The New Stack Podcast28 Mars 2024

LLM Observability: The Breakdown

LLM observability focuses on maximizing the utility of larger language models (LLMs) by monitoring key metrics and signals. Alex Williams, Founder and Publisher for The New Stack, and Janikiram MSV, Principal of Janikiram & Associates and an analyst and writer for The New Stack, discusses the emergence of the LLM stack, which encompasses various components like LLMs, vector databases, embedding models, retrieval systems, read anchor models, and more. The objective of LLM observability is to ensure that users can extract desired outcomes effectively from this complex ecosystem.

Similar to infrastructure observability in DevOps and SRE practices, LLM observability aims to provide insights into the LLM stack's performance. This includes monitoring metrics specific to LLMs, such as GPU/CPU usage, storage, model serving, change agents in applications, hallucinations, span traces, relevance, retrieval models, latency, monitoring, and user feedback. MSV emphasizes the importance of monitoring resource usage, model catalog synchronization with external providers like Hugging Face, vector database availability, and the inference engine's functionality.

He also mentions peer companies in the LLM observability space like Datadog, New Relic, Signoz, Dynatrace, LangChain (LangSmith), Arize.ai (Phoenix), and Truera, hinting at a deeper exploration in a future episode of The New Stack Makers.

Learn more from The New Stack about LLM and observability

Observability in 2024: More OpenTelemetry, Less Confusion

How AI Can Supercharge Observability

Next-Gen Observability: Monitoring and Analytics in Platform Engineering

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(300)

Why MotherDuck refuses to fork DuckDB

At a recent MCP developer summit, The New Stack spoke with Till Döhmen, AI lead atMotherDuck, about the company’s growing role in the evolving DuckDB ecosystem. Backed by investors includingTomasz Tun...

27 Maj 27min

JetBrains is selling independence as the rest of AI coding picks sides

JetBrains is positioning itself as the last major independent AI coding-tool vendor in a market increasingly tied to hyperscalers and foundation model labs. Speaking at Google Cloud Next, JetBrains VP...

21 Maj 26min

Why Block handed Goose to the Linux Foundation

What began as an internal developer tool atBlockhas evolved into a broader open-source initiative with industry backing. Goose, Block’s AI coding agent, followed a path similar to Amazon’s transformat...

15 Maj 19min

Fivetran's CPO: closed data stacks won't survive the agent era

At Google Cloud Next 2026, Fivetran Chief Product Officer Anjan Kundavaram argued that enterprise data systems are unprepared for the scale of AI-driven analytics. Unlike humans, AI agents can generat...

13 Maj 22min

The new FinOps problem isn't cloud bills

At Google Cloud Next 2026, Finout co-founder and CEO Roi Ravhon and Google Cloud FinOps lead Pathik Sharma discussed how FinOps is rapidly evolving for the AI era. Ravhon argued that while cloud FinOp...

12 Maj 28min

How Microsoft is governing thousands of Kubernetes clusters without manual intervention

Managing Kubernetes at fleet scale introduces significant complexity, especially as organizations expand from a few clusters to hundreds or thousands across cloud, on-premises, and edge environments. ...

7 Maj 25min

Why long-running AI agents break on HTTP and how Ably is fixing it

In this episode ofThe New Stack Makers, Matthew O’Riordan, CEO of Ably, explains how infrastructure originally built for human collaboration is now well-suited for long-running AI agents. While Ably i...

6 Maj 31min

Why the Linux Foundation adopted MCP, with Jim Zemlin and Mazin Gilbert

Agentic AI is advancing rapidly, with open-source projects racing to keep pace with real-world deployment. To accelerate progress, the Linux Foundation consolidated key technologies—Model Context Prot...

6 Maj 32min