Use Google Cloud-Digital-Leader Dumps To Succeed Instantly in Cloud-Digital-Leader Exam [Q56-Q77]

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Use Google Cloud-Digital-Leader Dumps To Succeed Instantly in Cloud-Digital-Leader Exam

Ultimate Guide to Cloud-Digital-Leader Dumps – Enhance Your Future Career Now

Google Cloud Digital Leader exam covers a broad range of topics, including cloud computing fundamentals, Google Cloud Platform services, data analytics, machine learning, and artificial intelligence. Cloud-Digital-Leader exam also assesses a candidate’s knowledge of Google Cloud’s security and compliance features, as well as their ability to develop and implement a digital transformation strategy that aligns with their organization’s business objectives.

Q56. A customer in the European Union region is very clear that their data should not go outside the Eu-ropean Union. Their end users are spread all over the European U. They have to choose a storage option that serves all the users within Asia via web browsers as quickly as possible. Which storage option will work for them?

Cloud Storage with a single region that is known to be within the European U

Cloud Filestore is connected to virtual machines which are guaranteed to be within the European U

Cloud Storage with the multi-region option of European U

Cloud Storage with the dual-region option of European U

Explanation
Multi-region option will use multiple datacenters that are within the European Union. More regions will also help with lower latency since users are spread across the European U.
https://cloud.google.com/storage/docs/locations#considerations

Q57. Your organization is developing a plan for migrating to Google Cloud.
What is a best practice when initially configuring your Google Cloud environment?

Create a project via Google Cloud Console per department in your company

Define your resource hierarchy with an organization node on top

Create projects based on tem members’ requests

Make every member of your company the project owner

Q58. A partner of yours used to have their own private data center. Your company was already on Google Cloud and now they have also moved to Google Cloud. You are investigating whether there are ways to collaborate better or shared services. What would be one good option to consider?

Use Private Service Access within Google Cloud.

Use VPC Peering to share resources privately between your two organizations.

Use public IP addresses as before. It will automatically be routed internally only.

Use VPC Shared Networks to share common resources.

Explanation
VPC Network Peering allows internal IP address connectivity across two Virtual Private Cloud (VPC) networks regardless of whether they belong to the same project or the same organization.
-> Shared VPC is only within an organization – it allows an organization to connect resources from multiple projects to a common Virtual Private Cloud (VPC) network, so that they can communicate with each other securely and efficiently using internal IPs from that network.
-> Private Google Access is only to access Google APIs and services
References:
-> https://cloud.google.com/vpc/docs/vpc-peering
-> https://cloud.google.com/vpc/docs/private-google-access
-> https://cloud.google.com/vpc/docs/shared-vpc

Q59. You are a DevOps Engineer in an E-commerce company that sells products globally, across the countries, Customers buy products, add them to carts or check-in stock from different parts of the world with different timestamps, you need to choose a database that can scale globally without any hassle and lots of developer support, it should be consistent across regions, can scale horizontally to support enormous user, automatically replicates, shards and even auto transaction pro-cessing. Which of the following database do you choose?

Cloud SQL

Cloud Spanner

Cloud Firestore.

Cloud Storage.

Cloud Spanner:
Fully managed relational database with unlimited scale, strong consistency, and up to 99.999% availability.
– Get all the benefits of relational semantics and SQL with unlimited scale
– Start at any size and scale with no limits as your needs grow
– Enjoy high availability with zero scheduled downtime and online schema changes
– Deliver high-performance transactions with strong consistency across regions and continents
– Focus on innovation, eliminating manual tasks with capabilities like automatic sharding Automatic sharding Cloud Spanner optimizes performance by automatically sharding the data based on request load and size of the data. As a result, you can spend less time worrying about how to scale your database and instead focus on scaling your business.
Strong transactional consistency
Purpose-built for external, strong, global transactional consistency.
Regional and multi-regional configurations
No matter where your users may be, apps backed by Cloud Spanner can read and write up-to-date strongly consistent data globally Additionally, when running a multi-region instance, your database is able to survive a regional failure, and offers industry-leading 99.999% availability.
Online schema changes with no downtime
Cloud Spanner users can make a schema change, whether it’s adding a column or adding an index while serving traffic with zero downtime. Hence you now have the flexibility to adapt your database to your business needs without compromising on the availability of your application.

