cloudflare

Choosing Cloudflare storage requires evaluating data patterns against service capabilities. A unified decision framework maps KV for edge key-value reads, D1 for relational SQL queries, and R2 for large object storage to ensure cohesive architecture.

Building a full-stack edge application involves combining Cloudflare Pages for frontend hosting with Workers for serverless compute. Patterns and references across these services enable fast, secure deployments with persistent storage and security controls.

Yes, you can use Terraform and Pulumi for Cloudflare infrastructure-as-code orchestration. Unified guidance includes applying these tools to provision and manage Workers, Pages, and storage bindings for scalable and secure deployments.

Integrating Cloudflare AI services involves combining Workers AI for model inference and Vectorize for vector search within edge compute workflows. Decision trees and examples demonstrate how to embed these services for cohesive, scalable AI deployments.

Using Cloudflare Durable Objects is appropriate when stateful compute requires strong consistency and real-time coordination across connections. The platform decision framework distinguishes DO from standard stateless Workers to guide scalable architecture choices.

Cloudflare platform guidance consolidates product selection into a single decision framework. It provides decision trees and references to evaluate edge compute, storage, security, and networking options to help select the right product for a given task.