GCP Interview Questions And Answers

Top 50+GCP Interview Questions and Answers

GCP Interview Question And Answers

1. What exactly is GCP?

GCP is an abbreviation for Google Cloud Platform. It is a Google cloud computing platform that offers a variety of services such as computing, storage, networking, and security.

2.What is the definition of computing?

Computing is the application of technology to various computations and information processing. It includes tasks like problem-solving, information analysis, and data storage. The software and programming languages used to run and communicate with a variety of hardware, including computers and servers, are all included in the category of computing technology.

The study and creation of algorithms, data structures, and other mathematical ideas essential to computing are also included.

Computing, to put it simply, is the application of technology to data processing to enhance the usefulness and significance of information. In many different domains, including science, business, entertainment, and communication, it is essential.

3. How does cloud computing work?

In order to facilitate faster innovation, more flexible resource allocation, and scale economies, cloud computing refers to the distribution of computing services—such as servers, storage, libraries, connectivity, software, analytics, and intelligence—over the internet, or “the cloud.” 

Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS) are the three primary categories into which cloud computing services fall. Cloud computing is becoming more and more popular, and companies of all sizes can now take advantage of its many benefits. These include lower costs, more operational efficiency, and the flexibility to scale resources as needed.

4.What distinguishing qualities do cloud services offer?

  • The ease with which commercial software can be accessed and managed from any location in the world is just one of the many features offered by cloud services and cloud computing in general.
  • Simple software centralization of all administration into a single web service
  • The creation of web applications with the ability to manage numerous clients at once from any location in the world
  • The centralization and automation of the updating process to eliminate the need for software upgrade downloads.

5. What Is the Platform Google Cloud?

  • Google Cloud Platform (GCP) is an array of cloud computing services provided by Google, operating on the same internal infrastructure as Google’s consumer products, including YouTube and Google Search.
  • GCP provides a broad range of services that let businesses create, launch, and grow apps on the same infrastructure as Google. These services include computing, storage, networking, big data, machine learning, and the Internet of Things (IoT).
  • With the help of a wide range of tools and services, Google Cloud Platform (GCP) enables users to develop, run, and manage their apps and data on Google’s infrastructure. These integrated services are made to work together harmoniously to provide a flexible and cost-effective solution that can be used by companies of all sizes.
  • Along with having to invest in and maintain their own data centers, businesses can use GCP to benefit from the scalability, security, and performance of Google’s infrastructure to power their applications.

6. What benefits can cloud computing offer?

Let’s start by contrasting AWS Cloud and Google Cloud:

Standards Cloud AWS Data Centers for Google comparatively smaller Big number

Market PlacementThree of the best market leaders

Arrival in the CloudEntering late very early adopter

There are numerous benefits to adopting cloud computing. We’ll talk about a few of the cloud’s most significant benefits here. By facilitating rapid and easy deployment, the cloud makes it possible for you to begin using services and apps as soon as possible.

7. Mention the cloud computing platforms that are used on a large scale.

Large-scale cloud computing is facilitated by several platforms, including Google Cloud Platform, Azure, and Amazon Web Services.

8. What are the various cloud computing deployment models?

  • Community cloud,
  •  private cloud, 
  • public cloud, and
  •  hybrid cloud

9. Which different parts make up the Google Cloud Platform?

The different parts of GCP are as follows:

  • Compute Engine on Google
  • Engine for Google Cloud Containers
  • Cloud Storage by Google
  • Cloud App Engine by Google
  • Cloud Dataflow on Google
  • Machine Learning Engine on Google Cloud
  • BigQuery Service on Google
  • Google Cloud Workplace Locator
  • Cloud Endpoints for Google
  • Cloud Test Lab for Google

10. What do cloud computing system integrators do?

There are several potentially complex components that make up the cloud. Among other things, the system integrator approach in cloud computing offers the process of cloud design and integration of the different parts to create a private or hybrid cloud network.

Enroll in the Google Cloud Certification Training offered by Azure training to learn more about GCP and acquire comprehensive knowledge on the subject.

11. How Does Utility Computing Benefit Users?

Utility computing refers to a type of on-demand and pay-as-you-go computing service where the provider manages and operates the computing resources and you choose which services to use. These resources are all hosted in the cloud.

