Attested Professional-Cloud-DevOps-Engineer Dumps PDF Resource [2023]
Latest Professional-Cloud-DevOps-Engineer Actual Free Exam Questions Updated 164 Questions
NEW QUESTION # 16
Your Cloud Run application writes unstructured logs as text strings to Cloud Logging. You want to convert the unstructured logs to JSON-based structured logs. What should you do?
- A. Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPay10ad field.
- B. Install the log agent in the Cloud Run container image, and use the log agent to forward logs to Cloud Logging.
- C. A Install a Fluent Bit sidecar container, and use a JSON parser.
- D. Configure the log agent to convert log text payload to JSON payload.
Answer: A
Explanation:
Explanation
The correct answer is D. Modify the application to use Cloud Logging software development kit (SDK), and send log entries with a jsonPayload field.
Cloud Logging SDKs are libraries that allow you to write structured logs from your Cloud Run application.
You can use the SDKs to create log entries with a jsonPayload field, which contains a JSON object with the properties of your log entry. The jsonPayload field allows you to use advanced features of Cloud Logging, such as filtering, querying, and exporting logs based on the properties of your log entry1.
To use Cloud Logging SDKs, you need to install the SDK for your programming language, and then use the SDK methods to create and send log entries to Cloud Logging. For example, if you are using Node.js, you can use the following code to write a structured log entry with a jsonPayload field2:
// Imports the Google Cloud client library
const {Logging} = require('@google-cloud/logging');
// Creates a client
const logging = new Logging();
// Selects the log to write to
const log = logging.log('my-log');
// The data to write to the log
const text = 'Hello, world!';
const metadata = {
// Set the Cloud Run service name and revision as labels
labels: {
service_name: process.env.K_SERVICE || 'unknown',
revision_name: process.env.K_REVISION || 'unknown',
},
// Set the log entry payload type and value
jsonPayload: {
message: text,
timestamp: new Date(),
},
};
// Prepares a log entry
const entry = log.entry(metadata);
// Writes the log entry
await log.write(entry);
console.log(`Logged: ${text}`);
Using Cloud Logging SDKs is the best way to convert unstructured logs to structured logs, as it provides more flexibility and control over the format and content of your log entries.
Using a Fluent Bit sidecar container is not a good option, as it adds complexity and overhead to your Cloud Run application. Fluent Bit is a lightweight log processor and forwarder that can be used to collect and parse logs from various sources and send them to different destinations3. However, Cloud Run does not support sidecar containers, so you would need to run Fluent Bit as part of your main container image. This would require modifying your Dockerfile and configuring Fluent Bit to read logs from supported locations and parse them as JSON. This is more cumbersome and less reliable than using Cloud Logging SDKs.
Using the log agent in the Cloud Run container image is not possible, as the log agent is not supported on Cloud Run. The log agent is a service that runs on Compute Engine or Google Kubernetes Engine instances and collects logs from various applications and system components. However, Cloud Run does not allow you to install or run any agents on its underlying infrastructure, as it is a fully managed service that abstracts away the details of the underlying platform.
Storing the password directly in the code is not a good practice, as it exposes sensitive information and makes it hard to change or rotate the password. It also requires rebuilding and redeploying the application each time the password changes, which adds unnecessary work and downtime.
References:
1: Writing structured logs | Cloud Run Documentation | Google Cloud
2: Write structured logs | Cloud Run Documentation | Google Cloud
3: Fluent Bit - Fast and Lightweight Log Processor & Forwarder
Logging Best Practices for Serverless Applications - Google Codelabs
About the logging agent | Cloud Logging Documentation | Google Cloud
Cloud Run FAQ | Google Cloud
NEW QUESTION # 17
You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?
- A. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.
- B. Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.
- C. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
- D. Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.
Answer: D
NEW QUESTION # 18
Your organization wants to increase the availability target of an application from 99 9% to 99 99% for an investment of $2 000 The application's current revenue is S1,000,000 You need to determine whether the increase in availability is worth the investment for a single year of usage What should you do?
