Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a Shoestring Budget
summary
A lightweight monitoring pipeline captures every inbound and outbound request from about 25 microservices, publishes compact events over an MQTT firehose, stores time-series metrics in InfluxDB + Grafana, and sends alerts to Slack/PagerDuty. It collects response codes, mean/90%/95% latencies, memory/CPU and crash events, and runs synthetic page-load checks. Deployed on a shoestring with Node.js middleware, it uncovers systemic outages and a dev-only CPU leak before production, and supports root-cause drilling via tabular and category dashboards.
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chapters (17)
- 0:00Intro
- 2:05Bluemix UI Architecture
- 2:44Importance of Monitoring
- 5:10What to Monitor?
- 6:29Monitoring Architecture
- 9:25Monitoring Components
- 9:39Grafana Dashboards
- 11:42Identifying a Problem in Grafana
- 13:09Root Cause Analysis
- 14:52Details View
- 16:31Wall of Shame
- 17:38Memory, CPU Usage, Crashes
- 19:52Default Capabilities and MQTT
- 20:24App Metrics - Default Capabilities
- 20:56Data Storage
- 21:22Collecting Synthetic Data
- 23:06The End
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