12. Describe the security features offered by the cloud.

  • Some of the most important security features that the cloud has to offer are listed below:
  • When a user joins the cloud ecosystem, access control allows them to control who can access what.
  • Identity Management: This authorizes the use of the application services.
  • Authorization and Authentication: Only users who have been authenticated can access the data and applications thanks to this security feature.

Interview Questions for New Hires at Google Cloud

13. What is Platform by Google Cloud?

The cloud-based infrastructure of the company is referred to as Google Cloud Platform. Numerous other subjects are covered by this set of services, including big data, computing, networking, machine learning, virtual machines, and storage. The infrastructure used by Google’s user products, such as Gmail, YouTube, and Google Search, is also used by these services.

14. What advantages does utilizing the Google cloud platform offer?

  • Price-wise, GCP is far more affordable than other cloud service providers.
  • On Google Cloud servers, your data and information are accessible from any location.
  • When it comes to cloud hosting, GCP offers superior performance and service.
  • Updating servers and security data is quicker and easier with Google Cloud.

15. What characteristics does the Google Cloud Platform offer?

  • The ability to customize your machine types with various RAM, HDD, and processor configurations.
  • Resizing discs in place can be done without affecting service in any way.
  • GCP comes with pre-installed tools for managing a broad range of operations.
  • There are two varieties of hosting available. Users have the option of using a compute engine (IaaS) or an app engine (PaaS).

16. What typical applications does the Google Cloud Platform serve?

  • The Google Cloud Platform can be used for a variety of tasks,
  • Including database management, 
  • Website and application development, AND
  •  Hosting.

17. How do AWS and GCP differ from one another?

Google Cloud is an amalgamation of Google’s publicly available cloud computing services and assets, while AWS is a secure cloud service that is developed and managed by Amazon. While Amazon Simple Storage Services is offered by AWS, Google Cloud Storage is supplied by Google Cloud.

18. What kinds of security features can be found on the cloud?

Among the cloud’s crucial security features are:

  • Identity Management: It prepares the ground for service application approval.
  • Users can control how other users can access 
  • Authentication and Authorization: This security measure makes sure that only users who have been verified and granted permission can access apps and data.

19. What are the various cloud architecture components?

The essential elements of the architecture of cloud computing are as follows:

  • The front-end system
  • back-end platform delivery via the cloud

20. Explain the different cloud architecture layers.

The following are the different cloud architecture layers:

  • Physical Layer: Objects that can be managed and controlled in the real world are included in this layer, such as physical servers and networks.
  • Platform Layer: This layer houses operating systems and applications, among other services. It functions as a platform for deployment and development. 
  • Infrastructure layer: Storage resources, virtualized servers, and networking are all included in the infrastructure layer. 
  • Application Layer: The Application Layer is directly used by end users. This layer can be scaled and configured. Customers can personalize the software with metadata.

21.Specifically, what does "EUCALYPTUS" mean in relation to cloud computing?

An open-source cloud computing infrastructure is called “EUCALYPTUS.” EUCALYPTUS is an acronym for “Elastic Utility Computing Architecture.” Developers can quickly and simply create private, public, and hybrid cloud environments with EUCALYPTUS.  By setting up your own data center in the cloud, you can benefit from everything that the cloud has to offer.

22. By Google Compute Engine, what do you mean?

The Google Cloud Platform is built on the Google Cloud Engine.. Users can run their own virtual machines—Windows or Linux—on this Google-hosted Infrastructure as a Service. KVM and long-term storage enable the operation of virtual machines.

23.How can one authenticate with the Google Compute Engine API using different methods?

There are several methods available for Google Compute Engine API authentication:

  • Using the client library 
  • Through OAuth 2.0
  • easily with a token of entry.

24. Which open-source cloud computing platforms are the most popular?

OpenStack Mesos Cloud Foundry KVM for Apache.

GCP Experienced Interview Questions

25.Describe the various types of software as a service (SaaS) offerings.

The two distinct categories of SaaS are:

  • The SaaS model known as single-tenant multi-tenancy allows you to have exclusive resources that you are not obliged to share with anybody else.
  • Fine-grained multi-tenancy: In this SaaS deployment, resources are shared by several tenants while the functionalities remain constant.

