Cloud-Digital-Leader Google Cloud Digital Leader exam Question and Answers

This is the definition of a least privilege model.

A supporting principle that helps organizations achieve these goals is the principle of least privilege. The principle of least privilege addresses access control and states that an individual should have only the minimum access privileges necessary to perform a specific job or task and nothing more

BigQuery is the data warehousing option on Google Cloud. Since the source data has already been used for analysis, it should easily fit the BigQuery structure too.

The Bare Metal solution is the recommended approach. You can deploy Oracle capabilities like clustered databases, replication, and all performance features at licensing costs that are similar to on-premise systems

https://cloud.google.com/architecture/migrating-bare-metal-workloads

Logged information

Your Google Cloud projects contain only the audit logs for resources that are directly within the Cloud project. Other Google Cloud resources, such as folders, organizations, and billing accounts, contain the audit logs for the entity itself.

Reference link- https://cloud.google.com/storage/docs/audit-logging

To change the Cloud Billing account for a project, you need to be able to move a project from one Cloud Billing account to another. To accomplish this task, you need permissions adequate to unlink the project from the existing Cloud Billing account AND to link the project to the target Cloud Billing account. Roles with adequate permissions to perform this task: Project Owner or Project Billing Manager on the project, AND Billing Account Administrator or Billing Account User for the target Cloud Billing account

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Reference link- https://cloud.google.com/billing/docs/how-to/modify-

Service Level Agreement (SLA) 

A service level agreement (SLA) is a contract between a service provider (either internal or external) and the end user that defines the level of service expected from the service provider. Some common SLA’s are uptime, Response Time, etc.

Bucket names have to be unique across Google Cloud Platform [GCP], Including other organizations and projects.

Apigee includes analytics services which allow enterprises to report on various aspects of an API.

Containers and Kubernetes are ideal for the kind of requirement mentioned here - separate microservices that need to scale independently.

Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines (specifically, Compute Engine instances) grouped together to form a cluster.

Reference link- https://cloud.google.com/kubernetes-engine/docs/concepts/kubernetes-engine-overview

Cloud Datastore is the best for semi-structured application data that is used in app engines' applications. Bigtable is best for analytical data with heavy read/write events like AdTech, Financial or IoT data. Cloud Storage is best for structured and unstructured, binary or object data like images, large media files and backups. SQL is best for web frameworks and in existing applications like storing user credentials and customer orders. Cloud Spanner is best for large scale database applications that are larger than two terabytes; for example, for financial trading and e-commerce use cases. As I mentioned at the beginning of the module, depending on your application, you might use one or several of these services to get the job done.

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/

Comply with data security and privacy regulations in each geographical region For a multi-national corporation, they need to abide not just by international laws, but also regional laws where they do business.

A label is a key-value pair that helps you organize your Google Cloud resources. You can attach a label to each resource, then filter the resources based on their labels. Information about labels is forwarded to the billing system, so you can break down your billed charges by label.

Reference link- https://cloud.google.com/cost-management

One row of a dataset containing one or more input columns and possibly a prediction result.

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https://developers.google.com/machine-learning/guides/rules-of-ml#terminology

Dataflow is the managed version of Apache Beam. Beam = Batch + Stream. Unified stream and batch data processing that's serverless, fast, and cost-effective.

Reference link-  https://cloud.google.com/dataflow

Explanation

Organizations can scale in the cloud by paying for what they use, when they use it.

Explanation

IDaaS - identity providers managed by the company give better control over security and privacy. Security/access can be set granularly, while also being centralized. You don't have to manage multiple credentials.

Horizontal scaling, also called scaling out, adds new VMs to increase application capacity.

Google provides a page that brings together everything needed around support. Its called the Support Hub

Reference link- https://cloud.google.com/support-hub

Sole-tenancy lets you have exclusive access to a sole-tenant node, which is a physical Compute Engine server that is dedicated to hosting only your project's VMs. Use sole-tenant nodes to keep your VMs physically separated from VMs in other projects, or to group your VMs together on the same host hardware.

https://cloud.google.com/compute/docs/nodes/sole-tenant-nodes

Policies are a union of those applied to resources themselves and those inherited from higher levels in the hierarchy. If a parent policy is less restrictive, it overrides a more restrictive policy applied to the resource. If a parent policy is more restrictive, it does not override a less restrictive policy applied to the resource. Therefore, access granted at a higher level in the hierarchy cannot be taken away by policies applied at a lower level in the hierarchy.

