2023's Most Common Cloud Computing Interview Questions - IQCode's Top Picks

Introduction to Cloud Computing

Cloud computing is a method of sharing computing resources that include applications, storage, networking, development and deployment platforms, and business processes. By providing standardization and automation, cloud computing makes computing resources more accessible and easier to employ.

It's important to note that "cloud" does not refer to just one cloud. Instead, it symbolizes the Internet, which is a network of networks. Additionally, it's worth noting that not all types of remote computing are considered cloud computing.

Cloud Computing Interview Questions for Entry-Level Candidates

    1. What is cloud technology?

Key Features of Cloud Computing

Cloud computing offers numerous features such as:

  1. Scalability: It enables users to scale up or down the computing resources based on their requirements.
  2. Flexibility: Cloud computing provides the flexibility to access applications or data from anywhere via the Internet.
  3. Cost-effectiveness: Users only need to pay for the resources they use, saving them money on hardware and maintenance costs.
  4. Reliability: Cloud computing offers high availability and uptime by distributing resources across multiple servers.
  5. Security: Cloud providers implement stringent security measures to protect data against unauthorized access or breaches.
// Sample code for scaling resources in AWS
// Create an Amazon EC2 Auto Scaling group
aws autoscaling create-auto-scaling-group --auto-scaling-group-name my-asg --launch-configuration-name my-launch-config --min-size 1 --max-size 10 --vpc-zone-identifier subnet-12345678

// Update an Amazon EC2 Auto Scaling group to increase the maximum size
aws autoscaling update-auto-scaling-group --auto-scaling-group-name my-asg --max-size 20


Cloud delivery models refer to the ways in which cloud computing services are provided to users. There are three main models: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).

SaaS is a model where a third-party provider hosts applications and makes them available to customers over the internet. PaaS is a model where a provider offers a platform for customers to develop, run and manage their own applications, without having to worry about the underlying infrastructure. IaaS is a model where a third-party provider hosts virtualized computing resources, including servers, storage and networking, and makes them available to customers over the internet.

What Are the Different Versions of the Cloud?

The cloud has several different versions, including:

    <li>Public cloud: A third-party provider hosts and manages the infrastructure and services, which are accessible over the internet by multiple customers.</li>
    <li>Private cloud: A cloud hosted within an organization’s own infrastructure and is not shared with other organizations. It can be managed by the organization itself or a third party.</li>
    <li>Hybrid cloud: A combination of public and private cloud, allowing applications and data to be shared between them.</li>
    <li>Community cloud: A cloud shared by multiple organizations with common concerns, such as security or compliance, that can be managed by the organizations themselves or a third party.</li>

Each of these versions has its own advantages and disadvantages. Organizations should carefully consider their needs and objectives before deciding which version(s) to use.

Main Components of the Cloud Ecosystem

In the cloud ecosystem, some of the main constituents include cloud service providers, users, developers, and third-party vendors. These constituents work together to create a cloud computing environment that allows for the deployment and management of various applications over the internet. Additionally, cloud infrastructure such as servers, storage, databases, and networking play a crucial role in supporting the cloud ecosystem. Together, these components enable businesses and organizations to access computing power, storage, and other resources on-demand, making the cloud a highly scalable and flexible technology solution.

Identifying Cloud Consumers in a Cloud Ecosystem

In a cloud ecosystem, the cloud consumers can be classified into two categories:

  1. Individual Consumers: These are individual users who use cloud services to access and store their personal data such as photos, videos, and documents.
  2. Enterprise Consumers: These are organizations or businesses that use cloud services to store and manage their data, run their applications and software, and access cloud-based resources that can help them operate and grow their businesses efficiently.

The cloud ecosystem also includes cloud providers who offer different cloud services to the consumers, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

It is important for both individual and enterprise consumers to carefully evaluate their cloud needs and choose the appropriate cloud service provider that can meet their specific requirements in terms of security, performance, scalability, and cost-effectiveness.

