LLM observability: tools for developers

Monitoring, traces, evaluation and quality tracking for LLM applications. An entry can appear under several use cases when its topics or description provide several explicit signals.

Use case

Activity

Sort by

4 entries in this view.

Tool ranking

Ranked by measured growth, normalized across sources. Raw values keep their source-specific window, shown under each tool; a change requires at least two snapshots from the last 7 days.

  1. 1

    Other
    Active

    Open source observability platform for logs, metrics, traces, frontend monitoring, pipelines and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage…

    TypeScriptLicense: AGPL-3.0
    • analytics
    • apm
    • datadog
    • elasticsearch
    • grafana

    githubmeasured growthOpen source ↗

    21 615GitHub stars+96 (+0.45 %)
  2. 2

    Agent
    Active

    The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models…

    PythonLicense: Apache-2.0
    • agentops
    • agents
    • ai
    • ai-governance
    • apache-spark

    githubmeasured growthOpen source ↗

    27 783GitHub stars+82 (+0.30 %)
  3. 3

    Library
    Active

    Prefect is a workflow orchestration framework for building resilient data pipelines in Python.

    PythonLicense: Apache-2.0
    • automation
    • data
    • data-engineering
    • data-ops
    • data-science

    githubmeasured growthOpen source ↗

    23 766GitHub stars+66 (+0.28 %)
  4. 4

    Other
    Active

    A high-performance observability data pipeline.

    RustLicense: MPL-2.0
    • agent
    • cloud-native
    • data-transformation
    • datadog
    • etl

    githubmeasured growthOpen source ↗

    22 509GitHub stars+40 (+0.18 %)

Page 1 of 1 · 4 entries