26.How does API work in the cloud domain?

  • It’s not necessary to create the entire program.
  • Sending data from one app to another is simple.
  • Creating apps and integrating them with cloud services is simple.
  • It securely links two applications together.

27. Describe the distinction between cloud computing's elasticity and scalability.

  • Scalability: Scalability in the cloud refers to the capacity to manage an increased workload. It can be done by expanding the number of servers or creating space for them on already-existing ones.
  • Elasticity: Elasticity is the ability to add or remove virtual machines as needed, which helps you save money and maximize resource usage

28. What are accounts for services?

Project-related special accounts are called service accounts. They are used to provide access to non-sensitive data and authorize Google Compute Engine to carry out operations on behalf of the user.

29. How well-versed are you in the Google Cloud SDK?

A suite of tools for interacting with services and data based on the Google Cloud Platform is available to developers through the Google Cloud Software Development Kit (SDK). It consists of the gcloud, gsutil, and BQ command, three distinct command line utilities. Only specific operating systems and versions of Python (2.7.x), including Windows, Linux, and macOS, are compatible with the Google Cloud SDK. For the other tools in the set, there might be additional, more detailed specifications.

30. Enumerate the Google Cloud Platform's principal elements.

Among the important parts of GCP are:

  • Kubernetes container orchestration system and Google App Engine are examples of data processing tools.
  • A variety of networking-related components, such as cloud firewalls and virtual private clouds (VPCs).
  • A database and a storage system are present.
  • components of big data.
  • Management tools, such as a debugger, logger, and tracer.
  • Cloud IAM and Cloud Identity are two examples of software used for cloud identity management.
  • Effectiveness and skilled equipment.
  • A container builder and a cloud-based testing lab are two resources for programmers.

31. How does the cloud support on-demand functionality?

Cloud computing was created as a technology so that its users could use it whenever and wherever they wanted. With today’s technology and easy access to apps like Google Cloud, the idea is much easier to implement than it used to be. Users of Google Cloud and other similar apps can access their cloud-stored files from any device, at any time, and from anywhere in the world.

32.What is the GCP cloud pricing model?

  • Azure Active Directory is usually referred to as Azure AD and it is a cloud-based identity and access management service that will assist in managing the Azure resources.
  • An Azure AD has a various relationship with subscriptions. 
  • An Azure subscription can only trust a single Active Directory, but multiple subscriptions can be associated with a single Azure Active Directory instance.

33. What are the Google Cloud Platform cloud storage libraries and tools?

  • The JSON API and the XML API are heavily used in cloud storage on Google’s cloud platform. Google also provides the following services to engage with cloud storage.
  • The Google Cloud Platform Console supports basic bucket and object operations.
  • Cloud storage client libraries are available in a variety of languages.
  • The Gustily Command-line Tool is a cloud storage command-line interface

34.What do you think "Managed VMs" mean in the context of GCP?

Google manages VMs, or virtual machines. When you launch a virtual machine on GCP using Managed VMs, Google manages the infrastructure, including the host operating system, virtualization layer, and hardware. It can help you simplify your workflow and focus on developing and deploying applications.

35. What is the distinction between PaaS and IaaS?

  • IaaS: IaaS, or “Infrastructure as a Service,” is a type of cloud computing that provides users with access to a virtualized computing environment. This can include, among other things, storage, networking, and servers.
  • PaaS (Platform as a Service):  is a type of cloud computing that provides users with access to a platform for testing, building, and deploying applications. Because it handles much of the infrastructure behind apps, PaaS can make them easier to build and deploy.

36. What is GCP autoscaling?

The Google Cloud Platform’s managed instance groups support auto-scaling. Managed instance groups are collections of instances that are identical and were created using the same master template. The simplest way to auto-scale in Avi Vantage is to scale based on the amount of CPU used by a group of virtual machine instances.

37. What is the purpose of a Google Cloud Storage bucket?

Buckets are simple containers for storing data. Everything in Cloud Storage must be placed in a “bucket.” There is no limit to the number of buckets you can create or delete. However, buckets cannot be nested within each other in the same way that directories and files can.