The standby instance is used in high availability to replace the primary instance when failover occurs. The standby instance doesn't appear in the Google Cloud Console. When failover occurs, connections to the primary instance are automatically transferred to the standby instance.

Cloud SQL Key Terms:

Cloud SQL instance

A Cloud SQL instance corresponds to one virtual machine (VM). The VM includes the database instance and accompanying software containers to keep the database instance up and running.

Database instance

A database instance is the set of software and files that operate the databases: MySQL, PostgreSQL or SQL Server.

High availability

Cloud SQL instances using high availability (HA) provide greater reliability than non-HA instances.

HA in Cloud SQL works by having two synchronized instances: a primary instance and a standby instance. Each instance has exactly one VM. Each instance is in a different zone in the same region.

Failover

A failover is when Cloud SQL switches serving from the original primary instance to the standby instance.

Autofailover is a mechanism that automatically triggers failover when a Cloud SQL instance didn't issue a heartbeat in the previous interval.

Standby instances

The standby instance is used in high availability to replace the primary instance when failover occurs. The standby instance doesn't appear in the Google Cloud Console. When failover occurs, connections to the primary instance are automatically transferred to the standby instance.

Clone

When you clone a Cloud SQL instance, you create a new instance that is a copy of the source instance, but is completely independent. After cloning is complete, changes to the source instance are not reflected in the clone, and changes in the clone are not reflected in the source instance.

Replication

Replication is the ability to create copies of a Cloud SQL instance or an on-premises database, and offload work to the copies. The main reason for using replication is to scale the use of data in a database without degrading performance on the primary instance.

Read replica

The read replica is an exact copy of the primary instance. Data and other changes on the primary instance are updated in almost real time on the read replica. Send your write transactions to the primary instance, and your read requests to the read replica. The read replica processes queries, read requests, and analytics traffic, thus reducing the load on the primary instance.

Source server

Replication copies transactions from a primary instance to one or more read replicas. The primary instance is also called the source server. The source server can be a Cloud SQL primary instance, or a server outside of Google Cloud, such as an on-premises server or a server running in a different cloud. If the source server is outside of Google Cloud, we call it Replication from an external server.

Cloud SQL Auth proxy client

The Cloud SQL Auth proxy client is open source software maintained by Cloud SQL. It connects to a companion process, the Cloud SQL Auth proxy server, running on your Cloud SQL instance. You run the Cloud SQL Auth proxy client on your own servers. The Cloud SQL Auth proxy client can be used to establish a secure SSL/TLS connection to the database instance, and/or to avoid having to open the firewall. Authentication is done through Identity and Access Management (IAM).

Sustained, Committed and Preemptible

  vCPU and memory usage for each of these categories can receive discounts

VM vCPU and memory usage for each of these categories can receive discounts

Sustained-use discounts—Google offers up to 30% off for workloads that run for most of the billing month on GCP services.

Committed-use discounts—users can save up to 57% by committing to use an instance for a certain time period, with no upfront payment and with the flexibility to change instances during the commitment period.

Preemptible VMs—similar to the concept of AWS spot instances, Google offers up to 79% off for Virtual Machines that may be shut down at any time and replaced by others.

Reference link-  https://cloud.google.com/compute/docs/sustained-use-discounts

Reference link– https://cloud.google.com/compute/docs/instances/signing-up-committed-use-discounts

Reference link– https://cloud.google.com/compute/docs/instances/preemptible

Groups are convenient to use for this requirement. Permissions to the group are automatically inherited by the members of the group. Adding and removing UX testers from the group will grant and remove permissions.

Cloud BigTable

Key features

High throughput at low latency

Bigtable is ideal for storing very large amounts of data in a key-value store and supports high read and write throughput at low latency for fast access to large amounts of data. Throughput scales linearly—you can increase QPS (queries per second) by adding Bigtable nodes. Bigtable is built with proven infrastructure that powers Google products used by billions such as Search and Maps.

Cluster resizing without downtime

Scale seamlessly from thousands to millions of reads/writes per second. Bigtable throughput can be dynamically adjusted by adding or removing cluster nodes without restarting, meaning you can increase the size of a Bigtable cluster for a few hours to handle a large load, then reduce the cluster's size again—all without any downtime.

Flexible, automated replication to optimize any workload

Write data once and automatically replicate where needed with eventual consistency—giving you control for high availability and isolation of reading and write workloads. No manual steps are needed to ensure consistency, repair data, or synchronize writes and deletes. Benefit from a high availability SLA of 99.999% for instances with multi-cluster routing across 3 or more regions (99.9% for single-cluster instances).

