Google Cloud SQL - Cloud SQL and Google Kubernetes Engine (GKE) MCQ

Google Cloud SQL – 32 – Cloud SQL and Google Kubernetes Engine (GKE) MCQ

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1. What is the primary advantage of using Google Cloud SQL with Google Kubernetes Engine (GKE)?

Manual infrastructure management

Scalability and containerization

Reduced security

Enhanced query performance

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2. Which Google Cloud service provides container orchestration capabilities for running containerized applications?

Google Kubernetes Engine (GKE)

Google Cloud Functions

Google Cloud Storage

Google Cloud SQL

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3. How does Google Cloud SQL simplify database administration when integrated with GKE?

It handles routine database maintenance tasks.

It requires manual scaling of databases.

It offers containerization of databases.

It increases operational overhead.

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4. What kind of databases can be managed using Google Cloud SQL?

MongoDB and Cassandra

MySQL, PostgreSQL, and SQL Server

MySQL and PostgreSQL only

SQL Server and Oracle

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5. What is the primary benefit of scaling horizontally in Google Kubernetes Engine (GKE)?

Improved database security

Reduced operational overhead

Efficient resource utilization

Simplified application code

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6. What is the significance of configuring authorized networks or SSL/TLS encryption for a Google Cloud SQL instance?

To optimize database queries

To reduce storage costs

To allow secure database connections

To simplify code development

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7. In the context of GKE, what is a Kubernetes Pod?

A containerized application component

A serverless function

A database management tool

A virtual machine

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8. Which Google Cloud service offers high availability configurations, including regional instances and failover replicas?

Google Cloud Pub/Sub

Google Cloud SQL

Google Cloud Storage

Google Cloud Functions

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9. What is the role of environment variables in Kubernetes Pods when integrating with Google Cloud SQL?

To manage IAM permissions

To optimize database indexing

To store database credentials securely

To configure networking settings

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10. How can database operations be performed in Google Kubernetes Engine (GKE) when using Google Cloud SQL?

By manually configuring the database schema

By setting up containerization for the database

By using appropriate database libraries and connection parameters

By directly accessing the physical database server

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11. What is the best practice for securing sensitive information like database credentials in Kubernetes Pods?

Using Kubernetes Secrets or a similar mechanism

Storing credentials in plaintext files

Hardcoding credentials in application code

Exposing credentials in environment variables

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12. What is the primary role of IAM roles and permissions when integrating Google Cloud SQL with Google Kubernetes Engine (GKE)?

To optimize query performance

To manage database schema changes

To restrict access based on least privilege

To establish database connections

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13. Which use case is NOT typically associated with integrating Google Cloud SQL with Google Kubernetes Engine (GKE)?

Real-time analytics

Batch processing

Microservices architecture

Manual infrastructure management

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14. What is the recommended approach for managing database connections efficiently in Kubernetes Pods?

Exporting logs to external destinations

Using connection pooling libraries or mechanisms

Implementing complex error handling

Disabling audit logging

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15. What is the primary goal of implementing proper error handling in Google Kubernetes Engine (GKE)?

To gracefully handle database errors and failures

To ensure data privacy

To reduce storage costs

To improve query performance

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16. Why is it important to store database connection credentials securely in Kubernetes Pods when integrating with Google Cloud SQL?

To reduce operational overhead

To improve query performance

To simplify code development

To ensure data privacy and security

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17. In a scenario where an e-commerce website records order details in a Google Cloud SQL database, what would trigger the Kubernetes Pods responsible for this task?

HTTP requests when orders are placed

Scheduled intervals

Manual invocation only

Infrastructure scaling

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18. What is the primary benefit of using an HTTP trigger for a Kubernetes Pod in the e-commerce order scenario?

Scalability and real-time response

Reduced cost

Simplified database schema

Improved query performance

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19. Which Google Cloud service can be used to securely store sensitive data like database credentials for Kubernetes Pods?

Google Cloud Pub/Sub

Google Cloud Storage

Google Cloud Bigtable

Google Cloud Secret Manager

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20. What is the primary role of log monitoring and alerts in the integration of Kubernetes Pods with Google Cloud SQL?

To track code execution performance

To track the function's performance and troubleshoot issues

To optimize database indexing

To secure the database connection

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21. What is a common use case for integrating Google Cloud SQL with Google Kubernetes Engine (GKE)?

Database schema changes

Manual infrastructure management

Real-time data validation

Background job execution

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22. What is the primary focus of integrating Google Cloud SQL with Google Kubernetes Engine (GKE) for serverless applications?

Manual infrastructure scaling

Serverless architecture and event-driven operations

Scalability and simplified code development

Complex infrastructure management

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23. What is the primary role of establishing a secure database connection in Kubernetes Pods when integrating with Google Cloud SQL?

To ensure data privacy and security

To reduce operational overhead

To optimize query performance

To simplify code development

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24. In Kubernetes Pods, what triggers the execution of a function?

Infrastructure scaling

Scheduled intervals

Manual invocation only

Events or triggers

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25. What is the primary advantage of using serverless services like Google Cloud SQL and Google Kubernetes Engine (GKE)?

Reduced cost

Manual scaling

Reduced operational overhead

Complex infrastructure management

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Google Cloud SQL – Cloud SQL and Google Kubernetes Engine (GKE) MCQ