Cloud Computing Interview Questions Preparation Course

Cloud Computing is the latest trend in Software Architecture. This course covers the important questions on Cloud Computing architecture that may be asked in technical interview for Software professionals.

Many fortune 500 organizations use Cloud Computing. Therefore, Cloud Computing is also a very important topic in technical interview. This course contains basic to expert level Cloud Computing interview questions that an interviewer asks. Each question is accompanied with an answer so that you can prepare for job interview in short time.

Often, these questions and concepts are used in our daily programming work. But these are most helpful when an Interviewer is trying to test your deep knowledge of Cloud Computing concepts.

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How will this course help me?

By attending this course, you do not have to spend time searching the Internet for Cloud Computing interview questions. We have already compiled the list of the most popular and the latest Cloud Computing Interview questions.

Are there answers in this course?

Yes, in this course each question is followed by an answer. So you can save time in interview preparation.

What is the best way of viewing this course?

You have to just watch the course from beginning to end. Once you go through all the videos, try to answer the questions in your own words. Also mark the questions that you could not answer by yourself. Then, in second pass go through only the difficult questions. After going through this course 2-3 times, you will be well prepared to face a technical interview in Cloud Computing topic.

What is the level of questions in this course?

This course contains questions that are good for a Fresher to an Architect level. The difficulty level of question varies in the course from a Fresher to an Experienced professional.

What are the sample questions covered in this course?

Sample questions covered in this course are as follows:

  1. What are the benefits of Cloud Computing?
  2. What is On-demand computing in Cloud Computing?
  3. What are the different layers of Cloud computing?
  4. What resources are provided by Infrastructure as a Service (IAAS) provider?
  5. What is the benefit of Platform as a Service?
  6. What are the main advantages of PaaS?
  7. What is the main disadvantage of PaaS?
  8. What are the different deployment models in Cloud computing?
  9. What is the difference between Scalability and Elasticity?
  10. What is Software as a Service?
  11. What are the different types of Datacenters in Cloud computing?
  12. Explain the various modes of Software as a Service (SaaS) cloud environment?
  13. What are the important things to care about in Security in a cloud environment?
  14. Why do we use API in cloud computing environment?
  15. What are the different areas of Security Management in cloud?
  16. What are the main cost factors of cloud based data center?
  17. How can we measure the cloud-based services?
  18. How a traditional datacenter is different from a cloud environment?
  19. How will you optimize availability of your application in a Cloud environment?
  20. What are the requirements for implementing IaaS strategy in Cloud?
  21. What is the scenario in which public cloud is preferred over private cloud?
  22. Do you think Cloud Computing is a software application or a hardware service?
  23. Why companies now prefer Cloud Computing architecture over Client Server Architecture?
  24. What are the main characteristics of Cloud Computing architecture?
  25. How databases in Cloud computing are different from traditional databases?
  26. What is Virtual Private Network (VPN)?
  27. What are the main components of a VPN?
  28. How will you secure the application data for transport in a cloud environment?
  29. What are the large-scale databases available in Cloud?
  30. What are the options for open source NoSQL database in a Cloud environment?
  31. What are the important points to consider before selecting cloud computing?
  32. What is a System integrator in Cloud computing?
  33. What is virtualization in cloud computing?
  34. What is Eucalyptus in a cloud environment?
  35. What are the main components of Eucalyptus cloud architecture?
  36. What is Auto-scaling in Cloud computing?
  37. What are the benefits of Utility Computing model?
  38. What is a Hypervisor in Cloud Computing?
  39. What are the different types of Hypervisor in Cloud Computing?
  40. Why Type-1 Hypervisor has better performance than Type-2 Hypervisor?
  41. What is CaaS?
  42. How is Cloud computing different from computing for mobile devices?
  43. Why automation of deployment is very important in Cloud architecture?
  44. What are the main components in Amazon Cloud?
  45. What are main components in Google Cloud?
  46. What are the major offerings of Microsoft Azure Cloud?
  47. What are the reasons of popularity of Cloud Computing architecture?
  48. What are the Machine Learning options from Google Cloud?
  49. How will you optimize the Cloud Computing environment?
  50. Do you think Regulations and Legal Compliance is an important aspect of Cloud Computing?

