Brief

Databricks has introduced a new feature allowing AI agents to write OpenTelemetry traces directly into Unity Catalog tables. This integration aims to overcome the limitations of traditional observability tools, which struggle with the high volume and cost of AI trace data. By storing traces in the Databricks Lakehouse, users can leverage familiar tools like SQL for analysis, apply governance, and integrate trace data into evaluation and monitoring workflows for continuous AI agent improvement. AI

STRIDE-GPT is an open-source tool designed to generate STRIDE threat models for AI applications by analyzing architecture descriptions. It emphasizes treating LLM-specific assets like system prompts, RAG documents, and agent reasoning chains as first-class components in the threat modeling process. The tool requires detailed architecture descriptions, including components, data flows, and trust boundaries, to produce effective security models. Additionally, it highlights the importance of comprehensive logging for post-incident reconstruction and suggests layered rate limiting strategies to prevent token drain attacks. AI

This article details how to achieve end-to-end observability for large language model inference servers like vLLM and TGI. It highlights that standard observability tools fall short due to unique LLM serving characteristics such as variable latency, dynamic batching, and the critical role of the KV cache. The author proposes a layered approach, correlating user-facing token rendering with underlying GPU silicon metrics, and provides specific signals to monitor at each layer, from business costs down to GPU hardware. AI

Bronto has released a new integration that allows users to send monitoring data from Anthropic's Claude Code to its platform. This integration enables developers and teams to gain insights into AI-assisted coding usage, including productivity metrics, cost visibility, and prompt auditing. The setup can be achieved through a direct connection using OpenTelemetry or by routing logs via an existing OpenTelemetry collector. AI

This article details how to integrate Spring AI applications with observability tools like LangSmith or OpenLIT. The integration leverages OpenTelemetry and Arconia to provide key insights into AI-infused applications, which are crucial for production-grade systems. AI