Google Cloud (GCP) Interview Questions and Answers

Every software engineer’s ultimate dream is to work at Google. Rated as one of the best employers in the world, Google opens a host of opportunities, which allows you as a software engineer to push boundaries and work on some of the most cutting-edge applications. 

Out of the various divisions and roles at Google, working on the Google Cloud Team is a highly coveted role for every software developer. However, getting hired for the Google Cloud Platform (GCP) role is no cakewalk. You’ll need to crack the Google cloud interview questions to demonstrate your expertise and knowledge in the field of cloud computing.

1. What is Google Cloud Platform?

Google Cloud Platform (GCP) is a suite of cloud computing services provided by Google. It is a public cloud computing platform consisting of a variety of services like computing, storage, networking, application development, Big Data, and more, which run on the same cloud infrastructure that Google uses internally for its end-user products, such as Google Search, Photos, Gmail and YouTube, etc.

GCP services can be accessed by software developers, cloud administrators, and IT professionals over the Internet or through a dedicated network connection.

2. Why Google Cloud Platform?

Google Cloud Platform is known as one of the leading cloud providers in the field. The services and features can be easily accessed and used by software developers and users with little technical knowledge. Google has been on top amongst its competitors, offering the highly scalable and most reliable platform for building, testing, and deploying the applications in a real-time environment.

Apart from this, GCP was announced as the leading cloud platform in Gartner’s IaaS Magic Quadrant in 2018. Gartner is one of the leading research and advisory companies. Gartner organized a campaign where Google Cloud Platform was compared with other cloud providers, and GCP was selected as one of the top three providers in the market.

Most companies use data centers because of the availability of cost forecasting, hardware certainty, and advanced control. However, they lack the necessary features to run and maintain resources in the data center. GCP, on the other side, is a fully-featured cloud platform that includes:

• Capacity: Sufficient resources for easy scaling whenever required. Also, effective management of those resources for optimum performance.
• Security: Multi-level security options to protect resources, such as assets, networks, and OS -components.
• Network Infrastructure: Number of physical, logistical, and human-resource-related components, such as wiring, routers, switches, firewalls, load balancers, etc.
• Support: Skilled professionals for installation, maintenance, and support.
• Bandwidth: Suitable amount of bandwidth for peak load.
• Facilities: Other infrastructure components, including physical equipment and power resources.

Therefore, the Google Cloud Platform is a viable option for businesses, especially when the businesses require an extensive catalog of services with global recognition.

3. What are the Benefits of the Google Cloud Platform?

Some of the main benefits of the Google Cloud Platform are explained below:

• Best Pricing
• Work from Anywhere
• Private Network
• Scalable
• Security
• Redundant Backup

4. List some GCP Services?

There are some featured products of Google Cloud as below.

• BigQuery – Data warehouse for business insights.
• Cloud CDN – It’s a content delivery network for images, audio, video, etc.
• Cloud Functions – Server-less execution, just write your code, Google will handle the infrastructure to run that
• Cloud Run – A managed environment to run containerized applications.
• Cloud SDK – provides command-line tools and other libraries for Google cloud.
• Cloud SQL – provides Relational database services for PostgreSQL, SQL Server, and MySQL.
• Cloud Storage – Object storage in different formats that are secure and durable.
• Compute Engine – provide virtual machines that run on Google’s data centers.
• Data Flow – provide streaming analytics for batch processing and streams.
• Google Kubernetes Engine – It’s a managed environment for running containerized applications.
• Operations – Monitoring, logging, and other performance services.

 5. List some commonly used Google Cloud Services?

Below are the services of GCP which are commonly used.

• Computing and hosting
• Storage
• Databases
• Networking
• Big data
• Machine learning

6. What are the different computing and hosting services?

Google Cloud Platform provides much computing and hosting services as per your requirement.

• Serverless computing – Google cloud’s Cloud Functions provide a serverless execution environment known as FaaS (Function as a service). Just you need to write the code, Infrastructure will be handled by Google cloud. These functions are triggered by events.
• Application Platform –
• Containers
• Virtual Machines
• Combining computing and hosting options

7. What are the types of migrations in GCP?

There are 3 types of Migrations:

• Lift and shift
• Rip and replace
• Improve and move

8. What are the many levels of cloud architecture?

The following are the many layers of cloud architecture:

• Physical Layer: This layer contains the network, physical servers, and other components.
• Infrastructure layer: This layer includes virtualized storage levels, among other things.
• Platform layer: This layer consists of the applications, operating systems, and other components.
• Application layer: It is the layer with which the end-user interacts directly.