What are the requirements?

Software Development or Operations Experience
Familiarity with Software Applications in an organization

What am I going to get from this course?

Understand Cloud Computing Components and Models
Learn important concepts of Cloud Computing
Understand benefits of Cloud Computing
Answer interview questions on Cloud Computing
Cloud Computing offerings from Google, Amazon and Microsoft
Demand higher salary or promotion based on the knowledge gained

What is the target audience?

Software Engineer, Sr. Software Engineer, Member Technical Staff, Expert
DevOps Engineer, Operations Engineer
Software Architect, Development Manager, Director
Anyone who wants to learn Cloud Computing architecture

Join the Cloud Computing Interview Preparation Course for Special Discount today!!

What are main components in Google Cloud?

Google is a newer cloud alternative than Amazon. But Google provides many additional features than AWS. Some of the main components of Google Cloud are as follows:

  • Compute Engine: This component provides computing power to Google Cloud users.
  • Cloud Storage: As the name suggests this is a cloud storage solution from Google for storing large files for application use or just serving over the Internet.
  • Cloud Bigtable: It is a Google proprietary database from Google in Cloud. Now users can use this unique database for creating their applications.
  • Cloud Load Balancing: This is a cloud-based load balancing service from Google.
  • BigQuery: It is a data-warehouse solution from Google in Cloud to perform data analytics of large scale.
  • Cloud Machine Learning Platform: It is a powerful cloud based machine learning product from Google to perform machine learning with APIs like- Job Search, Text Analysis, Speech Recognition, Dynamic translation etc.
  • Cloud IAM: This is an Identity and Access management tool from Google to help administrators run the security and authorization/authentication policies of an organization.

What are the major offerings of Microsoft Azure Cloud?

Microsoft is a relatively new entrant to Cloud computing with Azure cloud offering. Some of the main products of Microsoft cloud are as follows:

  • Azure Container Service: This is a cloud computing service from Microsoft to run and manage Docker based containers.
  • StorSimple: It is a Storage solution from Microsoft for Azure cloud.
  • App Service: By using App Services, users can create Apps for mobile devices as well as websites.
  • SQL Database: It is a Cloud based SQL database from Microsoft.
  • DocumentDB: This is a NoSQL database in cloud by Microsoft.
  • Azure Bot Service: We can use Azure Bot Service to create serverless bots that can be scaled up on demand.
  • Azure IoT Hub: It is a solution for Internet of Things services in cloud by Microsoft.

What are the reasons of popularity of Cloud Computing architecture?

These days Cloud Computing is one of the most favorite architecture among organizations for their systems. Following are some of the reasons for popularity of Cloud Computing architecture:

  • IoT: With the Internet of Things, there are many types of machines joining the Internet and creating various types of interactions. In such a scenario, Cloud Computing serves well to provide scalable interfaces to communicate between the machines in IoT.
  • Big Data: Another major trend in today’s computing is Big Data. With Big Data there is very large amount of user / machine data that is generated. Using in-house solution to handle Big Data is very costly and capital intensive. In Cloud Computing we can handle Big Data very easily since we do not have to worry about capital costs.
  • Mobile Devices: A large number of users are going to Mobile computing. With a mobile device users can access a service from any location. To handle wide-variety of mobile devices, standard interfaces of Cloud Computing are very useful.
  • Viral Content: With growth of Social Media, content and media is getting viral i.e. It takes very short time to increase the traffic exponentially on a server. In such a scenario Auto-scaling of Cloud Computing architecture can handle such spikes very easily.

What are the Machine Learning options from Google Cloud?