38. What exactly are Google Cloud APIs?

Google Cloud APIs are most useful when used to automate processes in your preferred language. APIs allow multiple Google services to communicate with one another and be integrated into third-party applications. Another way to think of it is as a middleman that allows end users to access cloud-based resources and applications.

39. What are the similarities and differences between Google Compute Engine and Google App Engine?

Google Compute Engine is the company’s offering for IaaS (infrastructure as a service). Google App Engine, on the other hand, is Google’s platform services PaaS offering. They make an excellent team and complement each other. Compute Engine develops custom business logic, whereas App Engine powers websites and mobile backends. It can even be used to host a private data storage system.

40. What are the various GCP service types?

  • Computing, Storage, Networking, and Big Data are the four major categories of GCP services.
  • GCP’s computing services include virtual machines, containers, and serverless computing.
  •  GCP’s Storage services include options such as databases, object storage, and block storage. GCP’s network services include VPC, load balancing, and DNS.
  •  Businesses can use GCP’s Big Data services to process data and perform analytics.

41. What are the fundamental concepts of GCP?

Google Cloud Platform (GCP) includes a broad range of cloud computing services and principles, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These fundamental concepts give businesses the ability to scale, secure, and manage their IT infrastructure while leveraging the power of cloud technology.

42. What are the three main GCP principles?

The three main GCP principles are as follows:

  • GCP prioritizes data and infrastructure security through cutting-edge security measures such as encryption, robust Identity and Access Management (IAM), and stringent compliance certifications.
  •  Scalability: GCP allows users to easily scale up or down their resources, ensuring seamless adaptability to fluctuating demands while maintaining cost-efficiency.
  •  Flexibility: GCP’s extensive offering of services and tools allows users to choose and configure solutions that precisely match their specific needs, promoting versatility and agility in cloud operations.

43.What are the three GCP pillars?

The three pillars of GCP principles are as follows:

  • GCP provides users with virtual machines (VMs) and container orchestration via Google Kubernetes Engine, allowing for highly adaptable compute resources.
  •  Storage: Google Cloud Platform provides scalable storage solutions, such as Google Cloud Storage and Bigtable, for efficient data management, storage, and analysis.
  •  Networking: GCP’s robust networking services enable users to build secure, high-performance networks and establish global connectivity for cross-regional operations.

44. What exactly is a GCP diagram?

A GCP diagram is a graphical representation of Google Cloud Platform’s cloud architecture. These visualizations vividly depict the interconnections and interactions between various GCP services and components, allowing for effective cloud deployment planning, design, and comprehension.

45.What exactly is the GCP pipeline?

A GCP pipeline is a set of automated data processing steps used by Google Cloud Platform. These pipelines use GCP services such as Cloud Dataflow or Cloud Composer to easily ingest, transform, and analyze data, and are frequently used as the foundation for data processing or ETL (Extract, Transform, Load) workflows. This automated approach ensures that data management and analysis processes are reliable and efficient.

46.What exactly is the Google Kubernetes Engine (GKE)?

Google Kubernetes Engine (GKE) is Google’s container orchestration system. It simplifies containerized application deployment and management on GCP, making it easier for developers to run and manage their applications in the cloud.

47.What exactly is Google Cloud SQL?

Google Cloud SQL is a cloud-based service that provides fully managed relational databases. It is intended to make database setup, maintenance, management, and administration easier. Cloud SQL allows you to concentrate on developing your applications while Google manages the database. This feature makes running your cloud applications easier and more efficient.

48.Describe Google Cloud Dataflow.

Google Cloud Dataflow is a fully managed service that allows you to build and run data processing pipelines. It is intended to work in both real-time and batch modes, making it a versatile business tool. Cloud Dataflow, which is based on Apache Beam, provides an easy-to-use platform for data transformation and processing.

49.What exactly is Google Cloud Pub/Sub?

Google Cloud Pub/Sub supports a variety of message delivery methods. It ensures that messages are delivered in the order in which they were published. It has a high throughput and is highly available, making it an excellent choice for businesses that need dependable and scalable messaging services.

50.What exactly is Google Cloud Composer?

Google Cloud Composer has an easy-to-use interface for creating and managing complex workflows, including features such as task scheduling, monitoring, and error handling. It is an effective tool for businesses that need to automate workflows, reduce operational costs, and increase efficiency.

