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Free CLOUD-DIGITAL-LEADER Exam Braindumps (page: 39)

Page 38 of 104
PDF with 411 Questions

"With cloud messaging you can Customize and deliver messages accordingly to the predetermined time in the user's local time zone." Comment on the above statement.

  1. This statement is undefined.
  2. The above statement is partially true.
  3. The above statement is completely false.
  4. The above statement is completely true.

Answer(s): D

Explanation:

Firebase Cloud Messaging:

Firebase Cloud Messaging (FCM) is a cross-platform messaging solution that lets you reliably send messages at no cost.

Using FCM, you can notify a client app that new email or other data is available to sync. You can send notification messages to drive user re-engagement and retention. For use cases such as instant messaging, a message can transfer a payload of up to 4000 bytes to a client app.

Key capabilities of Firebase Cloud Messaging:

Send notification messages or data messages: Send notification messages that are displayed to your user. Or send data messages and determine completely what happens in your application code.

Versatile message targeting: Distribute messages to your client app in any of 3 ways--to single devices, to groups of devices, or to devices subscribed to topics.

Send messages from client apps: Send acknowledgments, chats, and other messages from devices back to your server over FCM's reliable and battery-efficient connection channel.



An e-commerce company's business has been booming. To keep up with the growth the IT team also grew. Many new people are being added and new resources are being set up. The CIO is in conver- sation with you over coffee one day and expresses her growing concern that they might be moving too fast. Their security checks and policies have not kept pace. She worries that somebody would make a misconfiguration or compliance violation thus exposing the company to data and privacy loss.
What can you advise her?

  1. Use Cloud Identity-Aware Proxy to allow only specific users to access the data.
  2. Use Security Command Center to have a centralized view of assets and get noti-fied on misconfigurations and vulnerabilities.
  3. Use Cloud Data Loss Prevention to prevent the loss of any data.
  4. Use Cloud Armor to block any DDoS attacks that could be a threat.

Answer(s): B

Explanation:

Security Command Center is the right tool for this use case. It can check resources for security issues and notify you when issues are found.

https://cloud.google.com/security-command-center



One of your clients is in the retail sector. They have a small team supporting their operations and a small development team taking care of application development. They have heard of the benefits of machine learning, but they do not have the capacity to hire data scientists or the work to retain them. They have a team of analysts who works primarily on BigQuery and knows how to run SQL queries. They want to be able to get into the new age of machine learning and artificial intelligence.
What options are available to run on Google Cloud?

  1. Use the popular open-source libraries SciPy and NumPy to create machine learn-ing models.
  2. Use the Unified AI Platform to create a custom TensorFlow model.
  3. Use BigQuery ML to create machine learning models using SQL queries.
  4. Integrate the Cloud Vision API and the Cloud Speech API to create a custom mod-el that will suit the retail sector.

Answer(s): C

Explanation:

BigQuery ML allows you to create ML models using standard SQL queries. Those familiar with BigQuery and ML will be able to create ML models with just a basic understanding of machine learning.

https://cloud.google.com/bigquery-ml/docs/



A customer has an application running in virtual machines. They are migrating this application to Google Cloud. They have previously had scaling issues when on-premises as VMs had to be pre- allocated. Capacity planning was repeatedly off mark - it's either too many VMs or too less. They want to match the capacity to demand while keeping the application running always. They don't have the time or budget to re-architect the systems using containers and Kubernetes at the mo- ment.
What would be your recommendation?

  1. Run a load test on Compute Engine VMs. Get an estimate of usage. Then plan for a VM capacity of 25% above the load test value.
  2. Use the Managed Instance Group with Compute Engine
  3. Inform them that new-age companies are using microservices, containers, and Kubernetes for this and they can plan to rewrite the app quickly.
  4. Inform them that using a serverless option will take care of the scaling and they can move to Cloud Run or App Engine.

Answer(s): B

Explanation:

Scalability.
When your apps require additional compute resources, autoscaled MIGs can automatically grow the number of instances in the group to meet demand. If demand drops,

autoscaled MIGs can automatically shrink to reduce your costs



https://cloud.google.com/compute/docs/instance-groups






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