger might change, so your process must support different types of triggers. You want the configuration to be simple so that multiple team members can update the triggers in the future. What should you do?

Configure a Firebase function that executes your application and is triggered when an object is updated in Cloud Storage.

Create an Eventarc trigger that monitors your Cloud Storage bucket for a specific filename, and set the target as Cloud Run.

Configure Cloud Storage events to be sent to Pub/Sub, and use Pub/Sub events to trigger a Cloud Build job that executes your application.

Configure a Firebase function that executes your application and is triggered when an object is updated in Cloud Storage.

Configure a Cloud Function that executes your application and is triggered when an object is updated in Cloud Storage.

You need to deploy an internet-facing microservices application to Google Kubernetes Engine (GKE). You want to validate new features using the A/B testing method. You have the following requirements for deploying new container image releases* There is no downtime when new container images are deployed.* New production releases are tested and verified using a subset of production users.What should you do?

1 Create a second namespace on GKE for the new release version. 2 Create a Deployment configuration for the second namespace with the desired number of Pods. 3 Deploy new container versions in the second namespace. 4 Update the ingress configuration to route traffic to the namespace with the new container versions.

1 Configure your Cl/CD pipeline to update the Deployment manifest file by replacing the container version with the latest version. 2 Recreate the Pods in your cluster by applying the Deployment manifest file. 3 Validate the application's performance by comparing its functionality with the previous release version and roll back if an issue arises.

1 install the Anthos Service Mesh on your GKE cluster. 2 Create two Deployments on the GKE cluster and label them with different version names. 3 Create a VirtualService with a routing rule to send a small percentage of traffic to the Deployment that references the new version of the application.

1 Create a second namespace on GKE for the new release version. 2 Create a Deployment configuration for the second namespace with the desired number of Pods. 3 Deploy new container versions in the second namespace. 4 Update the ingress configuration to route traffic to the namespace with the new container versions.

1. Implement a rolling update pattern by replacing the Pods gradually with the new release versify. 2 Validate the application's performance for the new subset of users during the rollout and roll back if an issue arises.

You are developing an event-driven application. You have created a topic to receive messages sent to Pub/Sub. You want those messages to be processed in real time. You need the application to be independent from any other system and only incur compute costs when new messages arrive. You want to configure the simplest and most efficient architecture What should you do?

Deploy your code on Cloud Functions. Use a Pub/Sub trigger to handle new messages in the topic.

Deploy your code on Cloud Functions. Use a Pub/Sub trigger to invoke the Cloud Function. Use the Pub/Sub API to create a pull subscription to the Pub/Sub topic and read messages from it.

Deploy your code on Cloud Functions. Use a Pub/Sub trigger to handle new messages in the topic.

Deploy the application on Google Kubernetes Engine. Use the Pub/Sub API to create a pull subscription to the Pub/Sub topic and read messages from it

Deploy the application on Compute Engine. Use a Pub/Sub push subscription to process new messages in the topic.

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?

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 after the change advisory board approves it.

Each developer commits their code to the main branch before each product release, conducts testing, and rolls back if integration issues are detected.

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.

Each developer creates a branch for their own work, commits their changes to their branch, and merges their code into the main branch daily.

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 after the change advisory board approves it.

You recently developed an application that monitors a large number of stock prices. You need to configure Pub/Sub to receive a high volume messages and update the current stock price in a single large in-memory database The downstream service needs only the most up-to-date prices in the in-memory database to perform stock trading transactions Each message contains three pieces of information* Stock symbol* Stock price* Timestamp for the update.How should you set up your Pub/Sub subscription?

Create a push subscription with exactly-once delivery enabled

Create a pull subscription with both ordering and exactly-once delivery turned off

Create a pull subscription with exactly-once delivery enabled

Create a push subscription with exactly-once delivery enabled

Create a push subscription with both ordering and exactly-once delivery turned off

You are a developer at a large corporation You manage three Google Kubernetes Engine clusters. Your team's developers need to switch from one cluster to another regularly without losing access to their preferred development tools. You want to configure access to these clusters using the fewest number of steps while following Google-recommended best practices. What should you do?

In a configuration file, define the clusters users, and contexts Email the file to the developers and ask them to use kubect1 config to add cluster, user and context details.

Ask the developers to use Cloud Shell and run gcloud container clusters get-credentials to switch to another cluster.

Ask the developers to open three terminals on their workstation and use kubecrt1 config to configure access to each cluster.

