Scenario: A company wants to reduce latency and improve the delivery speed of its web application globally. Which Google Cloud service should they implement?
- Cloud CDN
- Cloud Storage
- Cloud SQL
- Compute Engine
Cloud CDN is specifically designed to improve the performance of web applications by caching content closer to users, thus reducing latency and enhancing delivery speeds globally. It is the ideal solution for this scenario.
Scenario: A company wants to perform complex analytics on its massive datasets stored in Google Cloud. Which service should they choose for efficient and cost-effective analysis?
- BigQuery
- Cloud Dataflow
- Dataproc
- Cloud Pub/Sub
BigQuery is the recommended choice for performing complex analytics on massive datasets stored in Google Cloud due to its scalability, performance, and cost-effectiveness. Understanding the capabilities and use cases of different Google Cloud services is crucial for making informed decisions in data analytics projects.
Which Google Cloud service is commonly used for deploying and managing TensorFlow models?
- AI Platform
- Compute Engine
- Cloud Storage
- BigQuery
Knowing which Google Cloud service is commonly used for deploying and managing TensorFlow models helps beginners understand the practical steps involved in implementing machine learning solutions on GCP.
What are the key features of Stackdriver Monitoring that differentiate it from other monitoring tools?
- Automatic Ingestion
- Multi-Cloud Support
- AI-Driven Insights
- Cost Allocation
Stackdriver Monitoring's advanced features, such as automatic ingestion, AI-driven insights, and multi-cloud support, set it apart from other monitoring tools, empowering users with comprehensive visibility and actionable intelligence.
Scenario: A company wants to grant read-only access to a developer for a specific Google Cloud Storage bucket. Which IAM feature should they leverage to accomplish this?
- IAM Custom Roles
- IAM Conditions
- IAM Service Accounts
- IAM Roles
Understanding the appropriate IAM feature for granting read-only access to specific resources is crucial for maintaining security and compliance in cloud environments. By leveraging IAM roles, organizations can control access to resources based on the principle of least privilege.
Scenario: A company wants to track and analyze logs from its Kubernetes clusters running on Google Kubernetes Engine. Which Google Cloud service should they use for this purpose?
- Stackdriver Logging
- Cloud Monitoring
- Cloud Logging
- Cloud Logging with a third-party log analysis tool
Stackdriver Logging offers robust logging and monitoring capabilities tailored for Kubernetes clusters on GKE, making it the ideal choice for the company's requirements.
What is the primary purpose of Cloud Identity in a GCP environment?
- Managing user identities and controlling access to GCP resources
- Hosting websites and web applications
- Analyzing large datasets
- Automating infrastructure deployment
Understanding the primary purpose of Cloud Identity is crucial for effectively managing user access and ensuring security within a GCP environment.
What type of data redundancy does Persistent Disk offer to ensure data reliability?
- Replication
- Erasure Coding
- RAID (Redundant Array of Independent Disks)
- Backup
Understanding the data redundancy mechanisms employed by storage services like Persistent Disk is crucial for ensuring data availability and durability in cloud environments. Knowing how data is protected against failures helps in designing resilient architectures.
What are the benefits of using templates in Cloud Deployment Manager?
- Reusability
- Scalability
- Cost Optimization
- Security Enhancement
Using templates in Cloud Deployment Manager offers several benefits, including reusability, scalability, and cost optimization, which contribute to efficient and reliable infrastructure management.
TensorFlow _______ allows users to monitor, manage, and scale TensorFlow workloads efficiently on GCP.
- Cloud Monitoring
- Cloud Deployment Manager
- Cloud Composer
- Cloud AI Platform
TensorFlow AI Platform (formerly known as Cloud AI Platform) offers capabilities for deploying and managing TensorFlow models but does not specifically focus on monitoring, managing, and scaling TensorFlow workloads efficiently. Understanding the tools dedicated to these tasks is essential for expert-level proficiency in TensorFlow workload management on GCP.