20 GCP Interview Questions and Answers

Abhishek Pratap Singh 24 Jan, 2024 • 9 min read

Suppose you’re preparing for a managerial or senior role interview in a Google Cloud Platform (GCP) context. In that case, it’s crucial to comprehensively understand GCP and demonstrate leadership abilities in deployment, cost optimization, and security. Effective communication skills are also essential, both with technical and non-technical individuals. This article will cover a range of GCP interview questions, providing valuable insights to enhance your preparation for such roles.

GCP is a cloud service provided by Google, enabling businesses to store and process data and applications in the cloud rather than on physical servers. With its various services and tools, Google Cloud Platform offers a robust and flexible cloud computing environment for organizations seeking to migrate their workloads to the cloud. While answering GCP interview questions, you might have to share examples of specific business problems you have solved using GCP and discuss your recent projects and experiences. It’s important to note that these questions serve as examples, and answers may vary based on individual expertise and experience.

This article was published as a part of the Data Science Blogathon.

Table of contents

Let’s look at the most advanced GCP interview questions out there:

Q1. How would you migrate a company’s on-premises Infrastructure?

Migrating a company’s on-premises infrastructure to GCP can be a complex and multi-faceted project. You can give a high-level approach by explaining the following point as per your experience to how you could approach such a migration:

  • Assess the current infrastructure
  • Set up the environment
  • Migrate the data
  • Migrate the applications
  • Test and validate
  • Optimize the environment

Q2. What are some best Practices for Securing Data?

Securing data is a critical aspect of cloud infrastructure management. You can give a high-level approach by explaining the following point as per your experience to help ensure that data is protected in GCP:

  • Implement access controls(IAM)
  • Use encryption
  • Implement network security
  • Enable logging and monitoring
  • Use multi-factor authentication (MFA)
  • Follow security best practices

Q3. How do you ensure Cost Optimization?

Cost optimization is an important aspect of managing services. You can explain the following topics,

  • Use resource labels
  • Use resource sizing
  • Use managed services
  • Use serverless computing
  • Use committed use discounts
  • Use auto-scaling
  • Use Cloud Billing reports

Q4. How would you manage a team of Engineers responsible for Deploying and Managing?

Managing a team of engineers responsible for deploying and managing GCP resources requires strong leadership and technical skills. Here are some general steps to manage a team of engineers:

  • Set clear expectations with the team
  • Provide technical guidance and support to your team
  • Develop processes and best practices
  • Regularly Monitor and measure performance
  • Encourage team members to develop their technical skills and knowledge.
  • Communicate effectively, and keep everyone informed of project status, timelines, and any issues or risks.

Q5. How do you Monitor and Troubleshoot Issues?

To monitor and troubleshoot issues in GCP, we can enable Cloud Monitoring, set up alerts, and use Stackdriver LoggingTrace and Debugger, and Cloud Diagnostics. Cloud Monitoring provides metrics and logs for resources, and alerts can be set up based on specific metrics. Stackdriver Logging offers real-time log analysis, while Trace helps identify performance issues. Debugger helps diagnose and fix issues in code, and Cloud Diagnostics provides a suite of tools for troubleshooting applications. Also, add your expertise.

Monitor and Troubleshoot Issues in GCP | GCP Interview Questions

Q6. What is your experience with managing GCP resources using Automation Tools such as Terraform or Ansible?’

Managing GCP resources with automation tools such as Terraform or Ansible involves using code to define and provision infrastructure consistently and repeatedly. This enables us to automate the deployment and management of resources, reducing manual, error-prone tasks and increasing efficiency. Terraform allows us to define infrastructure as code and create a plan for deployment, while Ansible provides a way to automate the configuration and management of resources. Both tools enable us to manage resources at scale and ensure that they are provisioned and configured consistently. By using automation tools, we can reduce the time and effort required to manage GCP resources, streamline our workflows, and achieve greater control and visibility over our infrastructure. Also, add your expertise.

Q7. How do you ensure High Availability and Disaster Recovery?