51.What is a Site Reliability Engineer's (SRE) role in GCP?

A Site Reliability Engineer (SRE) in GCP ensures the reliability, availability, and performance of GCP services. They design and operate large-scale systems using software engineering principles, and they collaborate closely with developers to improve the overall system architecture.

52. What exactly is the Google Cloud AI Platform?

Google Cloud AI Platform is a managed service that allows you to create and run machine learning models. Support for popular frameworks such as TensorFlow and PyTorch simplifies the development and deployment of machine learning models. You can use this service to train your models, and Google will manage the underlying infrastructure. This feature speeds up and improves the efficiency with which machine learning models are built and deployed.

53. What exactly is the Google Cloud Memorystore?

Google Cloud Memorystore is a service that allows you to access data quickly by using a fully managed in-memory store.

It is designed to be fast and efficient, making it ideal for applications that require quick data access.

This feature is particularly beneficial for caching, session management, and analytic purposes.

54. What exactly is Google Cloud Auto ML?

Google Cloud AutoML is a set of tools that allows you to create machine-learning models without having to be a machine-learning expert.

It includes a variety of tools for working with images, words, and structured data.

Auto ML allows you to create and use machine-learning models for data understanding and organization.

Even if you have little experience, this feature makes it easier and faster to create machine-learning models.

55.What exactly is Google Cloud Bigtable?

Google Cloud Platform Bigtable is a fully managed NoSQL database service designed for large-scale applications that require massive amounts of data storage. It offers scalable and fast storage for analytics, IoT, and machine learning workloads. This feature allows you to use Bigtable to handle massive amounts of data quickly and easily without having to worry about the underlying infrastructure. You can concentrate on your application logic while Google handles database management by leveraging Bigtable’s capabilities.

56. What exactly is Google Cloud Armor?

Google Cloud Armor is a service that assists in the protection of your web applications against online attacks. It employs a web application firewall (WAF) to prevent malicious traffic and to implement customized security policies. You can use Cloud Armor to protect your web applications from cyber threats that could cause them to become unavailable to your users. You don’t have to worry about setting up and maintaining the infrastructure to protect your applications when you use this service; Google handles that for you.

57.What is Data Loss Prevention (DLP) in Google Cloud?

Google Cloud Data Loss Prevention (DLP) offers a comprehensive set of pre-built detectors for identifying sensitive data such as personally identifiable information (PII), financial data, and intellectual property. It also includes advanced customization options for developing custom detectors and policy-based actions for enforcing data protection policies throughout the organization. Because of this feature, it is a highly effective solution for businesses looking to protect sensitive data in the cloud.

58. What exactly is the Google Cloud Deployment Manager?

Google Cloud Deployment Manager is a service that automates cloud resource deployment and management. It enables you to define your infrastructure as code and deploy and manage your resources through a simple, declarative language.

59.What exactly is Google Cloud Interconnect?

Google Cloud Interconnect is a service that assists you in connecting your corporate network to GCP. It provides several connection options, including Dedicated Interconnect, Partner Interconnect, and VPN. Dedicated Interconnect establishes a direct link between your network and GCP. Simultaneously, Partner Interconnect allows you to connect via a supported provider. VPN is a versatile and cost-effective way to connect to GCP online. Businesses can use Cloud Interconnect to connect to GCP faster and more reliably, making it easier to use cloud services alongside their existing resources. Cloud Interconnect supports BGP, VLAN, and IPSec connections.

60. What are Google Cloud Firebase Functions?

Google Cloud Functions for Firebase is a service that lets you execute code in response to Firebase events. You don’t need to manage servers or infrastructure because it’s a serverless computing service. You can use Cloud Functions to create applications that interact with Firebase services without having to worry about the backend infrastructure. This feature makes developing and deploying serverless applications easier and faster.

61.Describe the Google Cloud Video Intelligence API.

You can extract information from videos using the Google Cloud Video Intelligence API. It has features such as object tracking, explicit content detection, shot change detection, and more.

62.What Is the Difference Between Google Cloud Dataflow and Apache Beam?

Google Cloud Dataflow is an Apache Beam-based fully managed stream and batch data processing service. Apache Beam is an open-source batch and streaming data processing unified programming model.

