Hey HN, I'm Karan. I built Logchef because we moved our log workloads to ClickHouse at Zerodha and found the ecosystem lacking for actual log exploration.

Tools like Metabase and Grafana are great for dashboards, but log exploration is a different workflow.

The Grafana ClickHouse plugin requires manual column configuration for logs, has no field sidebar, and its ad-hoc filters are slow on large tables. Grafana's RBAC is Enterprise-only, and even then it's datasource-level and not at table-level. If someone has access to the ClickHouse datasource, they can query any table. In Logchef, you create Sources (pointing to specific tables) and assign them to Teams. Team A only sees their logs, Team B only theirs. Fine-grained access control without any Enterprise license :)

Metabase has no concept of log-specific features at all. We kept falling back to raw SQL in clickhouse-client, which works but isn't something you want to hand to your whole team.

So I built Logchef — a log viewer designed specifically for ClickHouse. Schema-agnostic, so you can start filtering immediately without migrations.

What it does:

- Point at any ClickHouse table – no schema migrations/no OTEL requirement - LogchefQL query language (simpler than SQL for filtering) - Field sidebar like Kibana – click values to add filters - SQL-based alerting that routes to Alertmanager - AI assistant that turns natural language queries like "find slow POST requests" into working SQL - MCP server for querying logs from your favourite LLM assistant tool - Single Go binary (~15MB), embeds the frontend

We've been running this in production for 8 months and I'm excited to ship v1.0 today.

Demo: https://demo.logchef.app

GitHub: https://github.com/mr-karan/logchef

Docs: https://logchef.app

Happy to answer questions about ClickHouse for logs, the architecture, or anything else.