To ensure high availability and disaster recovery in GCP, configure resources across multiple zones or regions, use load balancing, implement backup and recovery processes, and test disaster recovery plans. This can ensure that applications and services remain available and can recover from any disaster that may occur, minimizing downtime and ensuring business continuity. Also, add your expertise.

Q8. What are your experience with Compliance and Regulatory requirements?

Compliance and regulatory requirements related to GCP involve meeting specific rules and guidelines for handling data and protecting privacy. Examples of these requirements include SOC 2, HIPAA, and GDPR. Organizations must establish policies and procedures, such as access controls and audit logging, to comply with these regulations to protect data. Compliance may require regular audits and assessments to verify that controls are effective and in place. It is essential to meet these requirements to maintain customer trust and ensure data security.  Also, add your expertise.

Q9. How do you keep up-to-date with the Latest Technologies and Updates?

Several resources are available to keep up-to-date with the latest GCP technologies and updates. GCP documentation and blogs provide detailed information on new releases, features, and best practices. GCP also offers various training and certification programs, which can help deepen understanding of the platform and its capabilities. Attending GCP conferences and events can provide opportunities to network with other professionals and hear from experts on emerging trends and best practices. Also, add your expertise.

Updates about GCP, GCP interview questions

Q10. Can you describe a complex project you have managed and the Challenges you faced and Overcame during the Project?

A complex GCP project could involve designing and deploying a large-scale, multi-tiered application or migrating an existing application to GCP. Challenges might include designing a highly available and scalable architecture, optimizing cost and performance, ensuring security and compliance, and managing and automating infrastructure. Ensuring the project is completed within budget and on time while meeting the client’s requirements can also be challenging. To overcome these challenges, one might leverage best practices, such as building infrastructure as code, automating testing and deployment, and using monitoring and analytics tools to optimize performance and detect issues. Also, add your expertise.

Now that you have explored the advanced GCP interview questions, here are some basic or entry level GCP interview questions for you to follow!

Q11. What is Google Cloud Platform (GCP), and what are its key components?

Google Cloud Platform (GCP) is a cloud computing service provided by Google. It offers a suite of cloud-based services and tools to help organizations build, deploy, and manage various applications and services in a scalable and flexible manner. Key components of GCP include computing resources (Google Compute Engine and Google Kubernetes Engine), storage services (Cloud Storage, Cloud SQL), data analytics (BigQuery), messaging and event-driven architectures (Pub/Sub), networking (Virtual Private Cloud), security features, application deployment (Google App Engine), serverless computing (Cloud Functions), and machine learning and AI tools.

Q12. Explain the differences between Google Compute Engine and Google Kubernetes Engine.

Google Compute Engine (GCE) is an Infrastructure-as-a-Service (IaaS) offering from GCP that provides virtual machine instances for running workloads. It allows users to create and manage virtual machines in the cloud, providing full control over the computing environment. On the other hand, Google Kubernetes Engine (GKE) is a managed container orchestration platform that automates the deployment, scaling, and management of containerized applications using Kubernetes. GKE abstracts away the underlying infrastructure and simplifies the management of containerized workloads.

Q13. What is Cloud Storage in GCP, and how is it different from Cloud SQL?

Cloud Storage in GCP is a highly scalable and durable object storage service that allows users to store and retrieve data. It is designed for storing unstructured data and provides high availability and data redundancy. Cloud SQL, on the other hand, is a fully managed relational database service in GCP that supports MySQL and PostgreSQL databases. While Cloud Storage is ideal for storing files and objects, Cloud SQL provides a managed relational database solution with features like automatic backups, replication, and scalability.

Q14. How does BigQuery work, and what are its key features?

BigQuery is a serverless, highly scalable, and fully managed data warehouse and analytics platform in GCP. It allows users to analyze massive datasets using SQL-like queries in a fast and efficient manner. BigQuery uses a distributed architecture to process queries in parallel and can handle petabytes of data. Key features of BigQuery include its speed and scalability, easy integration with other GCP services, support for real-time data streaming, and built-in machine learning capabilities for advanced analytics.