63.What Exactly Is Google Cloud CDN?

A CDN (Content Delivery Network) is a distributed network of servers that speeds up the delivery of content to users. It caches content near end users, reducing latency and improving web application performance.

64.Describe the function of Google Cloud Endpoints.

Google Cloud Endpoints is an API creation, deployment, and management framework. It assists developers in creating scalable APIs for their applications and includes features such as authentication, monitoring, and others.

65.What Exactly Is Google Cloud Spanner?

Google Cloud Spanner is a relational database service that is globally distributed and horizontally scalable. It has high availability and strong consistency, making it suitable for mission-critical applications.

66.Describe the function of Google Cloud Identity Platform.

Google Cloud Identity Platform is an identity as a service (IDAAS) solution for securely authenticating and managing users for your applications. It supports a variety of authentication methods, including OAuth, SAML, and others.

67.What Exactly Is Google Cloud Datastore?

Google Cloud Datastore is a NoSQL document database that is highly scalable for web and mobile applications. It is intended to handle large amounts of data while maintaining high availability.

68. When Would You Use Google Cloud Speech-To-Text?

Google Cloud Speech-to-Text is a service that converts spoken language into written text using automatic speech recognition. It’s used in a variety of applications, including transcription services, voice assistants, and more.

69. Describe the function of Google Cloud Auto ML.

Google Cloud Auto ML is a machine learning product suite that enables developers with limited equipment learning expertise to train high-quality models tailored to their business requirements.

70.How Do You Manage And Monitor GCP Resources?

Stack driver, which provides monitoring, logging, and diagnostics for GCP applications, can be used. It provides you with information about the performance and health of your applications.

71.What Is Dialog Flow and How Does It Work?

Dialog flow, is a platform for natural language understanding that allows you to create and integrate conversational user interfaces into applications. It’s frequently used to create chatbots and virtual assistants.

72. Explain the function of Google Cloud in GCP.

Google Cloud Functions is a serverless computer service that enables you to run code in response to events without having to manage servers. It’s intended for event-driven, light workloads.

73.What Is Bigtable, and When Is It a Good Option for Data Storage?

Bigtable is a NoSQL database with a large number of columns. It is appropriate for applications requiring high-throughput and low-latency access to large amounts of semi-structured data.

74.Explain the function of Google Cloud in GCP.

Google Cloud Functions is a serverless computing service that enables you to run code in response to events without having to manage servers. It’s intended for event-driven, light workloads.

75.How Can You Keep Your GCP Resources Safe?

You can secure GCP resources by controlling access with

  • Identity and Access Management (IAM),
  • enabling Cloud Identity-Aware Proxy (IAP),
  • configuring firewall rules, and encrypting data at rest and in transit.

76.How Do You Configure Auto Backups For A Google Cloud SQL Database?

You can set the backup retention period and enable automatic backups in the console or using google cloud commands to configure automated backups for a Cloud SQL database.

77.Explain the function of cloud CDN in GCp?

  • A cloud CDN is a content delivery network service that speeds up the delivery of web content to users. It reduces latency and speeds up page load times.

78. What Exactly Is Cloud Pub/Sub And How Does It Work?

  • Cloud Pub/Sub is a messaging service used to build event-driven systems. It enables you to send and receive messages asynchronously between independent applications.

79.Describe the function of Google Cloud Functions in GCP.

  • Google Cloud Functions is a serverless computer service that enables you to run code in response to events without having to manage servers. It’s intended for event-driven, light workloads. The following is an example of a Cloud Function deployment:                                                                                                                       –runtime=nodejs16 –trigger-HTTP google cloud functions deploy my-function.

80. What Is Bigtable, and When Is It a Good Option for Data Storage

Bigtable is a NoSQL database with a large number of columns. It is appropriate for applications requiring high-throughput and low-latency access to large amounts of semi-structured data. Here’s an example of how to make a Bigtable instance:        my-table cbt create table

81. How do AWS Snowclone and AWS storage devices convey data?

Using the AWS Snowcone service, data is collected and handled at the source level after being collected by sensors and other devices. The data is then moved, either online or offline, onto Amazon storage devices like S3 buckets. Additionally, data sync options allow you to continuously transmit data to AWS sources. Additionally, data is sent to AWS storage devices using the AWS Snowclone service after being processed via Amazon EC2 instances.

