VPC Service Controls enable organizations to enforce _______ boundaries for data access.
- Security
- Compliance
- Scalability
- Flexibility
Understanding the role of VPC Service Controls in enforcing security boundaries for data access is crucial for organizations aiming to protect their sensitive data within Google Cloud Platform.
What does VPC stand for in the context of cloud computing?
- Virtual Private Cloud
- Virtual Public Cloud
- Virtual Personal Computer
- Virtual Protocol Configuration
Understanding what VPC stands for and its role in cloud computing is essential for beginners to grasp the concept of network isolation and control in cloud environments.
In Pub/Sub, what is the role of a topic?
- A named resource to which messages are sent by publishers.
- A subscriber that receives messages from publishers and processes them.
- A storage location where messages are stored temporarily before being delivered to subscribers.
- A protocol used by publishers and subscribers to communicate with each other.
Understanding the role of topics in Pub/Sub is essential for designing efficient and scalable messaging architectures. Topics act as intermediaries between publishers and subscribers, facilitating the decoupling of components and enabling flexible message routing and distribution.
What is the purpose of Google Cloud Deployment Manager?
- Automate the creation and management of Google Cloud resources
- Monitor network traffic
- Schedule backups
- Manage user authentication
Google Cloud Deployment Manager simplifies resource management by automating the creation, deployment, and updating of infrastructure resources, enhancing efficiency and consistency in cloud environments.
Scenario: A company wants to deploy a TensorFlow model for image classification at scale. Which Google Cloud service should they use, considering scalability and efficiency?
- Google Kubernetes Engine (GKE)
- Google Compute Engine (GCE)
- Google Cloud Functions
- Google AI Platform
Google AI Platform is specifically designed to address the requirements of deploying machine learning models, including TensorFlow models, at scale on Google Cloud Platform. It offers features such as model versioning, scaling, and monitoring, making it the most suitable choice for the given scenario.
BigQuery is capable of analyzing and processing _______ datasets.
- Big
- Small
- Medium
- Structured
Understanding the scalability and capacity of BigQuery is essential for leveraging its capabilities effectively in data analytics projects. Recognizing its ability to handle large datasets is particularly important for intermediate users familiarizing themselves with the platform.
Google Compute Engine provides _______ virtual machine instances.
- Predefined
- Customizable
- Static
- Managed
Knowing that Google Compute Engine provides predefined virtual machine instances helps users understand the options available for deploying workloads on the platform without needing to configure every aspect of the instance.
Google Cloud _______ provides a managed environment for running TensorFlow workloads.
- AI Platform
- Compute Engine
- Cloud Storage
- Kubeflow
Google Cloud AI Platform provides a managed environment optimized for running TensorFlow workloads, offering features such as distributed training, model serving, and monitoring. Understanding the capabilities of AI Platform is essential for intermediate users seeking to leverage TensorFlow on Google Cloud Platform.
_______ is a feature of Cloud Functions that allows for the reuse of dependencies across function deployments.
- Dependency Injection
- Dependency Management
- Dependency Sharing
- Dependency Resolution
Understanding the features of Cloud Functions, such as dependency management, helps developers streamline the development and deployment processes, improve code maintainability, and reduce duplication of effort.
In Google Cloud, what feature allows users to seamlessly transition data between different storage classes based on access patterns?
- Object Lifecycle Management
- Data Transfer Service
- Access Control Lists
- Data Encryption
Object Lifecycle Management is a powerful feature of Google Cloud Storage that enables automatic and seamless transitions between storage classes based on predefined rules. Understanding how to leverage this feature can help optimize storage costs and resource utilization in Google Cloud environments.