Demo applications and reference architectures
Learn how you can use KV within your existing application and architecture.
Demo applications
Explore the following demo applications for KV.
- shrty.dev: A URL shortener that makes use of KV and Workers Analytics Engine. The admin interface uses Function Calling. Go Shorty!
- Queues Web Crawler: An example use-case for Queues, a web crawler built on Browser Rendering and Puppeteer. The crawler finds the number of links to Cloudflare.com on the site, and archives a screenshot to Workers KV.
Reference architectures
Explore the following reference architectures that use KV:
- A/B-testing using Workers: A/B testing, also known as split testing, is a fundamental technique in the realm of web development, allowing teams to iteratively refine and optimize their digital experiences. A/B testing involves comparing two versions of a web page or app feature to determine which one performs better in achieving a predefined goal, such as increasing conversions, engagement, or user satisfaction.
- Fullstack Applications: Full-stack web applications leverage a combination of frontend and backend technologies, collectively forming a stack that powers the entire application. This technology stack encompasses various tools, frameworks, and languages, each serving a specific purpose within the development ecosystem.
- Serverless global APIs: Serverless APIs represent a modern approach to building and deploying scalable and reliable application programming interfaces (APIs) without the need to manage traditional server infrastructure. These APIs are designed to handle incoming requests from users or other systems, execute the necessary logic or operations, and return a response, all without the need for developers to provision or manage underlying servers.
- Serverless image content management: In this reference architecture diagram, we reveal how to leverage various components of Cloudflare’s ecosystem to construct a scalable image management solution. This solution integrates moderation principles via Cloudflare’s Workers AI platform and performs image classification through inference at the edge. The storage of images is handled by Cloudflare’s R2 product, an S3 API-like object storage system, while metadata is stored in a key/value store to enable content augmentation.