9. What exactly is Google Cloud SDK?

The Google Cloud SDK is a set of command-line utilities. It is utilized in the development of the Google cloud. We may use these tools to access large queries, cloud storage, computing Engine, and other resources directly from the command line. The Google Cloud SDK also includes client libraries and API libraries. These tools and frameworks let us interact with Virtual Machine instances, and manage computer engine networks, storage, and firewalls, among other things.

10. How would you define VPC?

VPC is an abbreviation for Virtual Private Cloud. It is a virtual network that connects to Google Kubernetes Engine clusters, computes Engine VM instances, and various other services. The VPC provides a great deal of control over how workloads connect globally or regionally. A single VPC can serve multiple regions without relying on the Internet.

11. What libraries and tools are available for GCP cloud storage?

JSON and XML APIs are fundamental to Google Cloud Platform cloud storage. In addition to this, Google provides the following tools for interfacing with cloud storage.

Google Cloud Platform Console- It’s a collection of cloud computing services that run on the same infrastructure as Google’s end-user products including Google Search, Gmail, Google Drive, and YouTube. GCP Console offers a myriad of modular cloud services, including computing, data storage, data analytics, and machine learning, in addition to a set of management tools. A credit card or bank account number is required to register for GCP Console.

Cloud Storage Client Libraries- Google Cloud Storage enables you to store data on Google’s infrastructure with high reliability, performance, and availability, and it may also be used to deliver huge data items to consumers via direct download.

Gustil Command-line Tool- It’s a Python program that enables you to use the command line to access Cloud Storage. gsutil can be used to do a variety of bucket and object management operations, such as creating and deleting buckets. Objects can be uploaded, downloaded, and deleted.

12. What is a Google Cloud API? How did we get our hands on it?

Google Cloud APIs are programmatic interfaces that allow users to add power to everything from storage access to machine-learning-based image analytics to Google Cloud-based applications.

Cloud APIs are simple to use with client libraries and server applications. The Google Cloud API is accessible via a number of programming languages. Firebase SDKs or third-party clients can be utilized to build mobile applications. Google SDK command-line tools or the Google Cloud Platform Console Web UI can be used to access Google Cloud APIs.

13. What exactly is a bucket in Google Cloud Storage?

Buckets are the main containers for storing data. We may arrange the data and provide access to the control by using buckets. The bucket has a globally unique name and a geographic location where the material is kept. A default storage class is offered, which is applied to items that are added to the bucket but do not have a specified storage class. There is no limit to the number of buckets that can be added or removed.

14. Define Object Versioning?

Object versioning is used to recover objects that have been overwritten or erased. Object versioning raises storage costs, but it assures that objects are secure when replaced or removed. When the GCP bucket’s object versioning is enabled, a non-common version of the object is created whenever the object is deleted or overwritten. The properties generation and meta generation are used to identify a version of an item. Meta generation acknowledges metadata generation, whereas generation recognizes content generation.

15. What is serverless computing?

Serverless computing refers to the practice of offering backend services on a per-user basis. Although servers are still utilized, a company that uses serverless backend services is charged based on consumption rather than a fixed amount of bandwidth or number of servers. The cloud service provider will have a server in the cloud that operates and handles resource allocation dynamically in Serverless computing. The supplier provides the infrastructure required for the user to function without worrying about the hardware. Users must pay for the resources that they utilize. It will streamline the code deployment process while removing all maintenance and scalability difficulties for users. It’s a subset of utility computing.

16. On-demand functionality is provided by cloud computing in what way?

Cloud computing as technology was designed to give functionality to all on-demand users at any time and from any location. It has achieved this goal with subsequent advancements and simplicity of application availability, such as Google Cloud. A Google Cloud user will be able to access their files in the cloud at any time, on any device, from any location as long as they are connected to the Internet.

17. What is the connection between Google Compute Engine and Google App Engine?

Google App Engine and Google Compute Engine complement one another. Google Application Engine is a Platform-as-a-service (PaaS), whereas GCE is an Infrastructure-as-a-service (IaaS). GAE is commonly used to power mobile backends, web-based apps, and line-of-business applications. If we require additional control over the underlying infrastructure, Google Compute Engine is an excellent choice. GCE, for example, can be utilized to create bespoke business logic or to run our own storage solution.