Identifying the Direct Customers in a Cloud Ecosystem

In a cloud ecosystem, the direct customers are typically the individuals or organizations who purchase or subscribe to cloud services directly from the cloud service provider. These customers have a direct relationship with the provider and are responsible for paying for the services they use. Examples of direct customers in a cloud ecosystem include businesses, government agencies, and individual consumers. It's important to distinguish direct customers from indirect customers, who may use cloud services but do not have a direct relationship with the provider.

Cloud Service Providers in a Cloud Ecosystem

In a cloud ecosystem, cloud service providers are companies or organizations that offer cloud computing services. These can include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) providers. Some examples of cloud service providers are Amazon Web Services, Microsoft Azure, Google Cloud Platform, and IBM Cloud. These providers offer various services and solutions to individuals and businesses looking to use cloud computing technology.

Overview of Cloud Computing Architecture

Cloud computing architecture is the structure of a software application that is hosted on remote servers and accessed via the internet. It involves the use of multiple servers, networks, and components that work together to provide a flexible and scalable environment for running applications.

The key components of cloud computing architecture include:

  • Front-end Platform: This is the part of the application that users interact with, which includes the user interface and client-side logic.
  • Back-end Platform: This includes the cloud infrastructure, servers, databases, and other tools that support the front-end platform.
  • Cloud-based Delivery: This is the process of delivering the application to users over the internet, often using a cloud service provider like Amazon Web Services, Google Cloud, or Microsoft Azure.
  • Cloud-Based Services: These are the services offered by cloud providers that enable developers to build, test, and deploy their applications in the cloud.

Cloud computing architecture offers several benefits over traditional, on-premises infrastructure. It is highly scalable, flexible, and cost-effective, making it an attractive option for businesses of all sizes. By leveraging cloud-based services and resources, organizations can reduce their capital expenditures on hardware and infrastructure, while still accessing the compute resources needed to run their applications.


In general, cloud storage can be classified into three levels:

1. Object Storage: Cloud storage that stores data in the form of objects, each with its unique identifier. This level of storage is suitable for storing large and unstructured data.

2. Block Storage: Cloud storage that basically works like an external disk drive, where data is stored in fixed-sized blocks and can be accessed by a server. This level of storage is suitable for storing critical business data that requires high-speed data transfer.

3. File Storage: Cloud storage that basically works like a traditional file server, where data is stored in a hierarchical file system. This level of storage is suitable for storing and sharing data that is organized in a specific way such as files and directories.


One of the potential questions that may be asked during a cloud computing interview for experienced professionals is:

11. What are serverless components in cloud computing?

Serverless components in cloud computing refer to a type of cloud architecture where the cloud provider manages the infrastructure and automatically allocates resources as needed, without the need for the user to manage the server. This eliminates the need for physical servers or virtual machines, and the user only pays for the actual usage of the resources. Examples of serverless components include AWS Lambda and Azure Functions.

// Example of using AWS Lambda serverless component
exports.handler = function(event, context, callback) {
    console.log('Hello, World!');
    callback(null, 'Success');

// In this example, the AWS Lambda function triggers when an event occurs, such as when a new file is uploaded to an S3 bucket. The function logs a message and returns a success response to the client.

Advantages and Disadvantages of Serverless Computing

Serverless computing is a model of cloud computing where the cloud provider manages the infrastructure and automatically allocates resources as needed. Here are some advantages and disadvantages of serverless computing:


  • Cost-effective: Serverless computing allows users to pay only for the exact amount of resources used, which can lead to cost savings and more efficient resource allocation.
  • Scalability: The cloud provider automatically handles scaling based on the workload, allowing applications to handle high traffic without manual intervention.
  • Reduced Operations: Serverless computing reduces operational overhead since the cloud provider handles infrastructure management and patching of servers software
  • Increased developer productivity: With serverless computing, developers can focus on writing code rather than managing cloud infrastructure


  • Cold-start issues: Since serverless functions are ephemeral, the first request to a function can experience a delay as the cloud provider spins up resources to handle the traffic
  • Vendor lock-in: Serverless functions can be specific to a certain vendor’s architecture, which can make the transition to another provider or an on-premises solution difficult
  • Limited control: Developers have limited control over the underlying infrastructure and may not be able to customize certain aspects of the hardware or software stack
  • Debugging issues: Debugging in serverless architectures can be hard because of the lack of visibility into the underlying infrastructure


Serverless architecture can be beneficial in many cases, but it is not a one-size-fits-all solution. It's essential to consider the advantages and disadvantages of serverless computing carefully before choosing it for your project.

