Top 30+ Cloud Computing Interview Questions and Answers

Cloud computing is evolving at a very rapid pace. Be it a fresh graduate who’s looking to get placed as a cloud engineer, a system administrator in transition to cloud, or even an experienced professional looking to get certified at an advanced level for AWS, you would require a mix of fundamental knowledge as well as practical knowledge of architecture to ace an interview for the same.

The following guide serves as a study tool to learn and review cloud computing concepts. It is a set of high-yield study notes for cloud computing interview questions and answers. Whether you are looking to prepare for a technical interview or exam for a fresh cloud engineer position or even a promotion to cloud engineer from an administrator role, and need a review of key architecture, this guide to cloud computing interview questions has you covered. These cloud computing interview questions and answers also cover all of the key concepts for popular cloud platforms, including certification for AWS, Azure, and Google Cloud (GCP).

1. What are the primary service models in cloud computing?

The services that are offered through cloud computing are categorized into three different models or types. These are typically referred to by the term cloud computing stack.

IaaS (Infrastructure as a Service): IaaS services provide virtual or physical computers over the Internet. Customers can configure the servers as needed and install the operating system of their choice. They are also responsible for the middleware and applications that run on the servers. Some examples of IaaS services are AWS EC2, Azure Virtual Machines, and Google Compute Engine.
Platform as a Service (PaaS): PaaS is what we call a type of cloud service that allows the user to get into tools and also a hardware and software platform over the Internet that in turn is used for application development. A PaaS provider supplies the underlying infrastructure and tools that are required to support the development and deployment of applications. Examples of PaaS offerings include AWS Elastic Beanstalk, Heroku, and Google App Engine from Google.
Software as a Service (SaaS): A fully functional software application offered to consumers/end users over the internet/cloud and managed by the service provider on his SaaS platform. As a consumer, you just access the application via your browser. (For instance Microsoft 365, Salesforce.com, and Google Workspace.)

Q2. Explain the different cloud deployment models.

Here are the four different cloud deployment models.
Public Cloud: Resources for computing are provided by a third party; these resources are being shared with other so-called tenants on the public internet.
Private Cloud: The infrastructure is dedicated to a single customer. Also, it may be self-hosted in the customer’s own data center or hosted by a third-party service provider.
A hybrid cloud is when you have a mix of public and private clouds. The data and applications are distributed over both and thus can be shared in both environments. Thus, the hybrid cloud offers the greatest possible flexibility regarding the deployment of applications and of data.
Multi-Cloud is when you use services from many cloud providers (for example, you may provision a compute service from Amazon Web Services and then use Microsoft Azure for analytics, which in turn breaks lock-in).

Q3. What are the key characteristics of Cloud Computing?

The five essential characteristics of cloud computing are:

On-demand self-service: The consumer can unilaterally provision or de-provision computing capabilities as needed, 24/7 and without operator intervention.
Broad network access: The capabilities are available over the network and accessed from clients (mobile phones, tablets, etc.) via standard applications.
Resource pooling: The provider’s computing resources are pooled together to serve as a shared infrastructure, which is served up to multiple consumers as a multi-tenant environment.
Rapid elasticity: Capabilities can be elastically provisioned and released to scale rapidly outward or inward to match dynamic business needs.
Measured service: Resource usage can be metered and customers can be charged accordingly for the cloud services they have used. There is no need for them to have their own servers and data center staff to manage the resources they are using. The cloud service can automatically optimize the usage of the resources it is providing to its customers.

Q4. What is the difference between scalability and elasticity?

Scalability: Ability of a system to handle increased workload by adding more resources to the system. This can be vertical (more power, CPU, RAM on a single machine) or horizontal (more machines are added to the pool of resources).
As opposed to scalability (the property of a system to scale up or scale out in response to a growing workload, which is typically a design property of a system), elasticity is the capability of a system to quickly scale up or down within minutes or seconds in order to match fluctuating work loads with available resources in real time.

Q5. What is "multi-tenancy" in cloud computing?

Multi-tenancy is a cloud computing architecture where one instance of a software application (or even physical infrastructure) is serving multiple customers, also known as tenants. Each tenant has his own data, which is isolated from the data of other tenants. Other tenants are not able to see data of other tenants even though they all are sharing the same computing resources, same data center, or same database.

