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Alternatives

Products that do what sip-exporter does

Prometheus-native SIP and RTP monitoring with eBPF

  1. 1PI
  2. 2

    Trace LLM requests + costs with OpenTelemetry monitoring

    Oct 2025

  3. 3
    Heron 105

    Wireshark for AI Agents: passive eBPF observability

    Jun 2026

  4. 4
    TraceLLM100

    OpenTelemetry for production AI applications

    Jul 2026 · tracellm.in

  5. 5OP
  6. 6

    Your observability stack, managed by us completely for free

    2021

  7. 7BC
  8. 8
    TaVivo100

    Monitor APIs or web services based on a configurable time

    2022

  9. 9

    Kubernetes native health check platform

    2023

  10. 10SH
  11. 11MI
  12. 12PO
  13. 13PE
  14. 14SA
  15. 15TK
  16. 16MO

    2021 · monika.hyperjump.tech

  17. 17CA

    Hey HN, We launched Coroot a while ago as an open source observability tool that collects complete telemetry using eBPF. Today we are adding a major new capability: Coroot enterprise now includes AI-powered Root Cause Analysis. When an incident happens (like an SLO violation), Coroot: - Automatically kicks off an RCA - Summarizes what went wrong in plain English - Suggests immediate fixes - Shows the full investigation using metrics, logs, traces, and profiles With most tools, the quality of root cause analysis depends on how well the system is instrumented. Coroot takes a different…

    2025 · coroot.ai

  18. 18FE

    2017 · github.com

  19. 19PA

    I've added Prometheus and OpenTelemetry support to my beloved open-source pet project called Kuvasz, which is a cloud-native, feature-rich uptime & SSL monitoring service, written in Kotlin. If you already have an observability stack and you only need a free uptime/SSL monitor, you can easily integrate Kuvasz with it. Let me know what you think or what you miss from Kuvasz!

    2025 · kuvasz-uptime.dev

  20. 20FP

    2016 · proxycheck.io

  21. 21AU

    Hey HN! We built a tool that uses eBPF to discover AI services and their data flows in Kubernetes clusters. Modern AI apps often follow this pattern: 1. Service receives request 2. Queries database (PostgreSQL/Redis/MongoDB) 3. Sends data to LLM API (OpenAI/Anthropic/Bedrock) 4. Consumes or returns the AI generated response Security teams often don't know: - Which services are making AI calls - What databases they're accessing first - Whether PII is being sent to third-party APIs - What libraries and packages are being used for AI Our eBPF based tool attaches to network…

    Jan 2026 · aurva.io

  22. 22SA
  23. 23MY

    LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!

    2023 · github.com

  24. 24SC

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