Google Cloud's AI Platform provides _______ for building and deploying machine learning models.
- Infrastructure
- APIs
- Datasets
- Frameworks
Recognizing the role of AI Platform as a comprehensive platform for machine learning development and deployment helps users leverage its integrated tools and services effectively.
What are the considerations for setting up custom autoscaling policies in Google Compute Engine?
- Considerations for setting up custom autoscaling policies in Google Compute Engine include defining appropriate scaling triggers based on metrics such as CPU utilization, request latency, or custom application-specific metrics. Additionally, it's essential to set meaningful thresholds and scale-in and scale-out policies to ensure efficient resource allocation and cost optimization.
- Custom autoscaling policies in Google Compute Engine should prioritize simplicity and minimize the number of scaling triggers and policies to reduce complexity and improve manageability.
- Custom autoscaling policies in Google Compute Engine should rely solely on manual intervention, allowing administrators to make scaling decisions based on real-time observations and insights.
- Custom autoscaling policies in Google Compute Engine should be based solely on historical usage patterns, ignoring real-time metrics and workload characteristics to simplify configuration and management.
Setting up custom autoscaling policies in Google Compute Engine requires careful planning and consideration of various factors to ensure they align with business requirements and effectively manage resource utilization while maintaining application performance and availability.
How does Google Cloud IAM handle inheritance of permissions?
- Permissions are inherited from parent resources to child resources by default, but they can be overridden or restricted at any level in the resource hierarchy.
- Permissions are only inherited from parent resources to child resources if explicitly configured, otherwise, each resource has its own independent set of permissions.
- Permissions are inherited from child resources to parent resources, allowing more granular control over access rights at higher levels in the resource hierarchy.
- Google Cloud IAM does not support inheritance of permissions between resources.
Understanding how Google Cloud IAM handles inheritance of permissions is crucial for designing effective access control strategies and ensuring security in Google Cloud environments.
How does Stackdriver Trace provide insights into application dependencies and performance bottlenecks?
- Analyzes trace spans and dependencies
- Scans for security vulnerabilities
- Generates code coverage reports
- Monitors server uptime
By analyzing trace spans and dependencies, Stackdriver Trace provides developers with insights into the flow of requests through the application, highlighting areas of inefficiency and potential performance bottlenecks, facilitating optimization efforts.
In BigQuery, what is the purpose of a dataset?
- Organizing Related Tables
- Running Queries
- Storing Virtual Machines
- Managing Networking Infrastructure
Understanding the purpose of datasets in BigQuery is essential for organizing and managing data effectively within the platform. Datasets provide a hierarchical structure for organizing tables and controlling access permissions, enhancing data governance and security.
Which Google Cloud service allows users to deploy and manage virtual machines?
- Google Compute Engine
- Google Kubernetes Engine
- Google App Engine
- Google Cloud Functions
Google Compute Engine is the primary service in Google Cloud for deploying and managing virtual machines, providing flexibility, scalability, and integration with other Google Cloud services.
How does Google Cloud Pub/Sub ensure message delivery reliability?
- At-least-once Delivery
- Exactly-once Delivery
- Best-effort Delivery
- No Delivery Guarantees
Understanding how Pub/Sub ensures message delivery reliability is crucial for designing resilient and fault-tolerant systems that rely on real-time messaging. Knowing the different delivery modes helps architects choose the appropriate level of reliability for their use cases.
Scenario: A DevOps team wants to set up custom monitoring metrics and alerts for their microservices architecture in Google Cloud. Which feature of Stackdriver Monitoring should they leverage?
- Custom Metrics
- Service Monitoring
- Uptime Checks
- Error Reporting
Leveraging custom metrics in Stackdriver Monitoring enables the DevOps team to define and monitor metrics specific to their microservices architecture, facilitating proactive monitoring and alerting.
Scenario: An organization wants to migrate its existing applications to the cloud while minimizing code changes. Which Google Cloud service should they consider, and how does it support application migration?
- Google Anthos
- Google Cloud Run
- Google Cloud VMware Engine
- Google Migrate for Anthos
Google Anthos is the recommended Google Cloud service for organizations seeking to migrate existing applications to the cloud while minimizing code changes. It provides a consistent platform across on-premises and cloud environments, enabling seamless application modernization, migration, and management with minimal disruption to existing workflows and toolsets.
What features of Google Cloud Load Balancing contribute to its ability to handle sudden spikes in traffic effectively?
- Global Scalability
- Session Affinity
- SSL Termination
- HTTP(S) Load Balancing
Understanding the features of Google Cloud Load Balancing that contribute to its ability to handle sudden spikes in traffic is crucial for designing resilient and scalable architectures in the cloud. HTTP(S) Load Balancing, with its global scalability and intelligent routing capabilities, plays a significant role in this aspect.