Q6. What is the difference between a Region and an Availability Zone (AZ)?

A region is a geographical area where multiple isolated data centers (also called servers) are located within. Each region is made up of many availability zones (data centers). For example, us-east-1 is in Northern Virginia, and eu-west-1 is in Ireland.
Availability Zone (AZ): Refers to one or more data centers with redundant power, networking, and connectivity within a region. Each AZ is designed to operate independently, allowing for workloads to be placed in different locations to ensure that a failure in one location does not affect another location within the same region. An example would be to have a primary website in one AZ and a disaster recovery site in another AZ within the same region.

Q7. Explain edge computing and how it differs from cloud computing.

While in cloud computing, data is processed on remote servers, which may be a great distance from the end user, in edge computing, data storage and processing are brought closer to the point of need (the “edge” of the network, near the user or IoT devices). Edge computing reduces latency, conserves bandwidth, and enables real-time data processing.

Q8. What is a content delivery network (CDN), and how does it work?

A CDN is a geographically distributed network of proxy servers and data centers. It caches static content (like images, videos, HTML, and JavaScript files) at edge locations near to end users. When a user requests for a file the CDN serves it from the nearest edge server thus reducing latency and page load times. Examples include AWS CloudFront.

Q9. What is microservices architecture, and why is it preferred in the cloud?

Microservices architecture is a design that breaks down a single application into a set of small, independent services that together make up the full application. Each service runs in its own process and communicates with the others using lightweight protocols (like HTTP REST APIs or gRPC). It is a preferred option in the cloud for its ability to:.

Independent implementation and scaling of specific pieces. Fault isolation (if a microservice goes down, the entire application does not). Continuous integration and continuous delivery pipelines.

Q10. What is Serverless Computing? Is there really no server?

Serverless computing (also Function as a Service, FaaS) we see as a cloud model which is dynamic in its use of the servers. Of course there are servers which run the show, but they are out of the developer’s picture. At the end of the day you just code up your application (functions) and pay for the exact amount of time and resources your code uses during execution which means no payment for when your code is not running. Examples include AWS Lambda, Azure Functions, and Google Cloud Functions.

Q11. What is a Virtual Private Cloud (VPC) virtual network (VNet)?

A VPC (in AWS/GCP) or VNet (in Azure) is an isolated, private logical network carved out within a public cloud provider's infrastructure. It gives you complete control over your virtual networking environment, including selecting your own IP address ranges, creating subnets, configuring route tables, and setting up network gateways.

Q12. Describe the fundamental differences between security groups and network access control lists (NACLs).

Similar to Security Groups, Network Access Control Lists (NACLs) are used to secure network traffic, however they function at a different level.

Q13. What is the Shared Responsibility Model?

He Shared Responsibility Model. Security OF the Cloud (provided by the cloud provider) and Security IN the Cloud (configured and managed by the customer).

Security OF the Cloud: The cloud provider is responsible for security of the global infrastructure that supports all the cloud provider’s services (e.g., hardware, physical security of data centers, network, and virtualization software).
In cloud computing, everything customers put into the cloud is their responsibility to configure and manage, e.g., their operating systems, network configurations, their Identity and Access Management (IAM) functions, encrypting their data, and managing their application’s code.

Q14. What is IAM (Identity and Access Management)?

The Identity and Access Management (IAM) service is a web service framework that makes it easier for you to securely control access to your cloud-based resources. The service enables you to manage identity and access to resources in your organization by creating and managing users and groups and then creating permissions for those users and groups to use resources. The users, groups, and permissions are created as identities, which are then used to grant access to resources such as EC2 instances, S3 buckets, and RDS instances. By managing identities and their corresponding permissions, you can help to keep your resources and data secure. It is recommended that you follow the Principle of Least Privilege (PoLP) when granting permissions to identities to complete tasks. This means that you grant the minimum set of permissions required to complete a task. For example, instead of granting read/write access to an EC2 instance, you grant only write access to complete the required task.

Q15. How do you protect data at rest vs. data in transit in the cloud?