// Example function for AWS serverless architecture 

Cloud-Enabling Technologies Explained

Cloud-enabling technologies refer to tools and techniques that allow businesses and individuals to leverage cloud computing to its fullest potential. These technologies include virtualization, automation, orchestration, containerization, and software-defined networking. By utilizing these technologies, users can create, manage, and scale cloud-based applications and services with greater ease and efficiency. Cloud-enabling technologies are vital to the success of cloud computing and its ongoing evolution.

Understanding Microservices Architecture

Microservices is an architectural style that structures an application as a collection of small, autonomous services each running in its own process. These services communicate with each other through APIs, typically RESTful APIs, and they are designed around business capabilities. Each microservice is responsible for performing a single task and working together with other microservices to deliver a larger application.

The microservices architecture provides benefits such as scalability, resilience, and flexibility. It allows teams to develop, deploy, and scale services independently, making it easier to deliver applications faster. Furthermore, errors in one service do not cascade to the entire application, improving overall reliability.

Microservices are commonly implemented using containers such as Docker and managed through orchestration tools like Kubernetes. These tools provide automation and simplify deploying and managing large numbers of microservices.

In summary, microservices architecture is a software development approach that breaks down applications into small, independent services, allows for greater flexibility and scalability, and improves overall reliability.

Importance of Microservices in a True Cloud Environment

In a true cloud environment, microservices play a crucial role in ensuring scalability, flexibility, and resilience of applications. Microservices architecture breaks down complex applications into smaller, independent services that work together to form the application. Each service can be developed, deployed, and scaled independently. This modularity allows for greater agility in responding to changing business needs and enables continuous delivery and deployment. Additionally, microservices allow for better resource utilization and cost efficiency by enabling automatic scaling based on usage patterns. Overall, microservices provide the necessary infrastructure for building and running modern cloud-native applications.

What is the Cloud Usage Monitor?

The Cloud Usage Monitor is a tool used to track the utilization of cloud resources such as virtual machines, databases, and storage. It helps organizations to monitor their cloud usage and optimize resource allocation, cost management, and ensure that they are staying within their budget. This tool also provides insights into trends over time, which allows businesses to make informed decisions about their cloud infrastructure usage.

How does the monitoring agent track cloud usage?

The monitoring agent tracks cloud usage by regularly collecting data from various cloud resources such as virtual machines, storage accounts, and databases. It analyzes this data to provide insight into resource utilization, system performance and other critical metrics. The monitoring agent can also use APIs provided by cloud service providers to access data about resources and their usage. By monitoring cloud usage, the monitoring agent can help organizations optimize their cloud resources, improve performance, and prevent cloud cost overruns.

Monitoring Cloud Usage with Resource Agent

The Resource Agent monitors cloud usage by regularly checking the status and activity of the resources being used in the cloud environment. It collects and analyzes data on resource utilization, user behavior, and system performance, among other factors, to identify potential issues, optimize resource allocation, and ensure efficient use of resources. The Resource Agent also generates reports and alerts to notify administrators of any irregularities or potential problems, enabling them to take action quickly and proactively.

Monitoring Cloud Usage with Polling Agents

To monitor cloud usage, the polling agent continuously collects data on various metrics related to cloud resources such as CPU usage, network traffic, storage consumption, and more. The data is then analyzed to identify trends and anomalies that could indicate performance issues or resource limitations.

The polling agent can be configured to monitor specific resources or entire cloud environments, depending on the needs of the organization. It can also be set to trigger alerts or automated actions when certain thresholds are met, such as scaling up or down resources as needed.

