I Analyzed 6 Months of Zabbix Alerts Across My MSP Clients. Here's What the Data Shows.
Zabbix alert data analysis — patterns from MSP monitoring stack
Top alert categories. Here's what that actually involved.
The Setup
Time-of-day patterns
What I Built
Top alert categories
Top alert categories. This is where most implementations go wrong — not in the concept, but in the specifics that documentation tends to gloss over. The version that's actually running in production looks different from what the README describes.
Time-of-day patterns
Time-of-day patterns. This is where most implementations go wrong — not in the concept, but in the specifics that documentation tends to gloss over. The version that's actually running in production looks different from what the README describes.
Which alerts are
Which alerts are noise. This is where most implementations go wrong — not in the concept, but in the specifics that documentation tends to gloss over. The version that's actually running in production looks different from what the README describes.
What Broke First
Automation opportunities. This is the part that took the most time to figure out — not the implementation itself, but the failure mode you only encounter at the wrong moment. The fix is in the tooling, not the concept.
What's Running in Production
The stack: zabbix, monitoring, msp, data. Monitoring via Zabbix with a custom alert template. The rule I apply to everything in production: if it can't self-report a failure, it doesn't go in.
Key Takeaways
- Top — top alert categories
- Time-of-day — time-of-day patterns
- Which — which alerts are noise
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Live Life Automated covers the broader philosophy behind how I think about automation and building systems that don't require constant babysitting. Available at mfitz.net.
