#AI Gateway

Articles about AI Gateway — exploring patterns, best practices, and real-world implementations in production systems.

8 posts tagged with ai gateway. ← All posts

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Pratik Dhanave · ·6 min read

Building and Operating an AI Gateway

You've seen what an AI gateway does; the last question is how to get one — build it, adopt an open-source proxy, or use a managed service — and how to run it once you have it. This closing post assembles the full architecture, weighs build-versus-buy honestly, and covers operating the gateway as the critical piece of infrastructure it becomes.

You've seen what an AI gateway does; the last question is how to get one — build it, adopt an open-source proxy, or use a managed service — and how to run it once you have it. This closing post assembles the full architecture, weighs build-versus-buy honestly, and covers operating the gateway as the critical infrastructure it becomes.

#AI Gateway#LLM Infrastructure#AI Engineering#Architecture#LLMs
Pratik Dhanave · ·5 min read

Observability and Governance

You can't manage what you can't see, and AI systems are unusually hard to see into — non-deterministic outputs, per-token costs, quality that's a matter of degree. Because every model call flows through the gateway, it's the one place you can observe all of it: what was called, what it cost, how long it took, and whether it was allowed. This post is about turning the gateway into your AI system's source of truth and its governance point.

You can't manage what you can't see, and AI systems are unusually hard to see into — non-deterministic outputs, per-token costs, quality that's a matter of degree. Because every model call flows through the gateway, it's the one place you can observe all of it and govern it: what was called, what it cost, how long it took, whether it was allowed. Turning the gateway into your AI system's source of truth.

#AI Gateway#Observability#Governance#LLM Infrastructure#AI Engineering#Reliability#LLMs
Pratik Dhanave · ·6 min read

Rate Limiting, Quotas, and Budgets

Nothing concentrates the mind like a surprise five-figure AI bill from one runaway loop, or one team's traffic spike exhausting the rate limit everyone shares. Because every model call flows through the gateway, it's the one place you can enforce limits and budgets that actually hold — protecting your spend, your providers' rate limits, and fairness across teams. This post is about spending control as a first-class gateway capability.

Nothing concentrates the mind like a surprise five-figure AI bill from one runaway loop, or one team's spike exhausting the shared rate limit. Because every model call flows through the gateway, it's the one place you can enforce limits and budgets that actually hold — protecting your spend, your providers' rate limits, and fairness across teams. Spending control as a first-class capability.

#AI Gateway#Cost Optimization#LLM Infrastructure#Governance#AI Engineering#LLMs
Pratik Dhanave · ·5 min read

Caching at the Gateway

Model calls are slow and expensive, and a surprising fraction of them are repeats or near-repeats. Caching at the gateway turns those into instant, free responses — and because the gateway sees all traffic, it's the one place a cache benefits every application at once. Beyond exact-match caching, semantic caching catches queries that mean the same thing in different words, which is where the real savings live.

Model calls are slow and expensive, and a surprising fraction are repeats or near-repeats. Caching at the gateway turns those into instant, free responses — and because the gateway sees all traffic, it's the one place a cache benefits every app at once. Beyond exact-match caching, semantic caching catches queries that mean the same thing in different words, where the real savings live.

#AI Gateway#Caching#LLM Infrastructure#Performance#AI Engineering#LLMs
Pratik Dhanave · ·6 min read

Reliability: Fallback, Retries, and Circuit Breakers

Model providers go down, rate-limit you, and time out — regularly. If your application calls one provider directly, its reliability is capped at that provider's. An AI gateway breaks that ceiling: because it can route across providers, a failure on one becomes a transparent retry on another. This post covers the reliability patterns that turn provider outages into non-events.

Model providers go down, rate-limit you, and time out — regularly. If your application calls one provider directly, its reliability is capped at that provider's. An AI gateway breaks that ceiling: because it can route across providers, a failure on one becomes a transparent retry on another. Retries, fallback, and circuit breakers — with an interactive request-flow sequence diagram.

#AI Gateway#Reliability#LLM Infrastructure#AI Engineering#LLMs
Pratik Dhanave · ·5 min read

Routing and Load Balancing

Once every model call flows through one place, that place can make an intelligent decision on every request: which model should serve this, and through which of your capacity? Routing picks the right model for the task; load balancing spreads traffic across providers and keys so no single limit or outage bottlenecks you. Together they turn the gateway from a passthrough into a control plane.

Once every model call flows through one place, that place can make an intelligent decision on every request: which model should serve this, and through which of your capacity? Routing picks the right model for the task; load balancing spreads traffic across providers and keys so no single limit or outage bottlenecks you. Together they turn the gateway into a control plane.

#AI Gateway#LLM Infrastructure#Load Balancing#AI Engineering#LLMs
Pratik Dhanave · ·5 min read

The Unified API

The first thing an AI gateway gives you is one interface to every model. Instead of your applications learning each provider's SDK, request format, and quirks, they speak a single API and the gateway translates. That translation layer is what decouples your code from any one vendor — and it's what makes model-swapping a config change instead of a rewrite.

The first thing an AI gateway gives you is one interface to every model. Instead of your applications learning each provider's SDK, request format, and quirks, they speak a single API and the gateway translates. That translation layer is what decouples your code from any one vendor — and makes model-swapping a config change instead of a rewrite.

#AI Gateway#LLM Infrastructure#APIs#AI Engineering#LLMs
Pratik Dhanave · ·5 min read

Why You Need an AI Gateway

The moment your application talks to more than one model — or one model but seriously — you accumulate a pile of cross-cutting concerns: provider APIs that differ, outages you must survive, costs you must control, calls you must log. An AI gateway is the single control point that handles all of it, sitting between your applications and every model provider. This series builds one from first principles.

The moment your application talks to more than one model — or one model but seriously — you accumulate cross-cutting concerns: differing provider APIs, outages, costs, logging. An AI gateway is the single control point that handles all of it, sitting between your applications and every model provider. This series builds one from first principles, with interactive architecture diagrams.

#AI Gateway#LLM Infrastructure#AI Engineering#Architecture#LLMs

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.