Google Cloud Platform has other storage options to meet your needs for structured, unstructured, transactional and relational data. Core storage options: Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Data Store and Google Big Table. Depending on your application, you might want to use one or several of these services to get the job done.

When there are huge surges in demand, it is preferable to use serverless technologies that automatically scale on demand. In this case, the key concern is data ingestion. Pub/Sub is a serverless system that can expand to absorb such demand.

Cloud Vision API allows you to programmatically identify images, text, etc. in the document. This would be the best option.

https://cloud.google.com/vision

Firebase/Firestore is easy to build and is suitable for user information that could bvary in nature.

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.

In many cases, customers might not know the implications of the 9s with respect to scheduled maintenance, upgrades, etc. It's possible that they are holding unnecessary expectations that significantly exceed their requirements.

-> Even though 0.0009 % increase it looks like a small increment, an addition of a single 9 reduces the possible downtime by 10 times. So the effort is often much greater.

Reference link-  https://en.wikipedia.org/wiki/High_availability

Using sync for new images implies that you will continue to use your onprem and keep synchronizing it forever, Sync just once for the old images, new images go directly to google cloud via pub/sub, and eventually get rid of the onprem.

Lending DocAI is a pre-packaged AI solution that speeds "up the mortgage workflow processes to easily process loans and automate document data capture, while ensuring the accuracy and breadth of different documents (e.g., tax statements and asset documents)."

https://cloud.google.com/solutions/lending-doc-ai

Since they have already paid for  data center for another year. They have the time and resources to work with, They can make the change to their workloads locally/on-promise Improve and Migrate Move to Google Cloud later on.

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.

Autoscaling is supported in both Flexible and Standard environments. Flexible Environment does run a Docker container that includes a custom runtime or source code written in other programming languages.

Reference link - https://cloud.google.com/appengine/docs/the-appengine-environments

SaaS – Software as a Service (SaaS) provides you a complete product that is run and managed by the service provider. You worry only about using the software and not about infrastructure.

SaaS provides the lowest level of flexibility and management control over the infrastructure.    (Example:  Google Gsuite and MS O365)

Firebase Crashlytics:

Get clear, actionable insight into app issues with this powerful crash reporting solution for iOS, Android, and Unity.

Firebase Crashlytics is a lightweight, real-time crash reporter that helps you track, prioritize, and fix stability issues that erode your app quality. Crashlytics saves you troubleshooting time by intelligently grouping crashes and highlighting the circumstances that lead up to them.

Find out if a particular crash is impacting a lot of users. Get alerts when an issue suddenly increases in severity. Figure out which lines of code are causing crashes.

https://cloud.google.com/blog/products/devops-sre/sre-fundamentals-slis-slas-and-slos

The question is about a dynamic way to provision VM, it can be achieved by a Deployment manager or by using terraform. MIG is creating multiple machines based on templates by load balancing

Classification. De-classification and Inspection

Classification is the process to inspect the data and know what data we have, how sensitive it is, and the likelihood. Inspection and classification happen here.

De-identification is the process of removing, masking, replacing information from data.

Reference link- https://cloud.google.com/dlp/docs

"Cloud VPN securely extends your peer network to Google's network through an IPsec VPN tunnel. Traffic is encrypted and travels between the two networks over the public internet. Cloud VPN is useful for low-volume data connections. For additional connection options, see the Hybrid Connectivity product page."

You can send notification messages using the Notifications composer in the Firebase console. Though this does not provide the same flexibility or scalability as sending messages with the Admin SDK or the HTTP and XMPP protocols, it can be very useful for testing or for highly targeted marketing and user engagement. The Firebase console provides analytics-based A/B testing to help refine and improve marketing messages.

After you have developed logic in your app to receive messages, you can allow non-technical users to send messages per the instructions on the Notifications page in the Firebase Help Center.

BigQuery is an enterprise data warehouse for large amounts of relational structured data Serverless, highly scalable, and cost-effective multicloud data warehouse designed for business agility.

Store the information in Secret Manager is a secure and convenient storage system for API keys, passwords, certificates, and other sensitive data. Secret Manager provides a central place and single source of truth to manage access, and audit secrets across Google Cloud.

https://cloud.google.com/secret-manager

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

VM instances that only have internal IP addresses (no external IP addresses) can use Private Google Access. They can reach the external IP addresses of Google APIs and services. The source IP address of the packet can be the primary internal IP address of the network interface or an address in an alias IP range that is assigned to the interface. If you disable Private Google Access, the VM instances can no longer reach Google APIs and services; they can only send traffic within the VPC network.

https://cloud.google.com/vpc/docs/configure-private-google-access

You can run a single instance of Google Cloud Directory Sync to synchronize user accounts and groups to Google Cloud.

