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Alternatives

Products that do what ML condenses billions of logs into a tiny snapshot your LLM can debug does

Hi HN, I'm Kaushik, and I built Rocketgraph. I believe that while other spaces have caught up to the AI wave, the observability space is still lagging behind, using the same tools and dashboards that we use to analyse logs from human-written code. But now the code is written and debugged by AI, so we need to rethink how we do observability where the observer itself is an AI. The problem that I run into is when an alert fires, I have to manually check the Grafana dashboards and write LogQL queries, which is pretty much like greping. But production usually breaks due to a schema mismatch, or a…

  1. 1

    Trace, evaluate, and improve AI agents in production

    Aug 2026 · telerik.com

  2. 2

    Fix bugs faster with open source, AI native observability

    2025

  3. 3AW

    Hey HN, I wanted to show you a product a small team and I have been working on for 4 years. https://jam.dev It’s called Jam and it prevents product managers (like I used to be) from being able to create vague and un-reproducible bug tickets (like I used to create). It’s actually really hard as a non-engineer to file useful bug tickets for engineers. Like, sometimes I thought I included a screenshot, but the important information the engineer needed was what was actually right outside the boundary of the screenshot I took. Or I'd write that something "didn't work" but the engineer…

    2024

  4. 4
    superlog500

    Make your product bug-free

    Jun 2026 · superlog.sh

  5. 5IB

    Hey HN, Some of you were really interested in Postgres logging with pgAudit in my previous post here: https://news.ycombinator.com/item?id=37082827 So I built this logger: https://rocketgraph.io/logger-demo using pgAudit to show you what can be done with Postgres auditing. It offers some powerful features like "get me all the CREATE queries that ran in the past hour". These are generated by AWS RDS Instance running on my Rocketgraph account. Then they are forwarded to Cloudwatch for complex querying. In the future we can connect these logs to slack so you can…

    2023 · rocketgraph.io

  6. 6PI

    Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…

    2018 · parabola.io

  7. 7

    Observability copilot to resolve production issues instantly

    2025

  8. 8OA

    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

  9. 9LD

    Hi HN! We’re Adrien and Kanav. We met at our previous job, where we spent about a third of our lives combating a constant firehose of bugs. In the hope of reducing this pain for others in the future, we’re working on automating debugging. We’re currently working on a platform that ingests logs and then automatically reproduces, root causes and ultimately fixes production bugs as they happen. You can see some of our work on this here - https://news.ycombinator.com/item?id=39528087 As we were building the root-cause phase of our automated debugger, we realized that we developed…

    2024 · github.com

  10. 10TT

    Hi HN, I'm the CEO at https://replay.io. We've been building a time travel debugger for web apps for several years now (previous HN post: https://news.ycombinator.com/item?id=28539247) and are combining our tech with AI to automate the debugging process. AIs are really good at writing code but really bad at debugging -- it's amazing to use Claude to prompt an app into existence, and pretty frustrating when that app doesn't work right and Claude is all thumbs fixing the problem. The basic reason for this is a lack of context. People can use devtools to understand…

    2025 · nut.new

  11. 11

    Marketplace to buy reports of cloud services you use.

    2015

  12. 12

    Live logs inside your IDE to Debug without context switching

    Apr 2026 · mobileagents.io

  13. 13
    LLMonitor128

    Open source monitoring and production toolkit for AI apps

    2023

  14. 14

    Trace LLM requests + costs with OpenTelemetry monitoring

    Oct 2025

  15. 15HS

    Hey HN – Stefan and Elijah here from DAGWorks (http://dagworks.io/, YC W23). If you don’t remember us from our previous HN launch (https://news.ycombinator.com/item?id=35056903), we’re the authors of Hamilton (https://github.com/dagworks-inc/hamilton), an open-source library for building self-documenting, modular dataflows in python that works for data, ML, LLM pipelines, & even web-workflows. We’ve been developing this UI for a while and we’re excited to say we open-sourced it! It comes out of the box with the following capabilities, and…

    2024 · github.com

  16. 16SY

    Hey HN, we’re Nico and Arseniy, co-founders of Superlog (https://superlog.sh). We're building a self-installing, self healing observability tool meant not to be opened. It has a wizard that daily sets up proper logging and an agent that investigates errors and opens PRs. Super short demo: https://www.youtube.com/watch?v=xFhU9Mk247M. In our earlier startups, we tried Sentry, Datadog, Grafana, Dash0, and nothing was good enough. Proper telemetry and alerting still requires a ton of manual setup. We struggled with adding good logs, so debugging was tough, especially as…

    May 2026 · superlog.sh

  17. 17

    Visual debugging, tracing, and replay for agent workflows

    Apr 2026 · agenticlens.in

  18. 18LA

    Hello HN! I'm an Android OS engineer. I've worked with AOSP and Linux kernels all my career and always wondered about lack of sophisticated tools to debug and analyze system-level logs. Always had to resort to manually skimming through large log files to find something I needed to. With the rise of LLMs and the AI-age, I felt it was a great opportunity to build something for OS engineers, which is what led to logcat.ai! We are building the industry-first observability platform for system level intelligence. Think "Datadog for operating systems" instead of applications. Currently, we support…

    2025 · logcat.ai

  19. 19OS

    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

  20. 20RB

    We built HALO (Hierarchal Agent Loop Optimizer), an open-source tool for debugging and optimizing AI agents using their execution traces. It’s a loop. Run your agent, feed the traces to HALO, get the report, apply the fixes, then re-run your agent. HALO takes in OTEL compliant traces from AI agents using tracing frameworks such as Langfuse, Arize/OpenInference, or even just plain JSONL. It uses an RLM (Recursive Language Model) to more efficiently break trace analysis into smaller subproblems in order to find recurring patterns across large amounts of data and fix systemic issues that…

    Jun 2026 · github.com

  21. 21

    Bounded-memory telemetry for observability

    Jul 2026 · sbalavignesh123.github.io

  22. 22

    Track AI Agents with a single line of code

    Mar 2026 · tracium.ai

  23. 23LO

    Hi HN, I'm Robel. I built LogClaw because I was tired of paying for Datadog and still waking up to pages that said "something is wrong" with no context. LogClaw is an open-source log intelligence platform that runs on Kubernetes. It ingests logs via OpenTelemetry and detects anomalies using signal-based composite scoring — not simple threshold alerting. The system extracts 8 failure-type signals (OOM, crashes, resource exhaustion, dependency failures, DB deadlocks, timeouts, connection errors, auth failures), combines them with statistical z-score analysis, blast radius, error velocity, and…

    Mar 2026 · logclaw.ai

  24. 24SA

    Hi all! I built Spikelog because I kept wanting to track simple numbers over time but every time I looked at proper observability tools, I'd bounce off the setup complexity. I wanted to make something that didn't require a lot of thinking to use. Spikelog is made to be as simple as possible: - POST a JSON with chart name + value (you can add some tags as well but I've not tested this part works yet) - Chart appears automatically - 1,000 point rolling window per chart (old data expires, no retention config) - Max 10 charts That's basically the whole product. I built it in about a day using…

    Nov 2025 · spikelog.com

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