- A. Calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment
- B. Calculate the value of improved availability to be $1 000 and determine that the increase in availability is worth the investment
- C. Calculate the value of improved availability to be $9,000. and determine that the increase in availability is worth the investment
- D. Calculate the value of improved availability to be $1 000 and determine that the increase in availability is not worth the investment
Answer: A
Explanation:
Explanation
The best option for determining whether the increase in availability is worth the investment for a single year of usage is to calculate the value of improved availability to be $900, and determine that the increase in availability is not worth the investment. To calculate the value of improved availability, we can use the following formula:
Value of improved availability = Revenue * (New availability - Current availability) Plugging in the given numbers, we get:
Value of improved availability = $1,000,000 * (0.9999 - 0.999) = $900
Since the value of improved availability is less than the investment of $2,000, we can conclude that the increase in availability is not worth the investment.
NEW QUESTION # 19
Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?
- A. MTTD:5
MTTR: 10
MTBF: 90
Impact 50% - B. MTTD:5
MTTR: 20
MTBF: 90
Impact: 50% - C. MTTD:5
MTTR: 20
MTBF: 90
Impact: 33% - D. MTTD: 5
MTTR: 10
MTBF: 90
Impact: 33%
Answer: C
Explanation:
https://www.atlassian.com/incident-management/kpis/common-metrics
https://linkedin.github.io/school-of-sre/
NEW QUESTION # 20
You support a high-traffic web application with a microservice architecture. The home page of the application displays multiple widgets containing content such as the current weather, stock prices, and news headlines. The main serving thread makes a call to a dedicated microservice for each widget and then lays out the homepage for the user. The microservices occasionally fail; when that happens, the serving thread serves the homepage with some missing content. Users of the application are unhappy if this degraded mode occurs too frequently, but they would rather have some content served instead of no content at all. You want to set a Service Level Objective (SLO) to ensure that the user experience does not degrade too much. What Service Level Indicator {SLI) should you use to measure this?
- A. A latency SLI: the ratio of microservice calls that complete in under 100 ms to the total number of microservice calls
- B. A freshness SLI: the proportion of widgets that have been updated within the last 10 minutes
- C. An availability SLI: the ratio of healthy microservices to the total number of microservices
- D. A quality SLI: the ratio of non-degraded responses to total responses
Answer: C
Explanation:
https://cloud.google.com/blog/products/gcp/available-or-not-that-is-the-question-cre-life-lessons
NEW QUESTION # 21
You are deploying an application that needs to access sensitive information. You need to ensure that this information is encrypted and the risk of exposure is minimal if a breach occurs. What should you do?
- A. Inject the secret at the time of instance creation via an encrypted configuration management system.
- B. Leverage a continuous build pipeline that produces multiple versions of the secret for each instance of the application.
- C. Integrate the application with a Single sign-on (SSO) system and do not expose secrets to the application
- D. Store the encryption keys in Cloud Key Management Service (KMS) and rotate the keys frequently
Answer: D
Explanation:
Explanation
https://cloud.google.com/security-key-management
NEW QUESTION # 22
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub.
You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?
- A. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
- B. Disable the CI pipeline and revert to manually building and pushing the artifacts.
- C. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
- D. Change the CI pipeline to push the artifacts is Container Registry instead of Docker Hub.
Answer: D
NEW QUESTION # 23
You are part of an organization that follows SRE practices and principles. You are taking over the management of a new service from the Development Team, and you conduct a Production Readiness Review (PRR). After the PRR analysis phase, you determine that the service cannot currently meet its Service Level Objectives (SLOs). You want to ensure that the service can meet its SLOs in production. What should you do next?
- A. Identify recommended reliability improvements to the service to be completed before handover.
- B. Notify the development team that they will have to provide production support for the service.
- C. Adjust the SLO targets to be achievable by the service so you can bring it into production.
- D. Bring the service into production with no SLOs and build them when you have collected operational data.
Answer: B
NEW QUESTION # 24
You are working with a government agency that requires you to archive application logs for seven years. You need to configure Stackdriver to export and store the logs while minimizing costs of storage. What should you do?
- A. Develop an App Engine application that pulls the logs from Stackdriver and saves them in BigQuery.
- B. Create a Cloud Storage bucket and develop your application to send logs directly to the bucket.
- C. Create an export in Stackdriver and configure Cloud Pub/Sub to store logs in permanent storage for seven years.