Explanation

By storing their application data in the cloud the organization will be able to gather and analyze user behavior data in real-time. This will enable them to dynamically adjust their application for different user needs.

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_discounts_across_projects

Host all your subsidiaries' services together with your existing services on the public cloud.

https://cloud.google.com/anthos

VMware Engine helps migrate and run virtual machines in Google Cloud with minimal changes to the VM architecture.

https://cloud.google.com/learn/what-is-a-virtual-machine

Migrate for Compute Engine enables you to lift and shift workloads at scale to Google Cloud Compute Engine with minimal changes and risk.

After the service provider provisions your connection, you can start passing traffic between your networks by using the service provider's network.

You do not want to be required to provision infrastructure or create server clusters. Because Unified stream and batch data processing that's serverless, fast, and cost-effective.

Reference link- https://cloud.google.com/dataflow

you can get a 57% discount by agreeing to commit to a 3-year contract. Any usage over the commitment will just be billed at the standard rate. Since they only need 300 CPUs 30% of the time, will pick answer C so that we are not paying usage off 300 CPUs all of the time. This gives us a discount of 57% for 200 CPU's, huge cost savings.

Deploy your application to App Engine using the gcloud app deploy command. This command automatically builds a container image by using the Cloud Build service and then deploys that image to the App Engine flexible environment.

Explanation

Database Migration is the right one to use: "Simplifying migrations to Cloud SQL. Now available for MySQL and PostgreSQL migrations, with SQL Server coming soon." Since the customer also doesn't want to manage their own database installations in the future, Cloud SQL is the best option.

https://cloud.google.com/database-migration

Because containers can compartmentalize applications which enables parts to be edited in isolation.

Reference link- https://cloud.google.com/learn/what-are-containers

https://cloud.google.com/compute/docs/instances/preemptible

Bare Metal Solution for Oracle

Bring your Oracle workloads to Google Cloud with Bare Metal Solution and jumpstart your cloud journey with minimal risk.

- Continue to run any version, any feature set, any database option, and any customizations (patchsets)

- Enterprise-grade deployment platform

- High availability with Oracle RAC

- Works with any application, any Oracle versions

- All your existing investment in tooling and best practices will work as is

Cloud Memorystore is an in-memory database that has sub-millisecond latency. This is ideal for caching application data that also changes once in a while.

https://cloud.google.com/memorystore

Apply the Principle of Least Privilege and only provide read permissions on only the required buckets. No more, no less

https://cloud.google.com/storage/docs/access-control/iam-roles

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

Explanation

Because this will enable the business to better serve their users.

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.

Migrate for Compute Engine’s advanced replication migration technology copies instance data to Google Cloud in the background with no interruptions to the source workload that’s running.

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https://cloud.google.com/migrate/compute-engine

Modernizing applications means they can make alterations and innovate more easily.

Explanation

Option A is Correct- BigQuery Flex Slots for cyclical workloads that require extra capacity, or for workloads that need to process a lot of data in a short time, and so would be less expensive to run using reserved slots for a short time.

Google cloud have vast majority of products/tools that you can use to innovate. Additionally, there are products in google that scale automatically based from usage (Ex. App Engine, Cloud Run, etc.)

Virtual machines - you can install customized OS

Containers - about applications

Virtualization enables you to run multiple operating systems on the hardware of a single physical server, while containerization enables you to deploy multiple applications using the same operating system on a single virtual machine or server. Serverless computing would be no OS required and the open source operating system allows the use of code that is freely distributed and available to anyone and for commercial purposes such as Linux and Free BSD.

https://cloud.google.com/architecture/migrating-a-monolithic-app-to-microservices-gke

The Premium customer care service level in Google Cloud provides the fastest response times and includes a dedicated Technical Account Manager (TAM) to assist with managing critical workloads and ensuring smooth operations.

Option A: Premium is correct because it provides the required support features, including fast response times and a dedicated TAM.

