What is the difference between Cloud Storage Nearline and Coldline storage classes?
- Access Frequency and Cost
- Storage Capacity and Redundancy
- Performance and Latency
- Geographic Location and Data Center Placement
Understanding the differences between Google Cloud Storage classes like Nearline and Coldline is essential for optimizing storage costs and performance based on data access patterns and requirements.
What is Stackdriver Monitoring used for in Google Cloud Platform?
- Monitoring and observability
- Data Analytics
- Virtual Machine Management
- Payment Processing
Stackdriver Monitoring is primarily used for monitoring and observability, providing insights into the health and performance of applications and infrastructure in Google Cloud Platform.
How does Google Cloud ensure reliable performance with Network Service Tiers?
- By offering multiple tiers of network services optimized for different use cases and performance requirements.
- By providing dedicated hardware resources for each customer's network traffic.
- By guaranteeing a minimum bandwidth for all network traffic.
- By using machine learning algorithms to dynamically adjust network routing based on real-time traffic patterns.
Understanding how Google Cloud's Network Service Tiers operate is crucial for expert-level understanding of network optimization and performance management in the cloud. Organizations can leverage these tiers to fine-tune their network infrastructure based on their specific requirements and budget constraints.
_______ is a key metric for evaluating the performance of Cloud CDN.
- Latency
- Bandwidth
- Uptime
- Packet Loss
Latency is a critical metric for evaluating the performance of a CDN like Google Cloud CDN. It directly impacts user experience by measuring the delay before a transfer of data begins following an instruction for its transfer.
AI Platform provides _______ infrastructure for training and serving machine learning models.
- Scalable
- Static
- Heterogeneous
- Networked
Scalable infrastructure is a key feature of AI Platform, allowing users to train and deploy machine learning models efficiently at scale. Understanding this aspect helps users leverage AI Platform effectively for their ML workflows, ensuring optimal performance and resource utilization.
Scenario: A startup wants to deploy a web application without worrying about infrastructure management. Which service of Google Cloud would be the most suitable option for them?
- Google App Engine
- Google Compute Engine
- Google Kubernetes Engine
- Google Cloud Functions
Google App Engine is the most suitable option for startups seeking to deploy web applications without the burden of managing infrastructure. Its fully managed platform enables developers to focus on application development and innovation without worrying about server provisioning, scaling, or maintenance.
What is the primary purpose of Google Cloud Pub/Sub?
- Real-time messaging
- Database Management
- Event-driven architecture
- Video Streaming
Understanding the primary purpose of Google Cloud Pub/Sub is crucial for beginners to grasp its role in designing and implementing scalable and resilient distributed systems.
IAM enables _______ based access to Google Cloud resources.
- Role
- User
- Resource
- Service
Understanding role-based access control (RBAC) and its implementation in IAM is crucial for organizations to effectively manage access to Google Cloud resources, reduce complexity, and enforce security best practices.
What role does a cache key play in Cloud CDN?
- Identifying unique content to be cached
- Encrypting cached data for security
- Monitoring cache hit ratios
- Scheduling cache updates
The cache key is crucial for uniquely identifying pieces of content in the cache. This ensures accurate storage and retrieval, which is essential for the efficient operation of a CDN.
_______ allows users to configure virtual machine instances with predefined or custom machine types.
- Google Compute Engine
- Google Kubernetes Engine
- Google Cloud Functions
- Google Cloud Storage
Understanding how to configure virtual machine instances with predefined or custom machine types on Google Compute Engine is essential for optimizing performance, cost, and resource utilization in cloud deployments.
Which Google Cloud service integrates seamlessly with Google Dataflow for data processing?
- BigQuery
- Cloud Storage
- Compute Engine
- Cloud Pub/Sub
Understanding the integration between Google Dataflow and other Google Cloud services is essential for designing and implementing scalable and efficient data processing pipelines. BigQuery's seamless integration with Dataflow enables organizations to perform real-time or batch data processing and analysis with ease.
_______ is a feature of Google Cloud Dataproc that automatically adjusts cluster size based on workload requirements.
- Autoscaling
- Load Balancing
- Predictive Scaling
- Elastic Scaling
Understanding autoscaling in Google Cloud Dataproc is crucial for users seeking to optimize resource usage and manage costs effectively by automatically adjusting cluster sizes based on workload demands.