Q60. Your organization wants to migrate its data management solutions to Google Cloud because it needs to dynamically scale up or down and to run transactional SQL queries against historical data at scale. Which Google Cloud product or service should your organization use?

BigQuery

Cloud Bigtable

Pub/Sub

Cloud Spanner

Reference:
Cloud Spanner is a fully-managed, mission-critical relational database service. It is designed to provide a scalable online transaction processing (OLTP) database with high availability and strong consistency at global scale

Q61. Which of the following NIST Cloud characteristics uses the business model of shared re-sources in a cloud environment?

Elasticity

Availability

Broad Network Access

Multi-Tenancy

Explanation
In cloud computing, multitenancy means that multiple customers of a cloud vendor are using the same computing resources. Even though they share resources, cloud customers aren’t aware of each other, and their data is kept totally separate. Mul-titenancy is a crucial component of cloud computing; without it, cloud services would be far less practical. Multitenant architecture is a feature in many types of public cloud com-puting, including IaaS, PaaS, SaaS, containers, and serverless computing.

Q62. Your company needs to segment Google Cloud resources used by each team from the others. The teams’ efforts are changing frequently, and you need to reduce operational risk and maintain cost visibility. Which approach does Google recommend?

One project per team.

One organization per team.

One project that contains all of each team’s resources.

One top-level folder per team.

Q63. Your organization is developing an application that will manage payments and online bank accounts located around the world. The most critical requirement for your database is that each transaction is handled consistently. Your organization anticipates almost unlimited growth in the amount of data stored.
Which Google Cloud product should your organization choose?

Cloud SQL

Cloud Storage

Firestore

Cloud Spanner

Features of Cloud Spanner
Reference:

Q64. An organization wants to digitize and share large volumes of historical text and images.
Why is a public cloud a better option than an on-premises solution?

In-house hardware management

Provides physical encryption key

Cost-effective at scale

Optimizes capital expenditure

Q65. When an organization adopts cloud technology, how does their total cost of ownership (TCO) shift?

Away from cost management toward capital expenditure

Away from operational expenditure toward cost management

Away from capital expenditure toward operational expenditure

Away from operational expenditure toward capital expenditure

Q66. Which of the following statements is/are true about Google Cloud BigTable?

It is not compatible with Hadoop.

It Scales from Giga Byte to Peta Byte with No Downtime.

It can not be used in Real-time Ad analytics and tracking thousands of IoT Devices Data.

It is an enterprise-level Database that offers relational and non-relational features

Explanation
Cloud Bigtable
A fully managed, scalable NoSQL database service for large analytical and operational workloads with up to
99.999% availability.
– Consistent sub-10ms latency-handle millions of requests per second
– Ideal for use cases such as personalization, ad tech, fintech, digital media, and IoT
– Seamlessly scale to match your storage needs; no downtime during reconfiguration
– Designed with a storage engine for machine learning applications leading to better predictions
– Easily connect to Google Cloud services such as BigQuery or the Apache ecosystem

Q67. Your company provides car maintenance services. It is conducting an internal hackathon to identify new ideas that could expand their business. The teams have pitched different ideas and have started working on it. They have to present their application to the judges within 48 hours. A presentation alone is not enough; they have to demonstrate a working proof of concept. The team that you are mentoring is going to recommend additional ser-vices to drive in customers based on the brand of car they drive in. They need to be able to identify what brand of car the customer has, based on a photograph automatically taken at entry. They have already discovered an open source database of car images collected by online enthusiasts. How should they implement this solution?

Use Deep Learning Containers that are preconfigured and optimized containers for deep learning environments.

Use AutoML Image – upload the images and let it create a working model for you.

Use TensorFlow to create a model that will identify the car brands; use the available data to train the model.

