Did you know that @LaunchDarkly supports OpenLLMetry? You can use LaunchDarkly observability features to view and analyze large language model (LLM) spans. LLM observability provides visibility into h...
Over the last several weeks, I designed and implemented an end-to-end LLM observability and operations platform that takes a RAG-based assistant beyond the prototype stage and turns it into a producti...
Worth a read: a clear take on LLM observability and cost management on HPE Private Cloud AI. Practical perspective on what it takes to run LLMs responsibly.
Kudos to Santosh Nagaraj and Claudio Calde...
We are excited to announce four new integrations within watsonx․ai, helping organizations power LLM observability for enterprise AI. Check them out below ⤵ Fairly AI FAIRLY AI is proud to announce our...
Over the past year, we’ve seen rapid progress in LLM observability — but also a growing fragmentation. On one side, developers are adopting tools like Langfuse, LangSmith or Helicone to understand pro...
Hello, and welcome to the August 2025 ClickHouse newsletter! This month, we have lightweight updates introduced in ClickHouse 25.7, LLM observability for LibreChat with ClickStack, a Gemini vs Claude ...
"Model testing and monitoring refers to practices for enabling quality, resilience, stability and sustainable decision making with AI systems."
This perfectly highlights why LLM evaluation and observ...
🚀 From “It works on my machine” to “Here’s exactly what’s happening with 1k tokens/sec in production”
Last experiment I was manually running Python scripts to measure LLM performance. 🤡
This week? I ...
How do you observe generative AI (GenAI) systems in production when traditional metrics fall short?
As part of the I/built with Elastic series at Elastic{ON} Singapore, Adrian Cole, Principal Engine...
This article explores how the OpenRouter integration for Grafana Cloud enhances visibility into the performance and costs of AI workloads in production. I found it interesting that effective observabi...
Paper Project The authors observe that Reinforcement Learning with Verifiable Rewards (RLVR) improves LLM reasoning by selectively optimizing high-entropy tokens (critical points that steer reasoning ...
🚀 Self-Hosted LLM Observability is here.
Stop relying on black-box APIs — run your own stack with vLLM + GLM-4.7-Flash + Grafana on Kubernetes and get full visibility from GPU metrics to token-level t...
Self-Hosted Grafana Plugin for OpenClaw Enables Local LLM Monitoring and Security
📌 OpenClaw’s new self-hosted Grafana plugin brings enterprise-grade observability to local LLM agents-enabling real-t...
This article highlights how the OpenRouter integration for Grafana Cloud enhances visibility into the performance and costs of AI workloads in production. I found it interesting that such tools can si...
Upsonic now adds a Langfuse integration for agent tracing.
Langfuse is an open source observability platform for LLM apps. With this integration you can trace your Upsonic agents end to end. Every LL...
