Self-Hosted LLM Gateway: Open-source options and how to deploy one
Why and how to run a self-hosted LLM gateway: open-source options, deployment (Docker/Kubernetes), data control, and SaaS vs self-hosted trade-offs.
AI Gateway Comparison: Top Solutions in 2026
A side-by-side comparison of the leading AI gateways in 2026 — WSO2, Kong, Portkey, LiteLLM, Cloudflare, and Helicone — across deployment, cost control, security, and observability.
What Is an AI Gateway? Features, Benefits and How It Works
Learn what an AI gateway is, how it works, and how it differs from an API gateway: multi-model routing, token cost control, guardrails, and observability for LLM traffic.
AI Gateway Security: Guardrails for LLM Traffic
A guide to the concrete controls that secure LLM and agent traffic: prompt-injection defense, PII redaction, authentication and RBAC, guardrails, and audit logging.
AI Gateway vs API Gateway: Key Differences
A side-by-side breakdown of how AI gateways and API gateways differ, where they overlap, and how to decide where each one belongs in your stack.
AI Gateway Observability: Key Metrics, Logging, and Tracing for LLM Traffic
What AI gateway observability is, the key metrics to track (tokens, cost, latency, errors), and how logging, tracing, and OpenTelemetry fit in.
Best LiteLLM Alternatives in 2026
Compare the best LiteLLM alternatives in 2026 on routing, governance, security, and deployment after the LiteLLM supply-chain attack.
LLM Cost Control: Strategies to Cut AI Spend
How to control LLM costs with token tracking, budgets, caching, model routing, and prompt optimization, and why a gateway is the best place to enforce it.
LLM Routing: How It Works, Strategies, and Why It Matters
What LLM routing is, static vs dynamic vs model-aware strategies, and how routing cuts LLM cost and improves reliability at the gateway layer.
Prompt Injection Defense: Techniques That Actually Work
How to defend against prompt injection: input validation, prompt templating, trust boundaries, human-in-the-loop, and gateway guardrails. Practical techniques.
PII Redaction for LLMs: How to Do It Right
How to redact PII before it reaches an LLM: detection with regex and NER, gateway-level filtering of prompts and responses, and compliance with GDPR, HIPAA, and PCI. Includes a complete, end-to-end WSO2 AI Workspace tutorial.
LLM Fallback: How to Build Resilient AI Applications
What LLM fallback is and how to implement it: fallback chains, retries with backoff, and circuit breakers, to keep AI apps running through provider outages.
MCP Implementations: How to Implement MCP
A practical guide to MCP implementations: architecture, official SDKs, reference/example servers, a step-by-step build, and a hands-on walkthrough governing an existing server with WSO2 AI Workspace.
REST API to MCP Server: A Practical Guide
Learn how to turn a REST API into an MCP server: map endpoints to tools, handle auth and schemas, and avoid the auto-convert trap. Step-by-step with examples.
Semantic Caching for LLMs: Cut Cost & Latency
What semantic caching is, how it works (embeddings + similarity), and how it cuts LLM cost and latency, plus best practices and gateway-level implementation.
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