References:

Google Cloud Support Services: Premium Support Overview

Google Cloud Customer Care Options: Comparison of Support Levels

Per Google docs, specifically for GCP Cloud Storage there exists four types of storage with one of them, standard storage, being described as "storage for data that is frequently accessed ("hot" data) and/or stored for only brief periods of time." https://cloud.google.com/storage

Tensor Processing Units (TPUs) are a type of purpose-built hardware designed specifically to accelerate machine learning workloads, particularly those involving TensorFlow. TPUs provide significant speed and performance improvements over general-purpose CPUs and even GPUs when running complex ML models.

Option C: TPUs is correct because TPUs (Tensor Processing Units) are optimized to accelerate the training of machine learning models developed with TensorFlow, providing faster performance compared to other hardware.

References:

Google Cloud: TPUs Overview

Google Cloud AI and Machine Learning Products: Accelerators for TensorFlow

Streaming analytics is the real-time processing of data as it is ingested. The defining function of streaming analytics is to process data records continuously, as opposed to batch processing, which handles data in large chunks at intervals. Streaming analytics allows for immediate insights and actions based on live data.

Option B: Processing data records continuously is correct because it describes the fundamental nature of streaming analytics: it analyzes data streams as they come in, enabling real-time analysis, monitoring, and decision-making.

References:

Google Cloud Documentation on Dataflow: Real-Time Stream Processing

Google Cloud Platform's Big Data Solutions: Stream Analytics

The correct answer is B. When it is at rest and in transit. Here's why:

Context of the Question: The question is about when data is automatically encrypted by Google Cloud.

Google Cloud Product Relevance:

Google Cloud automatically encrypts data at rest and in transit. This means that data stored in Google Cloud (such as in Google Cloud Storage or BigQuery) is encrypted by default to protect it from unauthorized access. Similarly, data in transit between Google Cloud services or between users and Google Cloud is encrypted using TLS (Transport Layer Security).

These automatic encryption measures are part of Google's comprehensive approach to data security, ensuring that data remains protected throughout its lifecycle.

Why Not Other Options:

A. When it is at rest only: This is incorrect because data is also encrypted in transit.

C. When it is in transit only: This is incorrect because data is also encrypted at rest.

D. Data is not automatically encrypted by default: This is incorrect as Google Cloud provides automatic encryption for data both at rest and in transit.

Google Cloud Digital Leader References:

Refer to Google Cloud Encryption documentation for more information on how data is encrypted in Google Cloud.

BigQuery is a fully managed, serverless data warehouse that is designed for large-scale data analysis. It is optimized for handling petabytes of data and provides fast query performance. It is scalable and supports advanced analytical queries, making it ideal for organizations that need to analyze massive amounts of historical data efficiently.

Option A: BigQuery is correct because it is specifically designed for large-scale, advanced data analytics and is fully managed by Google Cloud.

References:

Google Cloud: BigQuery Product Overview

Google Cloud BigQuery: Advanced Data Analysis Capabilities

Per Google docs, App Engine, allows for "freeing up your developers with zero server management and zero configuration deployments". https://cloud.google.com/appengine

When data is uploaded to Google Cloud, the customer retains full ownership of their data. Google Cloud acts as the data processor, providing the infrastructure and services for storage, but the rights to the data, including access, control, and management, remain with the customer.

Option B: The customer is correct because, according to Google Cloud's data privacy policy, the customer owns their data.

References:

Google Cloud Privacy Policy: Data Ownership and Responsibility

Google Cloud Trust Principles: Data Protection and Privacy

The correct answer is D. Run a replica of the application in a region in the United States. Here's why:

Context of the Question: The application currently runs in a single region in Europe, and customers in the United States are experiencing high latencies. The organization needs to reduce latencies for these customers.

Google Cloud Product Relevance:

Running a replica of the application in a region in the United States would reduce latency by hosting the application closer to the end users. This improves response times and ensures a better user experience for customers in the United States.

Google Cloud provides services such as Cloud Load Balancing to distribute traffic efficiently between instances in different regions.

Why Not Other Options:

A. Set up a new billing account in the United States: Billing accounts do not affect application performance or latency.

B. Run the application in additional regions in Europe: This would not reduce latencies for users in the United States, as their traffic would still need to travel across the Atlantic.

C. Run the application in additional zones in the European region: Additional zones in Europe would not help with reducing latency for U.S. customers.

Google Cloud Digital Leader References:

Refer to Google Cloud's multi-region deployment documentation for more information on deploying applications across multiple regions.

The correct answer is D. Cloud Storage. Here's why:

Context of the Question: The organization has a large archive of unstructured data, including video and audio files. These types of files are typically large and require scalable storage that supports unstructured data formats.

