Your logs are talking. Start listening.
Build a real-time log analysis dashboard from your ClickHouse data. Severity heatmaps, error rate trends, and natural-language log queries—built by AI in one conversation.
Logs are the most valuable data you never look at.
Your infrastructure generates millions of log lines every hour. They contain the answers to every outage, every slow endpoint, every silent failure. But extracting those answers? That is where things fall apart. You are drowning in data and starving for insight.
Grep is not observability
You are SSHing into boxes and grepping gigabyte log files. By the time you find the needle, the haystack has doubled. There is no pattern recognition, no trend analysis, no cross-service correlation.
Alert fatigue kills response time
Your monitoring fires 200 alerts a day. Most are noise. By the time you triage the real ones, the incident is 20 minutes old and your users already noticed.
ELK and Datadog costs spiral at scale
You are paying thousands per month to index logs you rarely query. The dashboards take a week to set up, another week to tune, and break every time someone changes a log format.
Ask your logs anything. In English.
camelAI connects to your ClickHouse instance, learns your log table schemas, and builds a full-featured analysis dashboard. Query billions of log lines in natural language. The agent writes the ClickHouse SQL, formats the results, and deploys a live dashboard you can share with your team. No Grafana JSON, no Kibana config files, no vendor lock-in.
Found 47 errors across 6 unique messages. Here is the breakdown:
What you will build.
Total Events
0.0M
Errors (24h)
0
p99 Latency
0ms
Uptime
0.0%
Error Rate (24h)
Severity Heatmap
| Timestamp | Severity | Service | Message |
|---|---|---|---|
| 09:14:05.332 | ERROR | payments | OOM killed pid=4821 rss=2.1GB |
| 09:14:05.118 | INFO | gateway | Request served 200 /api/v1/users 12ms |
| 09:14:04.891 | WARN | auth | Slow query detected duration=1.8s |
| 09:14:04.445 | INFO | payments | Request served 200 /api/v1/orders 8ms |
| 09:14:03.998 | ERROR | db | Connection refused host=replica-03:9000 |
| 09:14:03.772 | DEBUG | cache | Cache hit key=user:8821 ttl=340s |
Three steps. One conversation.
Connect ClickHouse
Add your ClickHouse connection details in camelAI's integrations panel -- host, port, database, and credentials. The agent discovers your log tables and column schemas automatically. Supports ClickHouse Cloud, self-hosted, and Altinity deployments.
logs_production
ClickHouse Cloud
Describe what you need
Tell the agent exactly what you want in plain English.
Deploy and monitor
The agent builds your dashboard with React, Recharts, and Tailwind -- then deploys it to a live URL. Set up a cron job to check error rates every 5 minutes and post to Slack when they spike above your threshold.
Queries that used to take 20 minutes of SQL. Now they take one sentence.
“Show error spikes in the last 6 hours”
Result: Sparkline
“Which services have the highest error rate this week?”
Result: Ranked bar chart
“Find all timeout errors from the auth service after the last deploy”
Result: Filtered table
“Compare today's log volume to the same day last week”
Result: Overlay comparison
“What was the p99 query latency yesterday vs today?”
Result: Comparison stat
Yesterday
357ms
Today
342ms
“Show me the full stack trace for request ID abc-123-def”
Result: Trace waterfall
Built for the people who get paged at 3 AM.
You run the infrastructure. You need to see what is happening across 50 services without opening 50 tabs. Build a single pane of glass over your ClickHouse logs.
You own uptime. You need to see error patterns before they become incidents. Get a dashboard that highlights anomalies automatically and helps you cut MTTR.
You build the internal tools your team uses every day. Give them a log dashboard that actually helps -- searchable, filterable, and deployed to a URL they can bookmark.
Frequently asked questions
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Read guideStop grepping. Start seeing.
Connect ClickHouse, describe the dashboard you need, and deploy it in minutes.