Generative AI Observability

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Observe and troubleshoot your generative AI applications with comprehensive observability across LLMs, AI agents, and vector databases in-context with your existing applications and services.

Why Generative AI Observability matters

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Building production-ready generative AI applications introduces unique challenges. Your AI applications need specialized monitoring to:

  • Control costs: Track token usage and API costs across multiple LLM providers in real-time
  • Ensure performance: Monitor latency, throughput, and response quality at every layer of your AI stack
  • Debug complex workflows: Trace requests through multi-step agent workflows, RAG pipelines, and tool calls
  • Maintain reliability: Detect errors, rate limits, and quality degradation before they impact users

What you can monitor

Instana provides capabilities ranging from unified observability and real-time cost tracking to tracing of agentic workflows and intelligent alerting on golden signals across the full AI technology stack.

LLM providers

Monitor interactions with leading AI providers including IBM watsonx.ai, OpenAI, Amazon Bedrock, Anthropic Claude, Google Gemini, Groq, DeepSeek, and more. Track every API call with detailed metrics on latency, token consumption, and costs.

AI agent frameworks

Gain visibility into complex agent workflows built with LangChain, LangGraph, CrewAI, OpenAI Agents, Langflow, and Google ADK. Understand how agents make decisions, use tools, and orchestrate multi-step tasks.

Vector databases

Monitor vector database operations, embedding generation, and similarity searches that power your RAG (Retrieval-Augmented Generation) applications.

Infrastructure and hosting

Track GPU utilization, vLLM performance, and containerized AI workloads to optimize resource allocation and scaling.

References