AI Gateway

What Is Adaptive Load Balancing?

What Is Adaptive Load Balancing?

TL;DR * Adaptive load balancing distributes AI traffic across providers and API keys using live performance data instead of a fixed weight or round-robin rule. * Bifrost Enterprise recalculates route weights every 5 seconds from error rate, latency, and utilization, adding less than 10 microseconds to routing overhead. * Routes move

Best LLM Gateway to Manage Access for AI Models and Providers

Best LLM Gateway to Manage Access for AI Models and Providers

TL;DR * An LLM gateway centralizes access to every AI model and provider your teams use, so authentication, budgets, model allowlists, and audit trails live in one place instead of scattered across per-provider credentials. * The access controls that matter most in an LLM gateway are virtual keys, per-provider

Best AI Gateways for Production in 2026: 5 That Hold Up

Best AI Gateways for Production in 2026: 5 That Hold Up

TL;DR * The best AI gateway for production is the one that keeps requests flowing during provider outages, enforces budgets per consumer, and adds negligible latency. Bifrost meets all three: 11 microseconds of overhead at 5,000 requests per second, automatic provider failover, and virtual-key governance. * Five gateways run

What Happens When OpenAI Goes Down and How to Stay Online

What Happens When OpenAI Goes Down and How to Stay Online

TL;DR * An OpenAI outage takes down every application that calls OpenAI directly, at the same moment, because a direct integration has no second path for the request. * Retrying the same provider does not resolve a provider-wide outage, since every retry targets the same failing endpoint. * Bifrost retries transient

n8n AI Workflow: Routing LLM Nodes Through One Gateway

n8n AI Workflow: Routing LLM Nodes Through One Gateway

TL;DR * The Bifrost AI gateway is OpenAI-compatible, so any n8n LLM node that accepts a custom Base URL can route through it in a single credential change. * A single Bifrost virtual key becomes the per-workflow credential in n8n, carrying budget caps, rate limits, and provider allow-lists

OpenTelemetry for LLM Observability: Traces and Metrics

OpenTelemetry for LLM Observability: Traces and Metrics

TL;DR * LLM observability is the practice of capturing traces, metrics, and logs from model calls so teams can debug latency, cost, token usage, and errors across every provider in production. * OpenTelemetry (OTLP) is the vendor-neutral standard for that telemetry, and its GenAI semantic conventions define a common set

How to Cut Time to First Token (TTFT) for LLM Apps

How to Cut Time to First Token (TTFT) for LLM Apps

TL;DR * Time to first token (TTFT) is the delay between sending a request and receiving the first generated token. It is the latency number users actually feel, not average generation speed or tokens per second. * TTFT is dominated by three things: queue wait before a request starts processing, network