Ask the developers to install the gcloud CLI on their workstation and run gcloud container clusters get-credentials to switch to another cluster

In a configuration file, define the clusters users, and contexts Email the file to the developers and ask them to use kubect1 config to add cluster, user and context details.

You have a web application that publishes messages to Pub/Sub. You plan to build new versions of the application locally and need to quickly test Pub/Sub integration tor each new build. How should you configure local testing?

Install Cloud Code on the integrated development environment (IDE) Navigate to Cloud APIs, and enable Pub/Sub against a valid Google Project ID. When developing locally, configure your application to call pubsub.googleapis com

Run the gclcud config set api_endpoint_overrides/pubsub https: / 'pubsubemulator.googleapi3.com. coin/ command to change the Pub/Sub endpoint prior to starting the application

In the Google Cloud console, navigate to the API Library and enable the Pub/Sub API When developing locally, configure your application to call pubsub.googleapis com

Install Cloud Code on the integrated development environment (IDE) Navigate to Cloud APIs, and enable Pub/Sub against a valid Google Project ID. When developing locally, configure your application to call pubsub.googleapis com

Install the Pub/Sub emulator using gcloud and start the emulator with a valid Google Project ID. When developing locally, configure your application to use the local emulator by exporting the fuhsub emulator Host variable

You are supporting a business-critical application in production deployed on Cloud Run. The application is reporting HTTP 500 errors that are affecting the usability of the application. You want to be alerted when the number of errors exceeds 15% of the requests within a specific time window. What should you do?

Create a Cloud Function that consumes the Cloud Monitoring API Use Cloud Composer to trigger the Cloud Function daily and alert you if the number of errors is above the defined threshold.

Navigate to the Cloud Run page in the Google Cloud console, and select the service from the services list. Use the Metrics tab to visualize the number of errors for that revision and refresh the page daily.

Create a Cloud Function that consumes the Cloud Monitoring API Use Cloud Composer to trigger the Cloud Function daily and alert you if the number of errors is above the defined threshold.

Create an alerting policy in Cloud Monitoring that alerts you if the number of errors is above the defined threshold.

Create a Cloud Function that consumes the Cloud Monitoring API Use Cloud Scheduler to trigger the Cloud Function daily and alert you if the number of errors is above the defined threshold

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?

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

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

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

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

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

Your application stores customers' content in a Cloud Storage bucket, with each object being encrypted with the customer's encryption key. The key for each object in Cloud Storage is entered into your application by the customer. You discover that your application is receiving an HTTP 4xx error when reading the object from Cloud Storage What is a possible cause of this error?

You attempted the read operation on the object with the customers base64-encoded key.

You attempted the read operation without the base64-encoded SHA256 hash of the encryption key.

You entered the same encryption algorithm specified by the customer when attempting the read operation.

You attempted the read operation on the object with the base64-encoded SHA256 hash of the customer's key.

You attempted the read operation on the object with the customers base64-encoded key.

You are reviewing and updating your Cloud Build steps to adhere to Google-recommended practices. Currently, your build steps include:1. Pull the source code from a source repository.2. Build a container image3. 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?

Enable the Container Scanning API in Artifact Registry, and scan the built container images for vulnerabilities.

Enable Binary Authorization, and configure it to attest that no vulnerabilities exist in a container image.

Enable the Container Scanning API in Artifact Registry, and scan the built container images for vulnerabilities.

Upload the built container images to your Docker Hub instance, and scan them for vulnerabilities.

Add Artifact Registry to your Aqua Security instance, and scan the built container images for vulnerabilities

You work on an application that relies on Cloud Spanner as its main datastore. New application features have occasionally caused performance regressions. You want to prevent performance issues by running an automated performance test with Cloud Build for each commit made. If multiple commits are made at the same time, the tests might run concurrently. What should you do?

Create a new Cloud Spanner instance for every build. Load the required data. Delete the Cloud Spanner instance after the test is run.

Create a new project with a random name for every build. Load the required data. Delete the project after the test is run.

Create a new Cloud Spanner instance for every build. Load the required data. Delete the Cloud Spanner instance after the test is run.

Create a project with a Cloud Spanner instance and the required data. Adjust the Cloud Build build file to automatically restore the data to its previous state after the test is run.

Start the Cloud Spanner emulator locally. Load the required data. Shut down the emulator after the test is run.

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

Import 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.

Create 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.