Use Cloud Vision AI that is able to detect logos. Write only the code to integrate in-to your workflow.

Explanation
It would be most straightforward to use AutoML Image. Put the images in Cloud Storage, point to it from AutoML, and start the model building process.
Reference Link- https://cloud.google.com/automl

Q68. You are a program manager for a team of developers who are building an event-driven application to allow users to follow one another’s activities in the app. Each time a user adds himself as a follower of another user, a write occurs in the real-time database.
The developers will develop a lightweight piece of code that can respond to database writes and generate a notification to let the appropriate users know that they have gained new followers. The code should integrate with other cloud services such as Pub/Sub, Firebase, and Cloud APIs to streamline the orchestration process. The application requires a platform that automatically manages underlying infrastructure and scales to zero when there is no activity.
Which primary compute resource should your developers select, given these requirements?

Google Kubernetes Engine

Cloud Functions

App Engine flexible environment

Compute Engine

Reference:

Q69. An organization needs a platform to create custom end-to-end artificial intelligence models.
Which Google Cloud product or service should the organization use?

Dataproc

Compute Engine

Recommendations AI

Vertex AI

Recommendations AI enables you to build an end-to-end personalized recommendation system based on state-of-the-art deep learning ML models, without a need for expertise in ML or recommendation systems. With Vertex AI, both AutoML training and custom training are available options. Whichever option you choose for training, you can save models, deploy models, and request predictions with Vertex AI.
https://cloud.google.com/vertex-ai

Q70. Your organization needs to allow a production job to have access to a BigQuery dataset. The production job is running on a Compute Engine instance that is part of an instance group.
What should be included in the IAM Policy on the BigQuery dataset?

The Compute Engine instance group

The project that owns the Compute Engine instance

The Compute Engine service account

The Compute Engine instance

When an identity calls a Google Cloud API, BigQuery requires that the identity has the appropriate permissions to use the resource. You can grant permissions by granting roles to a user, a group, or a service account.
Reference link- https://cloud.google.com/bigquery/docs/access-control

Q71. A Customer has their current SAP systems using Microsoft SQL Server as the Database. They are migrating to Google Cloud and also preparing to later migrate to the latest ver-sion of SAP. The entire IT team is being directed to focus on the migration to the new ver-sion of SAP. The new version of SAP does not use Microsoft SQL Server as the Database, Any but the most critical IT management tasks are being deprioritized, How should they migrate their current database to Google Cloud?

Spanner

Bare Metal

BigQuery

Cloud SQL

Cloud SQL supports SQL Server, Since the IT team’s attention is being focused on other activities, they will have less time for existing admin tasks, It would be best to take a managed/hosted version.

Q72. Each of the three cloud service models – infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) – offers benefits between flexibility and levels of management by the cloud provider and the customer.
Why would SaaS be the right choice of service model?

You want a balance between flexibility for the customer and the level of management by the cloud provider

You want to minimize the level of management by the customer

You want to maximize flexibility for the customer.

You want to be able to shift your emphasis between flexibility and management by the cloud provider as business needs change

Benefits of SaaS
The main benefit of SaaS is that it offloads all infrastructure and application management to the SaaS vendor.

Q73. Customer Managed Encryption Keys (CMEK) can be used for encrypting data inside Cloud BigTable, which of the following statements is/are correct. (Select two answer)

Administrators can not rotate

Not supported for instances that have clustered in more than one region.

CMEK can only be configured at the cluster level.

You can not use the same CMEK key in multiple projects

Explanation
Customer-managed encryption keys for Cloud BigTable.
By default, all the data at rest in Cloud Bigtable is encrypted using Google’s default encryption. Bigtable handles and manages this encryption for you without any additional action on your part.
If you have specific compliance or regulatory requirements related to the keys that protect your data, you can use customer-managed encryption keys (CMEK) for BigTable. Instead of Google managing the encryption keys that protect your data, your BigTable instance is protected using a key that you control and manage in Cloud Key Management Service (Cloud KMS).
Features
Security: CMEK provides the same level of security as Google’s default encryption but provides more administrative control.
Data access control: Administrators can rotate, manage access to, and disable or destroy the key used to protect data at rest in BigTable .
Auditability: All actions on your CMEK keys are logged and viewable in Cloud Logging.
Comparable performance: BigTable CMEK-protected instances offer comparable performance to BigTable instances that use Google default encryption.
Flexibility: You can use the same CMEK key in multiple projects or instances or you can use separate keys, depending on your business needs.

