Win IT Exam with Last Dumps 2025

You are working on a new application that is deployed on Cloud Run and uses Cloud Functions. Each time new features are added, new Cloud Functions and Cloud Run services are deployed. You use ENV variables to keep track of the services and enable interservice communication, but the maintenance of the ENV variables has become difficult. You want to implement dynamic discovery in a scalable way. What should you do?

A. Configure your microservices to use the Cloud Run Admin and Cloud Functions APIs to query for deployed Cloud Run services and Cloud Functions in the Google Cloud project. B. Create a Service Directory namespace. Use API calls to register the services during deployment, and query during runtime. C. Rename the Cloud Functions and Cloud Run services endpoint is using a well-documented naming convention. D. Deploy Hashicorp Consul on a single Compute Engine instance. Register the services with Consul during deployment, and query during runtime.

You work for a financial services company that has a container-first approach. Your team develops microservices applications. A Cloud Build pipeline creates the container image, runs regression tests, and publishes the image to Artifact Registry. You need to ensure that only containers that have passed the regression tests are deployed to Google Kubernetes Engine (GKE) clusters. You have already enabled Binary Authorization on the GKE clusters. What should you do next?

A. Create an attestor and a policy. After a container image has successfully passed the regression tests, use Cloud Build to run Kritis Signer to create an attestation for the container image. B. Deploy Voucher Server and Voucher Client components. After a container image has successfully passed the regression tests, run Voucher Client as a step in the Cloud Build pipeline. C. Set the Pod Security Standard level to Restricted for the relevant namespaces. Use Cloud Build to digitally sign the container images that have passed the regression tests. D. Create an attestor and a policy. Create an attestation for the container images that have passed the regression tests as a step in the Cloud Build pipeline.

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?

A. Enable Binary Authorization, and configure it to attest that no vulnerabilities exist in a container image. B. Upload the built container images to your Docker Hub instance, and scan them for vulnerabilities. C. Enable the Container Scanning API in Artifact Registry, and scan the built container images for vulnerabilities. D. Add Artifact Registry to your Aqua Security instance, and scan the built container images for vulnerabilities.

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 do?

A. Configure GKE workload metrics using kubectl. 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. B. Update your microservices to log HTTP request methods and URL paths to STDOUT. Use the logs router to send container logs to Cloud Logging. Create filters in Cloud Logging to evaluate the latency of user requests across different methods and URL paths. C. Instrument your microservices by installing the OpenTelemetry 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. D. Install tcpdump on your GKE nodes. Run tcpdump 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.

You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests. Your load tests must meet the following requirements:
• Load is initiated from multiple parallel threads.
• User traffic to the API originates from multiple source IP addresses.
• Load can be scaled up using additional test instances.
You want to follow Google-recommended best practices. How should you configure the load testing?

A. Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in a managed instance group, and run one instance of the image for each VM. B. Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in an unmanaged instance group, and run one instance of the image for each VM. C. Deploy a distributed load testing framework on a private Google Kubernetes Engine cluster. Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users. D. Download the container image of a distributed load testing framework on Cloud Shell. Sequentially start several instances of the container on Cloud Shell to increase the load on the API.

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?

A. Enforce signed URLs for the desired bucket. Grant the Storage Object Viewer IAM role on the bucket to the Compute Engine default service account. B. 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. C. 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. D. 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 using Cloud Run to host a global ecommerce web application. Your company’s design team is creating a new color scheme for the web app. You have been tasked with determining whether the new color scheme will increase sales. You want to conduct testing on live production traffic. How should you design the study?

A. Use an external HTTP(S) load balancer to route a predetermined percentage of traffic to two different color schemes of your application. Analyze the results to determine whether there is a statistically significant difference in sales. B. Use an external HTTP(S) load balancer to route traffic to the original color scheme while the new deployment is created and tested. After testing is complete, reroute all traffic to the new color scheme. Analyze the results to determine whether there is a statistically significant difference in sales. C. Use an external HTTP(S) load balancer to mirror traffic to the new version of your application. Analyze the results to determine whether there is a statistically significant difference in sales. D. Enable a feature flag that displays the new color scheme to half of all users. Monitor sales to see whether they increase for this group of users.

You are a developer at a large corporation. You manage three Google Kubernetes Engine clusters on Google Cloud. 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 multiple clusters while following Google-recommended best practices. What should you do?

A. Ask the developers to use Cloud Shell and run gcloud container clusters get-credential to switch to another cluster. B. In a configuration file, define the clusters, users, and contexts. Share the file with the developers and ask them to use kubect1 contig to add cluster, user, and context details. C. Ask the developers to install the gcloud CLI on their workstation and run gcloud container clusters get-credentials to switch to another cluster. D. Ask the developers to open three terminals on their workstation and use kubect1 config to configure access to each cluster.

You are a lead developer working on a new retail system that runs on Cloud Run and Firestore. A web UI requirement is for the user to be able to browse through all products. A few months after go-live, you notice that Cloud Run instances are terminated with HTTP 500: Container instances are exceeding memory limits errors during busy times. This error coincides with spikes in the number of Firestore queries.
You need to prevent Cloud Run from crashing and decrease the number of Firestore queries. You want to use a solution that optimizes system performance. What should you do?

A. Modify the query that returns the product list using cursors with limits. B. Create a custom index over the products. C. Modify the query that returns the product list using integer offsets. D. Modify the Cloud Run configuration to increase the memory limits.

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 group of developers copies the repository, commits their changes to their repository, and merges their code into the main repository before each product release. C. Each developer creates a branch for their own work, commits their changes to their branch, and merges their code into the main branch daily. D. 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.