By using polling agents to monitor cloud usage, organizations can gain insight into their usage patterns, optimize resource allocation, and proactively address any performance issues before they impact users.

Understanding Cloud-Native Applications

Cloud-native applications are software programs designed to take full advantage of cloud computing platforms. These applications are built using microservices architecture and containerization, allowing for easy scaling and deployment across different cloud environments.

Unlike traditional applications, cloud-native applications are developed and optimized to run in the cloud from the outset. They are designed to be highly resilient, scalable, and flexible, and can be quickly adapted based on changing user demands.

Cloud-native applications are also highly portable and can run on any cloud infrastructure or even on-premises data centers. They enable DevOps teams to accelerate delivery and innovation by breaking down large monolithic applications into smaller modular services that can be developed and deployed in parallel. Overall, cloud-native architecture provides many benefits, including cost savings, improved performance, and faster go-to-market times, making it an essential part of modern software development.

Definition of Cloud-Native Applications by the Cloud Native Computing Foundation

According to the Cloud Native Computing Foundation (CNCF), cloud-native applications are built and deployed as microservices, packaged in containers, and dynamically orchestrated across distributed infrastructures. They are designed to be resilient, scalable, and highly available.

In simpler terms, a cloud-native application is an application that is specifically designed to operate in a cloud computing environment. It is built using cloud-native technologies, which allows it to take full advantage of the benefits of cloud computing, including agility, scalability, and reliability.

Overall, the CNCF believes that cloud-native applications offer significant advantages over traditional monolithic applications, including improved flexibility, faster delivery times, and better overall performance.

What is Edge Computing?

Edge computing refers to the process of performing data processing and storage on devices located near the source of the data, rather than transferring the data to a centralized computing location such as a server or cloud. This approach allows for faster data analysis, reduced latency, and improved efficiency, as well as improved security and privacy by keeping sensitive data closer to its source and limiting exposure to external networks. Edge computing is increasingly important in industries such as healthcare, finance, manufacturing, and transportation, where real-time data analysis and decision making are critical.

Understanding the Concept of API Gateway

An API Gateway refers to a server that sits between the request coming from your client's app and your backend services. It is a crucial component in modern application development as it simplifies the client-server communication by handling tasks such as load balancing, internal routing, and security.

It acts as an entry point to all your microservices, which means that any requests coming into your application from the client-side must pass through the API Gateway. The API Gateway then resolves the request and passes it to the appropriate microservice. By doing so, you create a unified point of access to all your application services.

Using an API Gateway helps in enhancing security, scalability, and observability while allowing developers to manage and govern the traffic to the services. It reduces the complexity of the application and provides a single point of entry to all the APIs in your application. Hence, it is a crucial component to manage your API-based application effectively.


Rate limiting refers to the technique of limiting the number of requests an API client can make to an API at a given time. This is done to protect the API server from being overwhelmed by too many requests and to ensure fair usage of the API among all clients. In other words, rate limiting helps to prevent abuses and ensure a high level of availability and reliability for an API service.

Understanding Encapsulation in Cloud Computing

Encapsulation is a concept in cloud computing that involves wrapping data and the methods that operate on that data into a single unit to prevent outside interference and manipulation. This means that private data and functions are hidden from external users and can only be accessed through designated interfaces.

In cloud computing, encapsulation is important for security and privacy reasons. By encapsulating data and functionality, cloud providers can protect their users' data and prevent unauthorized access. Encapsulation also allows for easier maintenance and updates, since changes can be made to the encapsulated unit without affecting other parts of the system.

Overall, encapsulation is a vital aspect of cloud computing that helps ensure the security, privacy, and stability of cloud-based systems.

Various Datacenters for Cloud Computing Deployment

In cloud computing, different types of datacenters are deployed for various purposes, such as:

- Regional Datacenters

Regional datacenters are designed to serve specific geographical regions. They host cloud services that are intended for use in a particular location. This kind of datacenter helps maintain low latency and quick response times.

- Enterprise Datacenters

Enterprise datacenters are privately owned and managed by organizations. They are used to host cloud services for internal use or for external customers. These datacenters can be either on-premise or off-premise.