Import 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 which functions cause the most latercy.

Add print commands to the application source code to log when each function is called, and redeploy the application.

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?

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.

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.

Each developer commits their code to the main branch before each product release, conducts testing, and rolls back if integration issues are detected.

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.

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.

You are tasked with using C++ to build and deploy a microservice for an application hosted on Google Cloud. The code needs to be containerized and use several custom software libraries that your team has built. You do not want to maintain the underlying infrastructure of the application How should you deploy the microservice?

Use Cloud Build to create the container, and deploy it on Cloud Run.

Use Cloud Functions to deploy the microservice.

Use Cloud Build to create the container, and deploy it on Cloud Run.

Use Cloud Shell to containerize your microservice. and deploy it on GKE Standard.

Use Cloud Shell to containerize your microservice. and deploy it on a Container-Optimized OS Compute Engine instance.

Your team is creating a serverless web application on Cloud Run. The application needs to access images stored in a private Cloud Storage bucket. You want to give the application Identity and Access Management (IAM) permission to access the images in the bucket, while also securing the services using Google-recommended best practices What should you do?

Enforce public access prevention for the desired bucket. Grant the Storage Object Viewer IAM role on the bucket to the Compute Engine default service account.

Enforce signed URLs for the desired bucket. Grant the Storage Object Viewer IAM role on the bucket to the Compute Engine default service account.

Enforce public access prevention for the desired bucket. Grant the Storage Object Viewer IAM role on the bucket to the Compute Engine default service account.

Enforce signed URLs for the desired bucket Create and update the Cloud Run service to use a user -managed service account. Grant the Storage Object Viewer IAM role on the bucket to the service account

Enforce public access prevention for the desired bucket. Create and update the Cloud Run service to use a user-managed service account. Grant the Storage Object Viewer IAM role on the bucket to the service account.

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

Configure 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.

Update 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.

Install 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

Instrument 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

Configure 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.

You are a developer at a social media company The company runs their social media website on-premises and uses MySQL as a backend to store user profiles and user posts. Your company plans to migrate to Google Cloud, and your team will migrate user profile information to Firestore. You are tasked with designing the Firestore collections. What should you do?

Create one root collection for user profiles, and create one subcollection for each user's posts.

Create one root collection for user profiles, and store each user's post as a nested list in the user profile document.

Create one root collection for user profiles, and create one root collection for user posts.

Create one root collection for user profiles, and create one subcollection for each user's posts.

Create one root collection for user posts, and create one subcollection for each user's profile

You manage a microservice-based ecommerce platform on Google Cloud that sends confirmation emails to a third-party email service provider using a Cloud Function. Your company just launched a marketing campaign, and some customers are reporting that they have not received order confirmation emails. You discover that the services triggering the Cloud Function are receiving HTTP 500 errors. You need to change the way emails are handled to minimize email loss. What should you do?

Configure the sender application to publish the outgoing emails in a message to a Pub/Sub topic. Update the Cloud Function configuration to consume the Pub/Sub queue.

Increase the Cloud Function's timeout to nine minutes.

Configure the sender application to publish the outgoing emails in a message to a Pub/Sub topic. Update the Cloud Function configuration to consume the Pub/Sub queue.

Configure the sender application to write emails to Memorystore and then trigger the Cloud Function. When the function is triggered, it reads the email details from Memorystore and sends them to the email service.

Configure the sender application to retry the execution of the Cloud Function every one second if a request fails.

A governmental regulation was recently passed that affects your application. For compliance purposes, you are now required to send a duplicate of specific application logs from your application's project to a project that is restricted to the security team. What should you do?

Create user-defined log buckets in the security team's project. Configure a Cloud Logging sink to route your application s logs to log buckets in the security team's project.

Modify the _Default tog bucket sink rules to reroute the logs into the security team's log bucket.

Create user-defined log buckets in the security team's project. Configure a Cloud Logging sink to route your application s logs to log buckets in the security team's project.

Create a job that copies the System Event logs from the _Required log bucket into the security team's log bucket in their project.

Create a job that copies the togs from the _Required log bucket into the security team's log bucket in their project.

Google Professional Cloud Developer Practice Test 7 - Free Online Exam Questions 241-265

You have deployed a Java application to Cloud Run. Your application requires access to a database hosted on Cloud SQL Due to regulatory requirements: your connection to the Cloud SQL instance must use its internal IP address. How should you configure the connectivity while following Google-recommended best practices'?

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