Google provides a very rich library of Machine Learning options in Google Cloud. Some of these API are:

  • Google Cloud ML: This is a general purpose Machine Learning API in cloud. We can use pre-trained models or generate new models for machine learning with this option.
  • Google Cloud Jobs API: It is an API to link Job Seekers with Opportunities. It is mainly for job search based on skills, demand and location.
  • Google Natural Language API: This API can do text analysis of natural language content. We can use it for analyzing the content of blogs, websites, books etc.
  • Google Cloud Speech API: It is a Speech Recognition API from Google to handle spoken text. It can recognize more than 80 languages and their related variants. It can even transcribe the user speech into written text.
  • Google Cloud Translate API: This API can translate content from one language to another language in cloud.
  • Google Cloud Vision API: It is a powerful API for Image analysis. It can recognize faces and objects in an image. It can even categorize images in multiple relevant categories with a simple REST API call.

How will you optimize the Cloud Computing environment?

In a Cloud Computing environment we pay by usage. In such a scenario our usage costs are much higher. To optimize the Cloud Computing environment we have to keep a balance between our usage costs and usage.

If we are paying for computing instances we can choose options like Lambda in AWS, which is a much cheaper options for computing in cloud.

In case of Storage, if the data to be stored is not going to be accesses frequently we can go for Glacier option in AWS.

Similarly when we pay for bandwidth usage, it makes sense to implement a caching strategy so that we use less bandwidth for the content that is accessed very frequently.

It is a challenging task for an architect in cloud to match the options available in cloud with the budget that an organization has to run its applications.

Optimizations like server-less computing, load balancing, and storage selection can help in keeping the Cloud computing costs low with no degradation in User experience.

Do you think Regulations and Legal Compliance is an important aspect of Cloud Computing?

Yes, in Cloud Computing we are using resources that are owned by the Cloud provider. Due to this our data resides on the servers that can be shared by other users of Cloud.

There are regulations and laws for handling user data. We have to ensure that these regulations are met while selecting and implementing a Cloud computing strategy.

Similarly, if we are in a contract with a client to provide certain Service Level Agreement (SLA) performance, we have to implement the cloud solution in such a way that there is no breach of SLA agreement due to Cloud provider’s failures.

For security there are laws that have to be followed irrespective of Cloud or Co-located Data center. This is in the interest of our end-customer as well as for the benefit of business continuity.

With Cloud computing architecture we have to do due diligence in selecting Security and Encryption options in Cloud.

Why automation of deployment is very important in Cloud architecture?

One of the main reasons for selecting Cloud architecture is scalability of the system. In case of heavy load, we have to scale up the system so that there is no performance degradation.

While scaling up the system we have to start new instances. To provision new instances we have to deploy our application on them.

In such a scenario, if we want to save time, it makes sense to automate the deployment process. Another term for this is Auto-scaling.

With a fully automated deployment process we can start new instances based on automated triggers that are raised by load reaching a threshold.

What are the main components in Amazon Cloud?

Amazon provides a wide range of products in Amazon Web Services for implementing Cloud computing architecture. In AWS some of the main components are as follows:

  • Amazon EC2: This is used for creating instances and getting computing power to run applications in AWS.
  • Amazon S3: This is a Simple Storage Service from AWS to store files and media in cloud.
  • Amazon DynamoDB: It is the database solution by AWS in cloud. It can store very large-scale data to meet needs of even BigData computing.
  • Amazon Route53: This is a cloud based Domain Name System (DNS) service from AWS.
  • Amazon Elastic Load Balancing (ELB): This component can be used to load balance the various nodes in AWS cloud.
  • Amazon CodeDeploy: This service provides feature to automate the code deployment to any instance in AWS.

What is CaaS?

CaaS is also known as Communication as a Service. It is available in Telecom domain. One of the examples for CaaS is Voice Over IP (VoIP).

CaaS offers business features like desktop call control, unified messaging, and fax via desktop.

CaaS also provides services for Call Center automation like- IVR, ACD, call recording, multimedia routing and screen sharing.