Google Cloud Product Relevance:

Cloud Storage is a fully managed, scalable, and highly durable object storage service that supports storing any amount of unstructured data, including images, videos, audio files, backups, and more. It offers various storage classes to optimize costs based on access frequency, making it ideal for large archives.

Cloud Storage provides features like versioning, lifecycle management, and access control, which are essential for managing a large archive of files.

Why Not Other Options:

A. Cloud SQL: Cloud SQL is a managed relational database service that supports structured data with predefined schemas, not suitable for storing unstructured data like videos and audio files.

B. Cloud Spanner: Cloud Spanner is a fully managed, globally distributed relational database. It is also designed for structured data and not suitable for large-scale unstructured data storage.

C. Cloud Bigtable: Cloud Bigtable is a NoSQL database for large-scale analytics but is not optimized for storing unstructured data like multimedia files.

Google Cloud Digital Leader References:

Refer to Google Cloud Storage documentation for details on storing unstructured data and managing large archives.

The correct answer is C. A hybrid-cloud approach. Here's why:

Context of the Question: The organization wants to use Google Cloud's advanced machine learning capabilities while maintaining data storage on-premises due to regulatory requirements.

Google Cloud Product Relevance:

A hybrid-cloud approach combines on-premises infrastructure with cloud services. This approach allows organizations to keep sensitive data on-premises while leveraging cloud services for additional computing capabilities, such as advanced machine learning. Google Cloud offers tools like Anthos and Google Cloud's hybrid and multi-cloud solutions to facilitate this integration, enabling the organization to use cloud-based machine learning tools while keeping data in their local data center.

Why Not Other Options:

A. A private-cloud approach: This refers to a cloud environment that is entirely operated within the organization's own infrastructure, which would not provide access to Google Cloud's ML capabilities.

B. A multi-cloud approach: While multi-cloud involves using services from multiple cloud providers, it does not specifically address the requirement to keep data on-premises.

D. A public-cloud approach: This would involve moving data to the public cloud, which contradicts the requirement to keep data stored on-premises.

Google Cloud Digital Leader References:

Refer to Hybrid and Multi-Cloud Solutions in Google Cloud documentation to understand how Google Cloud can integrate with on-premises data centers while providing cloud services.

Google Cloud commitment to keep the data secure and private:

1. Org owns the data and not Google

2. Google does not sell data to 3rd parties

3. All customer data is encrypted by default

4. Google Cloud guards insider against your data

5. No backdoor access to any govt. entity

6. Google’s privacy practices are audited against international standards

A relational database offers the functionality of storing transactional data, which can then be accessed electronically. Relational databases store structured data that can be organized in tables with defined relationships between them. This makes them well-suited for transactional data, such as inventory data, that needs to be accessed and updated frequently.

An Application Programming Interface (API) is a set of protocols, routines, and tools that allow different software applications to communicate with each other. APIs provide the necessary instructions for one program to interact with another, enabling the integration of different systems and the development of new functionalities.

Option D: To provide a set of instructions that allow computer programs to communicate with each other is correct because it accurately describes the fundamental purpose of an API.

References:

Google Cloud: Understanding APIs and their Use Cases

Google Cloud API Documentation: API Basics

https://cloud.google.com/vision

The correct answer is B. Back up data regularly. Here's why:

Context of the Question: The organization is concerned about data loss due to hardware failures or cyber-attacks and wants to restore their systems to a previous state in case of such events.

Google Cloud Product Relevance:

Backing up data regularly is the most effective way to ensure data can be restored in case of loss or damage. Regular backups create copies of data that can be stored separately from the main systems, ensuring that even if the primary data is lost or compromised, the backup can be used to restore it to a previous state.

Google Cloud offers several backup solutions, such as Cloud Storage for storing backups and Cloud SQL automated backups for database instances.

Why Not Other Options:

A. Use Cloud Monitoring: Cloud Monitoring helps observe and monitor the health and performance of applications and infrastructure but does not provide backup or data restoration capabilities.

C. Set service level objectives (SLOs): SLOs are targets for service availability and performance but do not directly help with data backup or recovery.

D. Enable autoscaling: Autoscaling helps automatically adjust resources to meet demand but does not protect against data loss or provide restoration capabilities.

Google Cloud Digital Leader References:

To understand more about backup strategies in Google Cloud, refer to Backup and DR (Disaster Recovery) documentation.

Cloud Logging is a fully managed service that allows you to store, search, analyze, monitor, and alert on logging data and events from Google Cloud and Amazon Web Services