Towards a full stack python monitoring+analysis framework
summary
Claim: build a full‑stack Python monitoring + analytics framework ready for SDN/NFV and IoT, not just dashboards. Uses mqtt for internal transport, Tornado for ingestion, Arctic/HDF5 or gnocchi for storage, pandas/scikit‑learn for analytics, Luigi + APScheduler for pipelines, Bokeh/Plotly for interactive or standalone HTML dashboards and mqttwarn/Telegram bots for alarms. Implements online/offline analytics (seasonal models, clustering correlated KPIs) to cut redundant alerts and surface meaningful anomalies, and demonstrates working deployments with telco customers and offline HTML demos that satisfied nontechnical stakeholders.
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chapters (15)
- 0:00Python monitoring intro
- 1:54Traditional tools limits
- 3:19Why Python for monitoring
- 5:32Analytics in monitoring pipelines
- 8:00Data processing workflows
- 11:13Seasonal KPI analysis
- 14:24Correlated alarms handling
- 15:28Monitoring data storage
- 20:18Data transfer protocols
- 23:10Cloud monitoring overview
- 26:26MQTT for IoT
- 30:47Python dashboards
- 34:47Automated alarms
- 36:14Monitoring framework design
- 38:28Q&A
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