- D. Create a sink in Stackdriver, name it, create a bucket on Cloud Storage for storing archived logs, and then select the bucket as the log export destination.
Answer: D
Explanation:
https://cloud.google.com/logging/docs/routing/overview
NEW QUESTION # 25
You need to reduce the cost of virtual machines (VM| for your organization. After reviewing different options, you decide to leverage preemptible VM instances. Which application is suitable for preemptible VMs?
- A. The organization's public-facing website
- B. A scalable in-memory caching system
- C. A GPU-accelerated video rendering platform that retrieves and stores videos in a storage bucket
- D. A distributed, eventually consistent NoSQL database cluster with sufficient quorum
Answer: C
Explanation:
Explanation
https://cloud.google.com/compute/docs/instances/preemptible
NEW QUESTION # 26
You have a pool of application servers running on Compute Engine. You need to provide a secure solution that requires the least amount of configuration and allows developers to easily access application logs for troubleshooting. How would you implement the solution on GCP?
- A. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Viewer role to access Stackdriver and view logs. - B. * Deploy the Stackdriver logging agent to the application servers.
* Give the developers the IAM Logs Private Logs Viewer role to access Stackdriver and view logs. - C. * Deploy the Stackdriver monitoring agent to the application servers.
* Give the developers the IAM Monitoring Viewer role to access Stackdriver and view metrics. - D. * Install the gsutil command line tool on your application servers.
* Write a script using gsutil to upload your application log to a Cloud Storage bucket, and then schedule it to run via cron every 5 minutes.
Answer: A
Explanation:
* Give the developers IAM Object Viewer access to view the logs in the specified bucket.
Explanation:
https://cloud.google.com/logging/docs/audit#access-control
NEW QUESTION # 27
You are running a web application deployed to a Compute Engine managed instance group Ops Agent is installed on all instances You recently noticed suspicious activity from a specific IP address You need to configure Cloud Monitoring to view the number of requests from that specific IP address with minimal operational overhead. What should you do?
- A. Configure the Ops Agent with a logging receiver Create a logs-based metric
- B. Update the application to export the IP address request metrics to the Cloud Monitoring API
- C. Create a script to scrape the web server log Export the IP address request metrics to the Cloud Monitoring API
- D. Configure the Ops Agent with a metrics receiver
Answer: A
Explanation:
Explanation
The best option for configuring Cloud Monitoring to view the number of requests from a specific IP address with minimal operational overhead is to configure the Ops Agent with a logging receiver and create a logs-based metric. The Ops Agent is an agent that collects system metrics and logs from your VM instances and sends them to Cloud Monitoring and Cloud Logging. A logging receiver is a configuration that specifies which logs are collected by the Ops Agent and how they are processed. You can use a logging receiver to collect web server logs from your VM instances and send them to Cloud Logging. A logs-based metric is a metric that is extracted from log entries in Cloud Logging. You can use a logs-based metric to count the number of requests from a specific IP address by using a filter expression. You can then use Cloud Monitoring to view and analyze the logs-based metric.
NEW QUESTION # 28
You use Spinnaker to deploy your application and have created a canary deployment stage in the pipeline.
Your application has an in-memory cache that loads objects at start time. You want to automate the comparison of the canary version against the production version. How should you configure the canary analysis?
- A. Compare the canary with the average performance of a sliding window of previous production versions.
- B. Compare the canary with a new deployment of the current production version.
- C. Compare the canary with a new deployment of the previous production version.
- D. Compare the canary with the existing deployment of the current production version.
Answer: B
Explanation:
Explanation
https://cloud.google.com/architecture/automated-canary-analysis-kubernetes-engine-spinnaker
https://spinnaker.io/guides/user/canary/best-practices/#compare-canary-against-baseline-not-against-production
NEW QUESTION # 29
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to- share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?
- A. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
3. Build the dashboards in the SIEM system and share with your stakeholders. - B. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
2. Enable the Cloud Storage API to pull the logs programmatically.
3. Build a custom data visualization application.
4. Display the pulled logs in a custom dashboard. - C. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. From BigQuery, export the logs to a CSV file.
3. Import the CSV file into Google Sheets.
4. Build a dashboard in Google Sheets and share it with your stakeholders. - D. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. Create a dashboard in Data Studio.
