Bifrost AI Gateway: Monitor Every Request, Token, and Cost
A guide to AI gateway observability, covering the telemetry captured per request and how to export it to Prometheus, OpenTelemetry or Datadog.
Kamya Shah
Semantic Caching for LLMs: How It Works and the Tools That Do It
TL;DR
* Semantic caching for LLMs serves a stored response when a new request's embedding falls within a similarity threshold of a cached one, so paraphrased repeats skip the model call.
* Bifrost runs an exact hash lookup first and a semantic lookup only on a miss, so identical
How to Govern AI Desktop Apps Like Claude Desktop
TL;DR
* AI desktop apps like Claude Desktop send prompts straight to model providers, so a gateway alone cannot govern them unless their traffic is routed through it.
* Bifrost, the AI gateway, is the control plane for virtual keys, budgets, guardrails, and audit logs; Bifrost Edge enforces those same policies
AI Observability Platform for Monitoring LLM Costs
A guide to monitoring LLM costs with an AI observability platform, covering the cost signals to track and how to turn them into budgets.
LLM Observability with Prometheus: Metrics and Dashboards
A guide to LLM observability with Prometheus, covering the metrics that matter, scraping the gateway and building Grafana dashboards.
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
Enterprise AI Security: A Secure AI Deployment Checklist
A seven-control checklist for secure AI deployment, covering the gateway, access control, guardrails, data isolation, shadow AI and audit logging.