Firebase Hosting- Firebase Hosting provides fast and secure hosting for your web app, static and dynamic content, and microservices.
Firebase Hosting is production-grade web content hosting for developers. With a single command, you can quickly deploy web apps and serve both static and dynamic content to a global CDN (content delivery network). You can also pair Firebase Hosting with Cloud Functions or Cloud Run to build and host microservices on Firebase.
Key capabilities of Firebase Hosting:
Serve content over a secure connection:- The modern web is secure. Zero-configuration SSL is built into Firebase Hosting, so content is always delivered securely.
Host static and dynamic content plus microservices:- Firebase Hosting supports all kinds of content for hosting, from your CSS and HTML files to your Express.js microservices or APIs.
Deliver content fast: Each file that you upload is cached on SSDs at CDN edges around the world and served as gzip or Brotli. We auto-select the best compression method for your content. No matter where your users are, the content is delivered fast.

Compliance Reports Manager, GDPR Home Page, Compliance Offerings
GCP provides three main compliance resource webpages
Compliance Reports Manager - https://cloud.google.com/security/compliance/compliance-reports-manager

Compliance Offerings - https://cloud.google.com/security/compliance/offerings GDPR Resource Center - https://cloud.google.com/security/gdpr/resource-center At Google Cloud, we champion initiatives that prioritize and improve the security and privacy of customer personal data, and want you, as a Google Cloud customer, to feel confident using our services in light of GDPR requirements. If you partner with Google Cloud, we will support your GDPR compliance efforts

BigQuery ML lets you create and execute machine learning models in BigQuery using standard SQL queries.

The correct answer is C. A hybrid-cloud approach. Here's why:
* Context of the Question: The organization wants to use Google Cloud's advanced machine learning capabilities while maintaining data storage on-premises due to regulatory requirements.
* Google Cloud Product Relevance:
* A hybrid-cloud approach combines on-premises infrastructure with cloud services. This approach allows organizations to keep sensitive data on-premises while leveraging cloud services for additional computing capabilities, such as advanced machine learning. Google Cloud offers tools like Anthos and Google Cloud's hybrid and multi-cloud solutions to facilitate this integration, enabling the organization to use cloud-based machine learning tools while keeping data in their local data center.
* Why Not Other Options:
* A. A private-cloud approach: This refers to a cloud environment that is entirely operated within the organization's own infrastructure, which would not provide access to Google Cloud's ML capabilities.
* B. A multi-cloud approach: While multi-cloud involves using services from multiple cloud providers, it does not specifically address the requirement to keep data on-premises.
* D. A public-cloud approach: This would involve moving data to the public cloud, which contradicts the requirement to keep data stored on-premises.
Google Cloud Digital Leader References:
* Refer to Hybrid and Multi-Cloud Solutions in Google Cloud documentation to understand how Google Cloud can integrate with on-premises data centers while providing cloud services.