3. Share the dashboard with your stakeholders.
Answer: D
NEW QUESTION # 30
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers
- A. Your application servers' logs
- B. A synthetic client that periodically sends simulated user requests
- C. Metrics exported from the application servers
- D. Instrumentation coded directly in the client
- E. GKE health checks for your application servers
Answer: C,E
NEW QUESTION # 31
You use Cloud Build to build your application. You want to reduce the build time while minimizing cost and development effort. What should you do?
- A. Use larger Cloud Build virtual machines (VMs) by using the machine-type option.
- B. Use multiple smaller build steps to minimize execution time.
- C. Use Cloud Storage to cache intermediate artifacts.
- D. Run multiple Jenkins agents to parallelize the build.
Answer: B
Explanation:
Explanation
https://cloud.google.com/storage/docs/best-practices
https://cloud.google.com/build/docs/speeding-up-builds#caching_directories_with_google_cloud_storage Caching directories with Google Cloud Storage To increase the speed of a build, reuse the results from a previous build. You can copy the results of a previous build to a Google Cloud Storage bucket, use the results for faster calculation, and then copy the new results back to the bucket. Use this method when your build takes a long time and produces a small number of files that does not take time to copy to and from Google Cloud Storage.
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NEW QUESTION # 32
Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?
- A. Expose the NGINX stats endpoint and configure the horizontal pod autoscaler to use the request metrics exposed by the NGINX deployment.
- B. Install the Stackdriver custom metrics adapter and configure a horizontal pod autoscaler to use the number of requests provided by the GCLB.
- C. Configure the vertical pod autoscaler in GKE and enable the cluster autoscaler to scale the cluster as pods expand.
- D. Configure the horizontal pod autoscaler to use the average response time from the Liveness and Readiness probes.
Answer: B
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/tutorials/autoscaling-metrics The Google Cloud HTTP Load Balancer (GCLB) provides metrics on the number of requests and the response latency for each backend service. These metrics can be used as custom metrics for the horizontal pod autoscaler (HPA) to scale the deployment based on the load. This is the correct solution to use an appropriate SLI for scaling.
NEW QUESTION # 33
Your application artifacts are being built and deployed via a CI/CD pipeline. You want the CI/CD pipeline to securely access application secrets. You also want to more easily rotate secrets in case of a security breach. What should you do?
- A. Prompt developers for secrets at build time. Instruct developers to not store secrets at rest.
- B. Store secrets in Cloud Storage encrypted with a key from Cloud KMS. Provide the CI/CD pipeline with access to Cloud KMS via IAM.
- C. Store secrets in a separate configuration file on Git. Provide select developers with access to the configuration file.
- D. Encrypt the secrets and store them in the source code repository. Store a decryption key in a separate repository and grant your pipeline access to it
Answer: C
NEW QUESTION # 34
You use a multiple step Cloud Build pipeline to build and deploy your application to Google Kubernetes Engine (GKE). You want to integrate with a third-party monitoring platform by performing a HTTP POST of the build information to a webhook. You want to minimize the development effort. What should you do?
- A. Add a new step at the end of the pipeline in Cloud Build to HTTP POST the build information to a webhook.
- B. Create a Cloud Pub/Sub push subscription to the Cloud Build cloud-builds PubSub topic to HTTP POST the build information to a webhook.
- C. Use Stackdriver Logging to create a logs-based metric from the Cloud Buitd logs. Create an Alert with a Webhook notification type.
- D. Add logic to each Cloud Build step to HTTP POST the build information to a webhook.
Answer: A
NEW QUESTION # 35
You are performing a semi-annual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP), using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?
- A. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough.
- B. Verify the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verify your expected resource needs.
- C. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
- D. Because you are deployed on GKE and are using a cluster autoscaler, your GKE cluster will scale automatically regardless of growth rate.
Answer: D
NEW QUESTION # 36
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?
- A. Specify the Container Developer role for Cloud Build in the cloudbuild.yaml file.
- B. Create a new service account with the Container Developer role and use it to run Cloud Build.
- C. Create a separate step in Cloud Build to retrieve service account credentials and pass these to kubectl.
- D. Assign the Container Developer role to the Cloud Build service account.