82. What is the connection between Cloud Endure Disaster Recovery and AWS Elastic Disaster Recovery?

Since Cloud Endure Disaster Recovery is the foundation on which AWS Elastic Disaster Recovery is often built, the capabilities of both services are comparable. They help you in:

Simplify setup, use, and recovery procedures for many different programs.

Perform disaster recovery drills and testing in a non-disruptive manner.

Recover TROs in days and RPOs in seconds.

Recover from a prior period of time

83. How do Amazon RDS and Amazon VPC communicate?

Amazon DB instances can be managed by the Amazon EC2 instances, EC2-VPC and EC2-Classic. Amazon DB instances can be created in a virtual private cloud by using Amazon VPC. Controlling the virtual networking environment is also aided by it. However, Amazon RDS is in charge of software areas, backups, and automated failure detection and recovery. Operating your database instances inside an Amazon VPC can result in substantial savings in costs.

84. How is workload separation and changeability managed by Amazon Redshift?

To accomplish read workload isolation, the ETL cluster exchanges its data with segregated BI and analytics clusters. In order to save expenses, it also permits the creation of optional fees. The analytic cluster can be arranged here in accordance with the budget that is required. It also makes integrating the new workloads relatively easy.

85. How does Elastic cache from Amazon improve caching efficiency?

Throughput and latency may be reduced with Amazon ElastiCache’s in-memory caching capability. In-memory caching is especially helpful for heavy workload applications like social networking, gaming, and media sharing, as it boosts the efficiency of data access. In addition, important data fragments can be kept in memory, significantly reducing latency.

86. What Do Amazon VPC Flow Logs and Traffic Mirroring Compare?

You may monitor traffic content, payloads, discover problem causes, and prevent data misuse by using Amazon VPC traffic mirroring to get actionable insights about network traffic.

But information on traffic acceptance and rejections, source and destination IP addresses, packet and byte counts, and port details are all provided by Amazon VPC flow logs. To maximize network performance, it helps in resolving security and related concerns.

87.How Does Cloud Scheduler Help You Automate Tasks?

Cloud Scheduler enables you to automate tasks by triggering them at predetermined intervals. Here’s an example of a job that triggers a Pub/Sub message:

google cloud scheduler jobs create pub sub my-job –schedule=”0 0 * * *” –topic=my-topic –message-body=”Hello, World!”

88. What Is a Cloud Memory Store, and Why Would You Use One?

Cloud Memorystore is an in-memory data storage service that is fully managed. It is used to store frequently accessed data. Here’s an example of how to make a Memorystore instance.

89. What Is Cloud Run, and How Does It Function?

Cloud Run is a fully managed container platform that scales applications automatically based on incoming requests. An example of deploying a containerized application to Cloud Run is provided below:

–image=gcr.io/my-project/my-image –platform=managed –region=us-central1 google cloud run deploy my-service

90.Describe the function of Google Kubernetes Engine (GKE) in GCP

GKE is a managed Kubernetes service that makes it easier to deploy, manage, and scale containerized applications. The following is an example of a GKE cluster:

Container clusters in google cloud create my-cluster –number-nodes=3 –zone=us-central1-a

91. What Is the Goal of Cloud Auto ML?

Cloud Auto ML is a machine-learning product suite that enables developers with little or no machine-learning experience to train high-quality models. Here’s an example of text classification model training:

g cloud ai-platform jobs submit training my-training-job –region=us-central1 –module-name=train.py –package-path=./ –job-dir=gs://bucket-name/job-dir – –input-data=gs://bucket-name/input-data

92.Describe the function of Cloud Composer.

Cloud Composer is a workflow orchestration service that is fully managed. It allows you to create, schedule, and track workflows. Here’s an example of a DAG in Cloud Composer:

 the import DAG from airflow import DAG import datetime, timedelta

default_args = ‘owner’:’airflow’, ‘depends_on_past’: False,’start_date’: datetime(2022, 1, 1)

    ’email_on_failure’ is false; ’email_on_retry’ is false.

