HouseWatch
https://github.com/posthog/housewatch- Category
- Developer Tools
- Rank
- No. 763Tools index
Previous survey · No. 758 ·
- Pricing
- Open Source
- Type
- TOOL
- Builder
- posthog
- GitHub
- 631 stars
- Latest release
- housewatch-0.1.9
- Date
About
Open-source tool from PostHog for monitoring and managing ClickHouse clusters, with a Django + React UI.
What it does
HouseWatch turns ClickHouse system metadata into practical troubleshooting views. Operators can inspect load, query cost, logs, errors, schema size, disk consumption and running work. They can also execute queries, stop active queries, benchmark performance and launch background operations with failure rollbacks.
Why it's ranked here
The appeal is operational focus: it combines diagnosis and action around ClickHouse instead of stopping at charts. Query analysis, storage inspection, logs and cluster operations share one interface. The verdict remains cautious because the project calls itself beta, lacks built-in security and lists important reliability work as unfinished.
What's good
Its strongest feature is the path from symptom to action. You can identify expensive queries, inspect their cluster load, examine explanations and benchmarks, then stop running work when needed. Disk reporting reaches nodes, tables, columns and parts. Read-only credentials preserve the analysis features when operational controls are too risky.
Tradeoffs
The interface is not secured, so exposing it publicly would be unsafe. Read-only credentials disable operations and the query editor. Multiple-instance support, configurable time ranges, log pagination and broader operation controls remain planned. The project also warns about production use, and background operations are not yet resilient to Celery failure.
How to use it well
Use it for ClickHouse incident investigation and routine performance work inside a trusted network. Start with read-only access for load, query, log and storage analysis. Grant write-capable credentials only where query execution and management actions justify the risk. It does not replace authentication, internet-facing access controls or a hardened multi-instance operations platform.
Technical notes+
housewatch/urls.py exposes Django REST Framework routes for instances, clusters, backups, scheduled backups, analysis, async migrations and saved queries, plus admin and health endpoints. housewatch/celery.py configures Celery tasks for scheduled base and incremental backups and async migrations, checking backup schedules every 60 seconds. frontend/vite.config.ts builds the React frontend and proxies API, admin and logout traffic to Django during development. requirements.txt pins Django, Celery, Redis, PostgreSQL, ClickHouse drivers, Gunicorn and OpenAI dependencies. housewatch/gunicorn.conf.py binds two workers on port 8100 and filters health checks from access logs. frontend/src/App.tsx mounts the routed application layout.
Observed
- Install surface
- Deployment uses Docker Compose with environment variables for the ClickHouse connection and UI address.
- User interface
- Browser interface for query analysis, logs, errors, disk usage, schema statistics, benchmarking and operations.
- API interface
- Django REST Framework routes cover instances, clusters, backups, analysis, async migrations and saved queries.
- Backend stack
- Python backend using Django, Celery, Redis, Gunicorn and ClickHouse drivers.
- Frontend stack
- React frontend built with Vite and routed in the browser.
- Background work
- Celery handles scheduled full and incremental backups plus asynchronous migrations.
- Access model
- Read-only ClickHouse credentials retain analysis features but disable management operations and query editing.
Read from README.md, pyproject.toml, requirements.txt, manage.py, housewatch/apps.py, housewatch/asgi.py, housewatch/urls.py, housewatch/wsgi.py, housewatch/admin.py, housewatch/views.py, housewatch/celery.py, frontend/vite.config.ts, housewatch/gunicorn.conf.py, frontend/src/App.tsx.
What it can do
Monitor ClickHouse cluster health and performance
ClickHouse cluster connection details → Real-time health metrics and performance data
View ClickHouse cluster configuration
ClickHouse cluster connection → Cluster configuration details and settings
Execute SQL queries against ClickHouse
SQL query statements → Query results and execution statistics
Monitor running queries and processes
ClickHouse cluster connection → List of active queries with execution details
View database schemas and table structures
ClickHouse database connection → Database schema information and table definitions
Analyze query performance and optimization
SQL queries and execution logs → Performance metrics and optimization suggestions
Manage ClickHouse users and permissions
User credentials and permission settings → Updated user access controls
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Editorially curated, with community endorsements as a secondary signal. Corrections welcome.