Q15. What is Pub/Sub in GCP, and how can it be used for messaging and event-driven architectures?

Pub/Sub is a messaging and event-driven architecture service in GCP. It provides reliable, real-time messaging between independent applications. Pub/Sub allows decoupling of components in distributed systems and enables asynchronous communication. It can be used to build scalable, event-driven architectures and supports the exchange of messages between various applications and services within GCP or external systems.

Q16. Explain the concept of Virtual Private Cloud (VPC) and its importance in GCP.

Virtual Private Cloud (VPC) in GCP is a networking feature that provides a logically isolated virtual network environment for resources deployed in GCP. It allows users to define and control IP ranges, subnets, firewall rules, and network gateways. VPC enables secure and private communication between resources within the same VPC and allows users to connect their VPCs securely to on-premises networks or other cloud providers. VPC provides network-level isolation, security controls, and segmentation for better network management and security.

Q17. How does GCP ensure the security and privacy of data stored on its platform?

GCP ensures the security and privacy of data stored on its platform through various measures. It offers a robust set of security features, including identity and access management, encryption at rest and in transit, network security controls, data loss prevention, and security logging and monitoring. GCP also adheres to various security certifications and compliance standards, such as ISO 27001, SOC 2, and HIPAA, providing assurance to customers about the security and privacy of their data.

Q18. Describe the process of deploying and managing applications on Google App Engine.

The process of deploying and managing applications on Google App Engine involves the following steps:

  • Develop and package your application code using the supported programming languages and frameworks.
  • Create an App Engine project and configure your application settings, such as specifying the runtime environment and resource allocation.
  • Use the deployment command or the web interface to upload your application code to the App Engine platform.
  • Google App Engine automatically handles the deployment process, including scaling, load balancing, and managing infrastructure.
  • Once deployed, you can monitor and manage your application through the App Engine dashboard, which provides insights into usage, performance, and logs. You can also update or roll back your application code as needed.

Q19. What is the purpose of Cloud Functions in GCP, and when would you use them?

Cloud Functions in GCP are serverless compute resources that allow you to run individual functions in response to events. The purpose of Cloud Functions is to execute small, focused units of code in a scalable and event-driven manner. You would use Cloud Functions when you need to perform specific tasks or execute logic in response to events like file uploads, database changes, HTTP requests, or message queue triggers. Cloud Functions eliminate the need to manage infrastructure, as they automatically scale based on event demand. They are well-suited for building event-driven architectures, implementing microservices, and enabling serverless computing workflows.

Q20. How does GCP support machine learning and artificial intelligence applications?

GCP provides a comprehensive set of services and tools to support machine learning (ML) and artificial intelligence (AI) applications. Some key components include:

  • Google Cloud AI Platform: A suite of services and tools for building, training, and deploying ML models at scale. It offers AutoML, which enables the development of custom ML models without extensive coding expertise.
  • TensorFlow on GCP: GCP provides support for TensorFlow, a popular open-source ML framework, with dedicated resources like TensorFlow Extended (TFX) and TensorFlow Enterprise.
  • AI Infrastructure: GCP offers specialized hardware accelerators, such as Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs), to optimize the performance of ML workloads.
  • BigQuery ML: It allows you to build and execute ML models directly in BigQuery, Google’s fully-managed data warehouse.
  • Cloud Machine Learning Engine: A managed service for training and deploying ML models using popular frameworks like TensorFlow, scikit-learn, and XGBoost.
  • Dialogflow: A conversational AI platform that enables the development of chatbots and virtual assistants.

Start Your Prep with GCP Interview Questions

We have covered a wide range of GCP interview questions. The answers provided demonstrated a strong understanding of GCP concepts and the best practices for managing GCP resources. We discussed the process of migrating on-premises infrastructure to GCP, which involves careful planning, assessment, and migration and may be automated using tools like Velostrata and Migrate for Compute Engine.

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