18. What do you know about Google Compute Engine?

• Google Compute Engine is an IaaS product that offers self-managed and flexible virtual machines that are hosted on the infrastructure of Google. It includes Windows and Linux-based virtual machines that may run on local, KVM, and durable storage options.
• It also includes REST-based API for control and configuration purposes. Google Compute Engine integrates with GCP technologies such as Google App Engine, Google Cloud Storage, and Google BigQuery in order to extend its computational ability and thus create more sophisticated and complex applications.

19. How are the Google Compute Engine and Google App Engine related?

• Google Compute Engine and Google App Engine are complementary to each other. Google Compute Engine is the IaaS product whereas Google App Engine is a PaaS product of Google.
• Google App Engine is generally used to run web-based applications, mobile backends, and lines of business. If you want to keep the underlying infrastructure in more of your control, then Compute Engine is a perfect choice. For instance, you can use Compute Engine for the implementation of customized business logic or in case, you need to run your own storage system.

20. How does the pricing model work in the GCP cloud?

• While working on the Google Cloud Platform, the user is charged on the basis of compute instance, network use, and storage by Google Compute Engine. Google Cloud charges virtual machines on the basis of per second with a limit of a minimum of 1 minute. Then, the cost of storage is charged on the basis of the amount of data that you store.
• The cost of the network is calculated as per the amount of data that has been transferred between the virtual machine instances communicating with each other over the network.

21. What are the service accounts? How will you create one?

• The service accounts are used for the authorization of Google Compute Engine so that it could perform on behalf of the user and thus could access non-sensitive data and information.
• These accounts generally simplify the authentication process from Google Cloud Engine to the other services by handling the process of authorization for the user. It is required to mention that service accounts are not used in order to access the information of the user.

There are various types of service accounts offered by Google but mainly, users prefer to use two types of service accounts, are

• Google Cloud Platform Console service accounts
• Google Compute Engine service accounts

The user doesn’t need to create a service account manually. It is automatically created by the Compute Engine whenever a new instance is created. Google Compute Engine also specifies the scope of the service account for that particular instance when it is created.

22. What do you know about Projects?

The projects are the containers for the resources of Google Compute Engine. The main points about the projects are

• The projects comprise the world of compartments
• The projects are not meant for resource sharing
• The projects may have different users and owners
• The billing for all the projects is done separately
• The projects are no more accessible to each other

23. How will you create a Project?

One needs to follow the below-mentioned steps for creating a Project –

• Go to the Google Cloud Platform Console
• Once prompted, create a new project or select an existing project
• In order to set up billing, follow the prompts.

24. How will you differentiate a Project Id and Project Number?

• There are two parameters to identify a project, one is the project id and another one is the project number. The two can be differentiated as follows –
• Whenever a new project is created, the project number for that is created automatically whereas the project number is created by the user himself. The project number is compulsory and mandatory while the project id can be optional for many services (but it is a must for the Google Compute Engine).

25. How will you request more quota for your project?

• Some default quotas are provided to all the Google Compute Engine projects for various types of resources. The quotas can also be increased on the basis of per project. One can check the quota limits for the project on the quota page on the Google Cloud Platform Console.
• In case, you find that you have reached the quota limit for your resources, and you want to increase the quota, then you can make a request to get more quotas for some specific resources using the IAM quotas page. You can request more quotas directly through the Edit Quotas button on the top of the page.

26. Suppose you have deleted your instance by mistake. Will you be able to retrieve it back? If yes, how?

No, it is not possible to retrieve the instances that have been deleted once. If it has been stopped, it can be retrieved back by simply starting it again.

27. What is Google BigQuery? What are the benefits of BigQuery for data warehouse practitioners?

Google BigQuery is a replacement for the hardware setup for the traditional data warehouse. It is used as a data warehouse and thus, acts as a collective store for all the analytical data in an organization. Also, BigQuery organizes the data table into the units that are known as datasets.

Using BigQuery proves very useful for the data warehouse practitioners, here are some of them –

• BigQuery allocated query resources and storage resources dynamically on the basis of requirement and usage. Thus, it doesn’t require the provisioning of resources before usage.
• BigQuery stores data in different formats such as proprietary format, proprietary columnar format, query access pattern, Google’s distributed file system, and others for efficient storage management.
• BigQuery is fully maintained and managed. BigQuery engineers manage the updates and maintenance of the service fully without any downtime or hindrance to the performance.
• BigQuery provides backup recovery and disaster recovery at a broader level. The users can easily undo the changes and revert to the previous state without making any request for the backup recovery.