HackerTrans
TopNewTrendsCommentsPastAskShowJobs

mr-karan

no profile record

Submissions

Show HN: Logchef – Open-source schema-agnostic log viewer for ClickHouse

logchef.app
5 points·by mr-karan·قبل 7 أشهر·3 comments

AI and Home-Cooked Software

mrkaran.dev
2 points·by mr-karan·قبل 9 أشهر·1 comments

Show HN: Logchef – Schema-agnostic log viewer for ClickHouse

github.com
41 points·by mr-karan·السنة الماضية·3 comments

comments

mr-karan
·قبل 8 أيام·discuss
[flagged]
mr-karan
·قبل 5 أشهر·discuss
Agreed on SQL being the best exploratory interface for agents. I've been building Logchef[1], an open-source log viewer for ClickHouse, and found the same thing — when you give an LLM the table schema, it writes surprisingly good ClickHouse SQL. I support both a simpler DSL (LogchefQL, compiles to type-aware SQL on the backend) and raw SQL, and honestly raw SQL wins for the agent use case — more flexible, more training data in the corpus.

I took this a few steps further beyond the web UI's AI assistant. There's an MCP server[2] so any AI assistant (Claude Desktop, Cursor, etc.) can discover your log sources, introspect schemas, and query directly. And a Rust CLI[3] with syntax highlighting and `--output jsonl` for piping — which means you can write a skill[4] that teaches the agent to triage incidents by running `logchef query` and `logchef sql` in a structured investigation workflow (count → group → sample → pivot on trace_id).

The interesting bit is this ends up very similar to what OP describes — an agent that iteratively queries logs to narrow down root cause — except it's composable pieces you self-host rather than an integrated product.

[1] https://github.com/mr-karan/logchef

[2] https://github.com/mr-karan/logchef-mcp

[3] https://logchef.app/integration/cli/

[4] https://github.com/mr-karan/logchef/tree/main/.agents/skills...
mr-karan
·قبل 6 أشهر·discuss
https://mrkaran.dev

Personal blog I update every now and then. Mostly infrastructure, networking, and observability stuff.
mr-karan
·قبل 6 أشهر·discuss
Just want to say thanks for creating Vector. We use it heavily at Zerodha and wrote about our setup here: https://zerodha.tech/blog/logging-at-zerodha/

It replaced both Filebeat and Logstash for us with a single binary that actually has sane resource usage (no more JVM nightmares). VRL turned out to be way more powerful than we could imagine - we do all our log parsing, metadata enrichment, and routing to different ClickHouse tables in one place. The agent/aggregator topology with disk buffering is pretty dope.

Genuinely one of my favorite pieces of infra software. Good luck with Tero.
mr-karan
·قبل 6 أشهر·discuss
I've landed on a similar philosophy but with a slightly different approach to orchestration. Instead of managing everything interactively, I built a lightweight bash-based deployment system that uses rsync + docker compose across multiple machines.

The structure is dead simple: `machines/<hostname>/stacks/<service>/` with a `config.sh` per machine defining SSH settings and optional pre/post deploy hooks. One command syncs files and runs `docker compose up -d`.

I could see Claude Code being useful for debugging compose files or generating new stack configs, but having the deployment itself be a single `./deploy.sh homeserver media` keeps the feedback loop tight and auditable.
mr-karan
·قبل 7 أشهر·discuss
You could perhaps checkout https://garagehq.deuxfleurs.fr/
mr-karan
·قبل 9 أشهر·discuss
I also quite like Localsend to quickly share files on the same network. Used to send photos/files to myself on Whatsapp/Telegram before but after discovering Localsend, stopped!

https://localsend.org/
mr-karan
·قبل 10 أشهر·discuss
I've been working on LogChef (https://logchef.app) - a specialized log analytics UI for ClickHouse that focuses on powerful querying and exploration without the complexity of full observability platforms.

The core idea is to leverage ClickHouse's incredible columnar performance for log analytics while providing a schema-agnostic interface that works with any log table structure. It supports both simple search syntax for quick queries and full ClickHouse SQL for complex analytics. Also it has proper RBAC: Team-based access controls for multi-tenant environments.

Off late I have also added some AI features:

  - AI-powered SQL generation - write queries in natural language

  - MCP (Model Context Protocol) server integration for AI assistants to query your logs
It's open source (AGPLv3) and deliberately doesn't handle log collection - instead it integrates with existing tools like Vector, Fluentd, or OpenTelemetry Collector. The roadmap includes REST APIs, client libraries, visualizations, and alerting.

Built with Go + Vue.js + TypeScript. Currently handles millions of log entries daily in production environments at my org. The deployment is just a single binary deployment with a SQLite DB.

Would love feedback from the community! GitHub: https://github.com/mr-karan/logchef
mr-karan
·قبل 10 أشهر·discuss
It's great to see Typst getting more visibility. We migrated a real-world workload to it a couple of years back: generating and e-mailing 1.5M+ PDFs daily at my org, Zerodha.

Our previous pipeline was LaTeX-based (first pdflatex, then lualatex), but we were constantly fighting cryptic memory errors on large documents and huge Docker image sizes that slowed down boot times of our ephemeral workers.

Switching to Typst was a massive win for us. The single static binary resulted in tiny images and faster boot times. More importantly, the performance gains were huge. Overall compile times were ~3–4× faster than LaTeX. On really large documents (2000+ pages, mostly tables), Typst compiles in ~1 minute vs. ~18 minutes with lualatex.

Beyond performance, the better developer experience and good error messages was a nice bonus too.

We wrote a detailed post about the entire architecture - from the job orchestration with Nomad to the S3 optimizations and the Typst migration in particular. If you're curious, you can read it here: https://zerodha.tech/blog/1-5-million-pdfs-in-25-minutes
mr-karan
·السنة الماضية·discuss
So, Logchef has a concept of "Source" which represents a ClickHouse table. You give the DSN (essentially host/port/user/password for now) and connect. In prod scenarios, usually you only `GRANT SELECT ON db_name.table_name TO user_name;`

Once you add the source, you can "connect" the source to a team. Only the members of the team will be allowed to query this source. So you can have multiple teams and add users accordingly. A source can be added to multiple teams as well.

Hope that answers your question!
mr-karan
·قبل 5 سنوات·discuss
AS6453 is having a mega outage according to https://www.thousandeyes.com/outages/. Lot of services for users in India were inaccessible for ~1h or so.