Monitoring LLM behavior: Drift, retries, and refusal patterns

The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production.
InfoWorld

LiteLLM: An open-source gateway for unified LLM access

LiteLLM allows developers to integrate a diverse range of LLM models as if they were calling OpenAI’s API, with support for fallbacks, budgets, rate limits, and real-time monitoring of API calls. The ...
VentureBeat

Why “which API do I call?” is the wrong question in the LLM era

For decades, we have adapted to software. We learned shell commands, memorized HTTP method names and wired together SDKs. Each interface assumed we would speak its language. In the 1980s, we typed ...
Morningstar

Traefik Labs Advances LLM and MCP Runtime Governance with Composable Safety Pipeline, Multi-Provider Resilience, and Token-Level Cost Controls

New capabilities extend Traefik Hub's Triple Gate architecture with guardrail integrations from NVIDIA, IBM, and Microsoft running in parallel, plus the ability for organizations to write their own ...
InfoWorld

Protecting LLM applications with Azure AI Content Safety

New tools for filtering malicious prompts, detecting ungrounded outputs, and evaluating the safety of models will make generative AI safer to use. Both extremely promising and extremely risky, ...