GCP Interview Questions and Answers

Top Google Cloud Platform (GCP) Interview Questions and Answers


Google Cloud Platform (GCP) is a leading cloud provider that offers a range of services for infrastructure, data analytics, machine learning, and more. If you're preparing for a GCP-related role, such as cloud engineer, architect, or data engineer, you need to be ready to answer a mix of theoretical and practical questions.

Here’s a curated list of common GCP interview questions and answers to help you prepare confidently.

General GCP Questions



  1. What is Google Cloud Platform (GCP)?
    Answer:
    GCP is a suite of cloud computing services provided by Google. It offers infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) solutions for building, deploying, and managing applications. Key features include scalability, reliability, and integration with Google’s AI and machine learning tools.


  2. What are the key components of GCP?
    Answer:



    • Compute: Compute Engine, App Engine, Kubernetes Engine.

    • Storage: Cloud Storage, Persistent Disk, Filestore.

    • Big Data: BigQuery, Dataflow, Dataproc.

    • Machine Learning: AI Platform, BigQuery ML, AutoML.

    • Networking: VPC, Cloud CDN, Cloud Load Balancing.



  3. What differentiates GCP from AWS and Azure?
    Answer:



    • Strong focus on data analytics and machine learning with tools like BigQuery and AI Platform.

    • Advanced networking infrastructure leveraging Google’s global network.

    • Cost-effectiveness with sustained use discounts and custom VM configurations.




Compute Questions



  1. What is Compute Engine, and how is it used?
    Answer:
    Compute Engine is GCP’s IaaS offering that provides virtual machines (VMs). It is used for running scalable applications, hosting websites, or deploying custom solutions.


  2. What is the difference between App Engine and Compute Engine?
    Answer:



    • App Engine: A PaaS for deploying and managing applications without managing the underlying infrastructure.

    • Compute Engine: An IaaS for running virtual machines with full control over the OS and environment.



  3. How do you optimize the cost of VMs in Compute Engine?
    Answer:



    • Use preemptible VMs for non-critical workloads.

    • Take advantage of sustained use discounts.

    • Right-size VMs based on actual usage.

    • Use custom machine types to tailor resources.




Storage and Database Questions



  1. What are the storage options available in GCP?
    Answer:



    • Cloud Storage: Object storage for unstructured data.

    • Persistent Disk: Block storage for VMs.

    • Filestore: Managed file storage for applications requiring shared file systems.

    • BigQuery: Serverless data warehouse for analytics.

    • Cloud SQL/Cloud Spanner: Managed relational databases.



  2. What is the difference between Cloud SQL and BigQuery?
    Answer:



    • Cloud SQL: A fully managed relational database for OLTP use cases.

    • BigQuery: A serverless data warehouse designed for OLAP use cases and large-scale analytics.



  3. How do you ensure data security in Cloud Storage?
    Answer:



    • Use IAM roles to control access.

    • Enable bucket-level and object-level permissions.

    • Encrypt data at rest and in transit.

    • Use VPC Service Controls for restricting access.




Networking Questions



  1. What is a Virtual Private Cloud (VPC) in GCP?
    Answer:
    A VPC is a logically isolated network within GCP. It allows you to define IP ranges, subnets, and firewall rules to securely connect resources.


  2. What is the difference between a static and an ephemeral external IP in GCP?
    Answer:




  • Static IP: Permanently reserved IP that doesn't change across reboots.

  • Ephemeral IP: Temporary IP assigned to a resource that changes if the resource is stopped or restarted.



  1. How do you configure load balancing in GCP?
    Answer:
    Use Cloud Load Balancing, which supports HTTP(S), TCP/UDP, and SSL proxy load balancing. Configure it through the GCP Console or CLI by specifying backend services and health checks.


Data Analytics and Machine Learning Questions



  1. What is BigQuery, and what are its key features?
    Answer:
    BigQuery is GCP’s serverless data warehouse for large-scale analytics. Key features include:



  • SQL-based querying.

  • Integration with Google Sheets and BI tools.

  • Support for partitioned and clustered tables.

  • Machine learning capabilities through BigQuery ML.



  1. What is the role of Pub/Sub in data pipelines?
    Answer:
    Pub/Sub is a messaging service that enables asynchronous communication between services. It is commonly used for event-driven architectures and streaming data pipelines.


  2. How do you use BigQuery ML?
    Answer:
    Use SQL queries to build, train, and deploy machine learning models directly within BigQuery without exporting data to external tools.



IAM and Security Questions



  1. What is IAM in GCP?
    Answer:
    Identity and Access Management (IAM) is a system for managing permissions. It enables fine-grained control over who can access specific GCP resources and what actions they can perform.


  2. What are service accounts in GCP?
    Answer:
    Service accounts are special accounts used by applications or services to authenticate and access GCP resources securely.


  3. How do you secure a GCP environment?
    Answer:




  • Use IAM roles and policies.

  • Enable VPC Service Controls.

  • Use encryption (default in GCP).

  • Enable Cloud Armor for protection against DDoS attacks.


Scenario-Based Questions



  1. How would you design a data pipeline on GCP?
    Answer:



  • Use Pub/Sub for real-time data ingestion.

  • Process the data using Dataflow.

  • Store the data in BigQuery for analytics.

  • Visualize results using Data Studio.



  1. How would you migrate an on-premises application to GCP?
    Answer:



  • Assess the application’s architecture and dependencies.

  • Select appropriate GCP services (e.g., Compute Engine, Kubernetes Engine).

  • Use tools like Migrate for Compute Engine for seamless migration.

  • Test the application and optimize for cloud performance.


Final Tips for GCP Interviews



  1. Understand GCP’s Core Services: Be familiar with key services and their use cases.

  2. Practice Hands-On: Use tools like Qwiklabs to gain real-world experience.

  3. Be Ready for Scenario Questions: Employers often assess your problem-solving skills with real-world challenges.

  4. Stay Updated: GCP evolves rapidly, so know the latest features and updates.


With this preparation, you’ll be ready to tackle GCP interviews with confidence.

 

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