Data at Rest: This refers to data that has been uploaded to cloud storage such as Amazon S3 or physical disks in a cloud provider’s data center. At rest, data is typically protected using symmetric encryption, i.e., using the same password/key for encryption and decryption. This data is managed by services such as AWS KMS or Azure Key Vault for the creation and management of encryption keys.
Data in Transit: The data traveling from system to system to system via networks, i.e., over the internet or within an organization’s internal network. Data in transit is protected using the same type of cryptography that’s used for data at rest but via cryptographic transport protocols (i.e., TLS/SSL) or via a VPN (Virtual Private Network) that connects securely to the remote resources.

Q16. What is the difference between Block Storage, Object Storage and File Storage?

Block Storage: Block storage stores data in the form of a series of fixed-size blocks. Each block has a unique address, similar to a hard drive that is unformatted. It’s attached to a server and it’s very, basically, an unformatted physical hard drive, and that’s why it offers ultra-low latency. Block storage is provided by AWS EBS, by Azure Disk, by Google Block Storage.
There are three primary forms of cloud storage; Block, Object and File. Object Storage: Data is stored in objects (e.g. a .jpg, mp3 etc) which are stored along with the metadata for that object. A unique identifier is created for the object which can then be used to access that object over APIs. (Examples of Object Storage are AWS S3, Azure Blob, Google Cloud Storage).
File Storage: A hierarchical folder-and-file structure is used to store data. It is very easy to access File Storage from multiple compute instances, all using standard protocols like NFS or SMB. Examples for File Storage are AWS EFS or Azure Files.

Q17. When would you go for a NoSQL DB System over a Relational DB System in the cloud.

Relational databases (e.g., Amazon RDS, Azure SQL) should be used for highly structured data that requires strict ACID (Atomicity, Consistency, Isolation, Durability) support. Relational databases are also appropriate for complex relational queries and large transaction-based workloads such as those found in banking applications. NoSQL databases (e.g., Amazon DynamoDB, MongoDB, Azure Cosmos DB) should be used for unstructured or semi-structured data, where high scalability and large throughputs are required. NoSQL databases also support ultra-low latency read and write operations for large amounts of data.Use NoSQL databases (such as Amazon DynamoDB, MongoDB or Azure Cosmos DB) for unstructured or semi-structured data. A NoSQL database supports flexible, dynamic data structures and thus supports a high scale-out performance. Its read and write performance for large data sets is also extremely fast.

Q18. What is an ephemeral drive?

An ephemeral drive also known as instance store which provides temporary block level storage for a virtual machine instance. The data on an ephemeral drive is only available as long as the associated instance is running. In the event of the instance being stopped, terminated or in the case of a hardware failure all data on that drive is lost. It is used for caching, scratch pads, and swap space.

Q19. What is Infrastructure as Code (IaC) and what are its benefits?

Infrastructure as Code is a practice that which you write out machine-readable config files or scripts to manage your cloud infrastructure, which is a change from the past of physical hardware config and interactive config tools.

Benefits include:.

Consistency: Reduces human error and configuration drift in dev, stage and prod envs.
Version Control: Use of Git for file tracking that also includes pull requests, history tracking, and rollbacks. Popular tools are Terraform, AWS CloudFormation, and Ansible.

Q20. Explain the concepts of Blue/Green Deployment and Canary Deployment.

In a Blue deployment we have the present live traffic running in the “Blue” environment while at the same time we deploy and test the new software release in the “Green” environment.Once we are fully satisfied, we route traffic from Blue to Green instantaneously via a load balancer or DNS switch. In the event of an issue, we are able to instantly roll back to Blue.

Canary Deployment: We roll out the new app version to a very small segment of the infrastructure or users (for instance 5%. We watch its performance and error rates. If all goes well we gradually route more traffic to the new version until it fully replaces the old version.

Q21. What is configuration drift, what is its cause, and how do you mitigate it?

Configuration drift is when team members make ad hoc manual changes to live cloud resources, which in turn causes the present state of the cloud to differ from what is defined in the infrastructure code. This is prevented by removing manual write access to production envs, forcing all changes to go through continuous deployment pipelines, and using tools like Terraform or AWS Config for automated drift detection.

22. What is the function of a load balancer in a cloud architecture?

A load balancer which is a component that puts out going application traffic at the incoming requests across many backend targets (which may be EC2 instances, containers, or IP addresses) thus no single server gets overloaded. It also increases application availability and enables fault tolerance which it does by that of performing health checks and taking down unhealthy targets from rotation until they are fixed.

