Apr 4
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Learn how to implement monitoring and observability for Hugging Face-based ML and AI systems using OpenTelemetry and SigNoz. In this video, we walk through instrumenting Hugging Face models and pipelines to capture traces, metrics, and logs, then visualize everything in SigNoz for real-time insights. You’ll learn how to debug model performance, track latency, and identify bottlenecks across your ML workflows in production. More about SigNoz: SigNoz - Monitor your applications and troubleshoot problems in your deployed applications, an open-source alternative to DataDog, New Relic, etc. Backed by Y Combinator. SigNoz helps developers monitor applications and troubleshoot problems in their deployed applications. SigNoz uses distributed tracing to gain visibility into your software stack. SigNoz website - https://signoz.io SigNoz Github repository - https://github.com/SigNoz/signoz SigNoz Hugging Face Docs - https://signoz.io/docs/huggingface-observability/ You can find the official LLM documentation here - https://signoz.io/docs/llm-observability/ Come say Hi to us on Slack - https://signoz.io/slack If you need any clarification or find something missing, feel free to raise a GitHub issue with the label documentation or reach out to us at the community slack channel.