Alternatives
Products that do what 500 years of Joseon court omens as an observability dashboard does
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2022 · opendatadiscovery.org
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A common open source approach to observability will begin with databases and visualizations for telemetry - Grafana, Prometheus, Jaeger. But observability doesn’t begin and end here: these tools require configuration, dashboard customization, and may not actually pinpoint the data you need to mitigate system risks. Coroot was designed to solve the problem of manual, time-consuming observability analysis: it handles the full observability journey — from collecting telemetry to turning it into actionable insights. We also strongly believe that simple observability should be an innovation…
2025 · github.com
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Hey HN, Nir, Gal and Tomer here. We’re open-sourcing a set of extensions we’ve built on top of OpenTelemetry that provide visibility into LLM applications - whether it be prompts, vector DBs and more. Here’s the repo: https://github.com/traceloop/openllmetry. There’s already a decent number of tools for LLM observability, some open-source and some not. But what we found was missing for all of them is that they were closed-protocol by design, vendor-locking you to use their observability platform or their proprietary framework for running your LLMs. It’s still early in the…
2023 · github.com
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If you've built any web-based app in the last 15 years, you probably used something like Datadog, New Relic, Sentry, etc. to monitor and trace your app, right? Why should it be different when the app you're building happens to be using LLMs? So today we're open-sourcing OpenLLMetry-JS. It's an open protocol and SDK, based on OpenTelemetry, that provides traces and metrics for LLM JS/TS applications and can be connected to any of the 15+ tools that already support OpenTelemetry. Here's the repo: https://github.com/traceloop/openllmetry-js A few months ago we launched…
2024 · github.com
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Trace LLM requests + costs with OpenTelemetry monitoring
Oct 2025
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Hello Everyone, I'm excited to introduce a new open-source observability platform and would love to hear your feedback. We are aware that there are lots of open-source/commercial tools out there. However, we believe that monitoring the clusters and extracting actionable insights requires deep know-how about the tools/domain. We mainly focused on this problem. - Alaz is an eBPF agent installed on your K8s cluster as DaemonSet. Thanks to eBPF, Alaz collects traces directly from Linux kernels. This means there's no need for sidecars, instrumentations, or service restarts. - The UI not…
2023 · github.com
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2015 · joeltg.github.io
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2021 · incidents.sh
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2015 · github.com
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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
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2024 · github.com
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
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Morning HN - - I have a quick story about building a startup and misreading the market, and an ask. (The ask: Try out our product>> https://app.datable.io/auth/sandbox) My name is Julian Giuca and I was an early employee at New Relic, where I led their Logging product until 2022. It’s safe to say I have opinions about logs. Sometimes I think they are great. Too often I think we can do much better. When people talk to me about logs, they reliably complain about observability costs. Engineering leaders have said it feels “like a protection racket”, where you're forced to…
2025
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Hi HN, Hugh and Vince here. LLMonitor helps you record, trace & search your LLM queries and chatbot conversations. You can also capture user feedback on your frontend and correlate it with backend LLM queries then use that to fine-tune your own models. The project started has an internal tool in our previous (failed) AI startup. We’re aware the LLM observability space is very crowded. Apart from being open-source, we differentiate with: - Model-agnostic and minimal lock-in (no MITM of requests). - High focus on DX and dashboard clarity. - Support for complex scenarios: e.g. a chatbot that…
2023 · github.com
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I built Chronoscope, a project to explore the world through time. I've been wanting to do this for a while, after being inspired by Ollie Bye's "History of the World" video several years ago. I'm not the first person to have done this - resources like OpenHistoricalMaps are amazing. But, I noticed there were a few disparate datasets / academic databases online, so I combined them together as best as I could (I've linked all sources in the app). To make it more interesting, I also included: - Notable events from the time period (geolocated where possible), sourced from wikidata - Ancient…
Mar 2026 · shiphappens.xyz
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2021 · monika.hyperjump.tech
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2013 · nli-labs.net
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