Serverless

A practical guide to building MCP servers on Cloudflare Workers, covering architecture, code examples with D1 and R2, and production patterns for exposing Cloudflare resources to AI assistants.

Discover how Apache Pulsar Functions enable developers to process streaming data and build event-driven microservices at scale without the overhead of external frameworks.

Introduction Retrieval‑Augmented Generation (RAG) has become the de‑facto pattern for building intelligent applications that combine the creativity of large language models (LLMs) with the precision of external knowledge sources. While the classic RAG loop—query → retrieve → augment → generate—works well for batch or low‑latency use‑cases, many modern products demand real‑time responses at sub‑second latency, massive concurrency, and the ability to evolve the knowledge base continuously. Achieving this level of performance forces architects to rethink three core components: ...

Introduction Serverless platforms have democratized backend development. With a few lines of JavaScript or Python, developers can deploy functions that automatically scale, handle routing, and pay‑only-for‑what‑they‑use. However, as applications mature, the limits of traditional serverless become evident: cold‑start latency, opaque runtime environments, limited language choices, and constrained performance for compute‑intensive workloads. Enter Rust and WebAssembly (Wasm). Rust offers memory safety without a garbage collector, deterministic performance, and a vibrant ecosystem for networking and cryptography. WebAssembly provides a portable binary format that runs in lightweight sandboxes across browsers, edge runtimes, and even standalone VMs. When combined, they enable high‑performance microservices that run at the network edge, delivering millisecond‑level response times while preserving the operational simplicity of serverless. ...

Table of Contents Introduction Fundamentals of Retrieval‑Augmented Generation (RAG) Why Scaling RAG Is Hard Distributed Vector Indexing 4.1 Sharding Strategies 4.2 Replication & Consistency 4.3 Popular Open‑Source & Managed Solutions Serverless Compute Orchestration 5.1 Function‑as‑a‑Service (FaaS) 5.2 Orchestration Frameworks Bridging Distributed Indexes and Serverless Compute 6.1 Query Routing & Load Balancing 6.2 Latency Optimizations 6.3 Cost‑Effective Scaling Practical End‑to‑End Example 7.1 Architecture Overview 7.2 Code Walk‑through Performance Tuning & Best Practices 8.1 Quantization & Compression 8.2 Hybrid Search (Dense + Sparse) 8.3 Batching & Asynchronous Pipelines Observability, Monitoring, and Security Real‑World Use Cases Future Directions Conclusion Resources Introduction Retrieval‑Augmented Generation (RAG) has emerged as a powerful paradigm for building knowledge‑aware language models. By coupling a large language model (LLM) with an external knowledge store, RAG can answer factual questions, ground hallucinations, and keep responses up‑to‑date without retraining the underlying model. ...