Answer: D
NEW QUESTION # 37
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (PII) is leaking into certain log entry fields. You want to prevent these fields from being written in new log entries as quickly as possible. What should you do?
- A. Stage log entries to Cloud Storage, and then trigger a Cloud Function to remove the fields and write the entries to Stackdriver via the Stackdriver Logging API.
- B. Use the fluent-plugin-record-reformer Fluentd output plugin to remove the fields from the log entries in flight.
- C. Wait for the application developers to patch the application, and then verify that the log entries are no longer exposing PII.
- D. Use the filter-record-transformer Fluentd filter plugin to remove the fields from the log entries in flight.
Answer: B
NEW QUESTION # 38
You need to run a business-critical workload on a fixed set of Compute Engine instances for several months. The workload is stable with the exact amount of resources allocated to it. You want to lower the costs for this workload without any performance implications. What should you do?
- A. Convert the instances to preemptible virtual machines.
- B. Purchase Committed Use Discounts.
- C. Create an Unmanaged Instance Group for the instances used to run the workload.
- D. Migrate the instances to a Managed Instance Group.
Answer: B
NEW QUESTION # 39
You are implementing a CI'CD pipeline for your application in your company s multi-cloud environment Your application is deployed by using custom Compute Engine images and the equivalent in other cloud providers You need to implement a solution that will enable you to build and deploy the images to your current environment and is adaptable to future changes Which solution stack should you use'?
- A. Google Kubernetes Engine with Google Cloud Deploy
- B. Cloud Build with kpt
- C. Cloud Build with Packer
- D. Cloud Build with Google Cloud Deploy
Answer: D
Explanation:
Explanation
Cloud Build is a fully managed continuous integration and continuous delivery (CI/CD) service that helps you automate your builds, tests, and deployments. Google Cloud Deploy is a service that automates the deployment of your applications to Google Kubernetes Engine (GKE).
Together, Cloud Build and Google Cloud Deploy can be used to build and deploy your application's custom Compute Engine images to your current environment and to other cloud providers in the future.
Here are the steps involved in using Cloud Build and Google Cloud Deploy to implement a CI/CD pipeline for your application:
Create a Cloud Build trigger that fires whenever a change is made to your application's code.
In the Cloud Build trigger, configure Cloud Build to build your application's Docker image.
Create a Google Cloud Deploy configuration file that specifies how to deploy your application's Docker image to GKE.
In Google Cloud Deploy, create a deployment that uses your configuration file.
Once you have created the Cloud Build trigger and Google Cloud Deploy configuration file, any changes made to your application's code will trigger Cloud Build to build a new Docker image. Google Cloud Deploy will then deploy the new Docker image to GKE.
This solution stack is adaptable to future changes because it uses a cloud-agnostic approach. Cloud Build can be used to build Docker images for any cloud provider, and Google Cloud Deploy can be used to deploy Docker images to any Kubernetes cluster.
The other solution stacks are not as adaptable to future changes. For example, solution stack A (Cloud Build with Packer) is limited to building Docker images for Compute Engine. Solution stack C (Google Kubernetes Engine with Google Cloud Deploy) is limited to deploying Docker images to GKE. Solution stack D (Cloud Build with kpt) is a newer solution that is not yet as mature as Cloud Build and Google Cloud Deploy.
Overall, the best solution stack for implementing a CI/CD pipeline for your application in a multi-cloud environment is Cloud Build with Google Cloud Deploy. This solution stack is fully managed, cloud-agnostic, and adaptable to future changes.
NEW QUESTION # 40
You support a high-traffic web application and want to ensure that the home page loads in a timely manner. As a first step, you decide to implement a Service Level Indicator (SLI) to represent home page request latency with an acceptable page load time set to 100 ms. What is the Google-recommended way of calculating this SLI?
- A. Bucketize the request latencies into ranges, and then compute the median and 90th percentiles.
- B. Count the number of home page requests that load in under 100 ms, and then divide by the total number of home page requests.
- C. Buckelize Ihe request latencies into ranges, and then compute the percentile at 100 ms.
- D. Count the number of home page requests that load in under 100 ms. and then divide by the total number of all web application requests.
Answer: C
NEW QUESTION # 41
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