Q23. A high-traffic application suffers from periodic, unpredictable traffic spikes that crash the backend servers. How would you redesign this architecture to be fault-tolerant and elastic?

To solve it I would separate out and scale the architecture by these steps:.

Implement an Auto Scaling Group: Configure compute resources for horizontal scaling out or in based on metrics such as CPU usage or target tracking requests.
Use a Load Balancer (ALB): Put an Application Load Balancer in front of the instances to even out traffic flow and handle TLS termination. Add a Message Queue: Break the front end from the back end with a messaging queue service like AWS SQS or RabbitMQ. What happens is that the queue is filled with incoming requests, and the back-end instances pull from the queue, which in turn allows the back end to process at a steady rate instead of breaking under sudden increases. Put in a Cache: Add an in-memory data store cache like Redis or Memcached (for example, Amazon ElastiCache) to reduce redundancy.

Q24. What is a "cloud migration strategy"? Briefly explain the "6 Rs" of migration.

A cloud migration strategy is what an organization uses to transition its on-prem digital assets to the cloud. The six standard approaches are:.

Rehost (Lift and Shift): Moving applications to the cloud in their present form with no architectural changes. Replatform
(Tweak, Tune, and Transform): Doing minor application improvements during the move to the cloud, which also brings in the use of cloud features (e.g., shifting a self-hosted DB to a managed service).
Refactor Re-architecture: Full rewrite of the application to take in native cloud features, which may include serverless or microservices. Retain: Leaving applications on-premise, which is done when it is found the apps do not require cloud migration.

Q25. What is data replication, and what is the difference between synchronous and asynchronous replication?

Writes data to primary storage and also to the replica at the same time. Write operation is only confirmed to the app once both sites have reported back. This is for zero data loss, which in turn introduces some write latency at a distance. Asynchronous Rep: Writes data out to the primary storage first and right away reports back to the application that it is done. The data is then mirrored to the secondary replica with a short delay. It gives better performance but has a slight risk of data loss if the primary site goes down before the data is fully mirrored.

Q26. How do you optimize cloud spend? Describe cost optimization strategies.

Cloud cost reduction is a matter of assessing and tuning your footprint, which in turn minimizes unnecessary spending. We see:.

Right-sizing: Analyzing performance metrics and reducing the number of underutilized virtual instances. Using Committed Use Models: We use options like AWS Reserved Instances (RIs) or Savings Plans that give up to 72% off of on-demand prices in trade for a long-term commitment of your capacity to a service for 1 or 3 years. Also, we use Spot Instances for stateless batch processes that are not mission critical and can be interrupted by the provider at any time we see fit, which gives us up to 90% off. We have put in place auto-scheduled shutoffs of nonproduction, development, and staging environments at nights and over the weekend.

Q27. What is a container, and how is it different from a Virtual Machine (VM)?

Virtual Machines: Include a full guest OS, virtual versions of physical hardware, and application code. We present them on a physical server which is managed by a hypervisor. VMs boot in minutes and are very resource intensive.
Containers: Use the host’s OS kernel instead of fully allocating a new one. They put the application code with only its required system dependencies (libraries and bins). Containers are very lightweight, do a great job of isolating processes, boot in a matter of milliseconds, and we see high portability in hybrid and multi-cloud systems.

Q28. What is Kubernetes (K8s)?

Kubernetes is a free-to-use container orchestration platform, which we have put together for the deployment, scaling, management, and networking of containerized applications at a large scale. It manages groups of containers, also takes care of self-healing (restarting failed containers), and does service discovery as well as load balancing across cluster nodes.

Q29. Explain the concept of "Chaos Engineering" in cloud systems.

Engineering is the practice of putting your software system to the test in a live environment by introducing artificial failures (for instance, turning off an availability zone, terminating random instances, or adding to the network latency). The goal is to proactively find out the architectural break points, which may not be obvious, and to make sure the cloud infrastructure does break under real-world doomsday scenarios but does not bring the whole system down.

Q30. What is a cloud-native application?

"Cloud-native application" is a term for software that we design with a cloud computing environment in mind. As opposed to legacy monolithic models that we adapt to the cloud, cloud-native applications are built from the ground up using microservices, packaged in small portable containers, managed with the use of dynamic orchestration platforms like Kubernetes, and put out into production using continuous deployment practices.