    ‘retries’: 1;’retry_delay’: timedelta(minutes=5);

DAG =(‘my_dag,’ default_arguments=default_arguments, schedule_interval=timedelta(days=1))

93. How Do You Set Up A CDN In GCP?

You can cache content at Google’s globally distributed edge caches using Cloud CDN. Here’s an example of how to enable Cloud CDN for a backend service:

g cloud compute backend-services –global –enable-cdn my-backend-service

94. How Do You Create A Cloud VPN In GCP?

You can create a VPN tunnel using the g cloud CLI.

Here’s an example:

vpn-tunnels vpn-tunnels vpn-tunnels vpn-tunnel 

–region=us-central1 

–peer-address=peer-ip

 –shared-secret=shared-secret create my-tunnel

95. What Is Big Query, and How Do You Use It?

BigQuery is a serverless, massively scalable data warehouse. 

To run a query with the bq CLI, follow these steps:

bq query ‘SELECT * FROM ‘project-id.dataset.table”

96. How Do You Configure VPC Peering in GCP?

To establish a peering connection, use the google cloud CLI. 

Here’s an example:

 compute networks in the cloud peering create 

my-peering –network=my-network –peer-project=peer-project-id 

–peer-network=peer-network –auto-create-routes

97. How Do You Integrate Google Cloud Platform Services Into Your App?

 A service account key file can be used for server-to-server authentication. 

Here’s an example in Python:

service_account import from google.oauth2

credentials are the same as service_account.Credentials.from_service_account_file (‘path/to/keyfile.json’, scopes= )) [‘https://www.googleapis.com/auth/cloud-platform’]

98. How Can GCP Resource Creation And Management Be Automated?

 Deployment Manager templates, which are YAML or Jinja2 files that describe the resources, can be used. An example YAML template for creating a VM is provided below Resources:

– name: my-vm; compute.v1.instance properties:

    machine type: zones/us-central1-a/machine Types/n1-standard-1 zone: us-central1-a

99. What Is Google Kubernetes Engine (GKE), and How Do You Set It Up?

You can cache content at Google’s globally distributed edge caches using Cloud CDN. Here’s an example of how to enable Cloud CDN for a backend service:

g cloud compute backend-services –global –enable-cdn my-backend-service

100. Explain the purpose of cloud functions and demonstrate how to create one.

Cloud Functions are serverless functions that are event-driven. Here’s an example of a function that’s triggered by an HTTP request:

definition

hello _world(request):

return ‘Good day, World!’

101. How Does Google Cloud Platform Handle Secrets?

Cloud Secret Manager can be used to store and manage sensitive information. Here’s an example of how to make a secret:secrets of gcloud –replication-policy=automatic create my-secret

secrets of google cloud –replication-policy=automatic create my-secret

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Frequently Asked Questions ON GCP

What is Google Cloud binary authorization?

Binary authorization is used by Cloud Run and GKE (Google Kubernetes Engine) to ensure that only trusted container images are used. Binary Authorization can be used to ensure that only trusted authorities sign images. Simultaneously, they are being built to ensure that signature validation is performed when deployed.

What exactly is Google Kubernetes?

 With the help of Google Kubernetes Engine (GKE), you can use Google’s infrastructure to deploy, manage, and scale containerized applications. The GKE environment is made up of a cluster of computers (Google Compute Engine instances).

What exactly is Google Cloud Vertex AI?

Vertex AI provides a unified set of Auto ML and AI Platform client libraries, APIs, and graphical user interfaces. Vertex AI users have access to Auto ML and can tailor their training to their specific requirements. Vertex AI lets you train models however you want, then store, deploy, and request predictions from those models. The use of pre-trained and custom tools on a unified AI platform can speed up the deployment, creation, and scaling of machine learning models. 

What types of databases are GCP compatible?

Among the database systems that can be used with GCP are MySQL, PostgreSQL, MongoDB, and Big Table.

What exactly does BigQuery mean?

BigQuery, a service provided by the Google Cloud Platform, serves as a warehouse for large businesses. The product is highly scalable and cost-effective due to its in-memory data analysis engine and machine learning capabilities. A data analytics engine allows you to perform real-time data analysis and generate insightful reports quickly and easily. Big Query can analyze data from external sources such as object storage, transactional databases, and spreadsheets in addition to internal data.