- Co-location Datacenters

Co-location datacenters are datacenters where multiple customers share space and network connectivity. They can either be managed or unmanaged by the colocation provider. In this kind of datacenter, customers rent space, power, and cooling for their IT equipment.

- Hyperscale Datacenters

Hyperscale datacenters are large-scale datacenters that host cloud services that require massive computing power and storage. They are highly automated and have the ability to scale quickly to meet the demand of the cloud services they host.

What are Containerized Data Centers?

Containerized data centers, also known as modular data centers, are pre-fabricated units that are designed for quick deployment and mobility. These units can be transported and deployed virtually anywhere, making them useful for areas with limited infrastructure or for disaster recovery situations. They contain all the necessary components of a traditional data center, such as servers, storage systems, and networking equipment, but are housed within a single, scalable and modular unit. Containerized data centers are becoming increasingly popular due to their flexibility, energy efficiency, and cost savings over traditional data center solutions.

Low-Density Data Centers Explained

A low-density data center refers to a facility that employs a lower power density design as opposed to traditional high-density data centers. This means that the low-density data centers use less energy to power their computing hardware and are configured to operate at a lower temperature. The lower power density design results in lower electricity bills which can translate to significant cost savings over time. Low-density data centers are also quieter due to fewer servers and cooling equipment, making them ideal for businesses that require a less noisy environment.

Common Issues with Cloud Computing

Cloud computing has become increasingly popular in recent years, but it is not without its challenges. Here are some of the common issues that organizations may face when using cloud computing:

1. Security concerns - since sensitive data is hosted on third-party servers, there is always a risk of data breaches.

2. Limited control - organizations may not have complete control over their data and applications when they are hosted on the cloud.

3. Downtime - if the cloud service experiences an outage, it may impact businesses' operations, causing downtime and loss of revenue.

4. Compatibility issues - some cloud services may not be compatible with certain applications or operating systems, which can limit their usefulness.

5. Cost - while cloud computing can be cost-effective in the long run, some organizations may find it expensive to migrate their data and applications to the cloud.

Despite these challenges, cloud computing can offer numerous benefits to organizations, including increased flexibility, scalability, and efficiency. Ultimately, the decision to use cloud computing should be carefully evaluated and weighed against a company's unique needs and priorities.


<p>Cloud computing has become increasingly popular in recent years, but it is not without its challenges. Here are some of the common issues that organizations may face when using cloud computing:</p>

<li>Security concerns - since sensitive data is hosted on third-party servers, there is always a risk of data breaches.</li>
<li>Limited control - organizations may not have complete control over their data and applications when they are hosted on the cloud.</li>
<li>Downtime - if the cloud service experiences an outage, it may impact businesses' operations, causing downtime and loss of revenue.</li>
<li>Compatibility issues - some cloud services may not be compatible with certain applications or operating systems, which can limit their usefulness.</li>
<li>Cost - while cloud computing can be cost-effective in the long run, some organizations may find it expensive to migrate their data and applications to the cloud.</li>

<p>Despite these challenges, cloud computing can offer numerous benefits to organizations, including increased flexibility, scalability, and efficiency. Ultimately, the decision to use cloud computing should be carefully evaluated and weighed against a company's unique needs and priorities. </p>

Resource Replication in Cloud Computing

Resource replication in cloud computing refers to the process of duplicating resources or data across multiple locations in a cloud infrastructure to ensure high availability and fault tolerance. This is done to prevent potential downtime or data loss in case of a hardware failure or other unforeseen circumstances.

Cloud providers typically use a variety of techniques to replicate resources, including data mirroring, backup and recovery, and load balancing. These techniques allow cloud users to access resources and data from multiple locations, ensuring that they are always available and accessible.

Resource replication is an essential feature of cloud computing and is critical for ensuring high levels of reliability, scalability, and performance for cloud-based applications and services. By replicating resources and data across multiple locations, cloud providers can ensure that their customers have access to the resources and data they need, regardless of their location or the state of the underlying hardware.

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