Q74. After rolling out a new update, an organization found a minor bug in its online video game.
How should the organization approach this bug while following SRE principles?

Accept and learn from the bug because failure is normal

Accept and ignore the bug because it is only minor

Hold a postmortem to reprimand the employee responsible for the bug

Document bug correction to eliminate all future bugs

Explanation
https://www.blameless.com/sre/sre-principles
Accepting failure as normal is one of the SRE principles. SREs believe that accepting failure as normal helps to build an iterative, collaborative culture. One way this is done is by holding a blameless “lessons learned” discussion after an incident occurs.

Q75. Customer Managed Encryption Keys (CMEK) can be used for encrypting data inside Cloud BigTable, which of the following statements is/are correct. (Select two answer)

Administrators can not rotate

Not supported for instances that have clustered in more than one region.

CMEK can only be configured at the cluster level.

You can not use the same CMEK key in multiple projects

Customer-managed encryption keys for Cloud BigTable.
By default, all the data at rest in Cloud Bigtable is encrypted using Google’s default encryption. Bigtable handles and manages this encryption for you without any additional action on your part.
If you have specific compliance or regulatory requirements related to the keys that protect your data, you can use customer-managed encryption keys (CMEK) for BigTable. Instead of Google managing the encryption keys that protect your data, your BigTable instance is protected using a key that you control and manage in Cloud Key Management Service (Cloud KMS).
Features
Security: CMEK provides the same level of security as Google’s default encryption but provides more administrative control.
Data access control: Administrators can rotate, manage access to, and disable or destroy the key used to protect data at rest in BigTable .
Auditability: All actions on your CMEK keys are logged and viewable in Cloud Logging.
Comparable performance: BigTable CMEK-protected instances offer comparable performance to BigTable instances that use Google default encryption.
Flexibility: You can use the same CMEK key in multiple projects or instances or you can use separate keys, depending on your business needs.

Q76. Your organization runs many workloads in different Google Cloud projects, each linked to the same billing account. Each project’s workload costs can vary from month to month, but the overall combined cost of all projects is relatively stable. Your organization needs to optimize its cost.
What should your organization do?

Purchase a commitment per project for each project’s usual minimum

Create a billing account per project, and link each project to a different billing account

Turn on committed use discount sharing, and create a commitment for the combined usage

Move all workloads from all different projects into one single consolidated project

Explanation
Turn on committed use discount sharing, and create a commitment for the combined usage Sharing your committed use discounts across all your projects reduces the overhead of managing discounts on a per-project basis, and maximizes your savings by pooling all your discounts across your projects’ resource usage. If you have multiple projects that share the same Cloud Billing account, you can enable committed use discount sharing so all of your projects within that Cloud Billing account share all of your committed use discount contracts. Your sustained use discounts are also pooled at the same time. That is, sustained use discounts are calculated using the total resources across these projects, rather than just the resources within a single project.
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Reference link
– https://cloud.google.com/compute/docs/instances/signing-up-committed-use-discounts#sharing_committed_use

Q77. A large organization is struggling to manage their cloud costs effectively. They want to increase vis-ibility into cloud costs. Which cost management approach should the organization use?

Establish a partnership between finance, technology, and business teams.

Appoint a single person to monitor cloud spending across the organization.

Review any cloud spending that exceeds the organization’s error budget.

Increase monitoring of on-premises infrastructure and services.

Explanation
Because cross-team partnerships are part of the visibility cost management strategy.
https://wa.aws.amazon.com/wat.question.COST_1.en.html

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