ELK Stack: Use in Performance Testing and More
summary
Shows how to stream JMeter CSV results live into the ELK stack by wiring Filebeat and Logstash into Elasticsearch and Kibana, including the Logstash CSV filter used to convert string columns to numeric metrics and the JMeter setting to flush results line-by-line. Presents an alternative that uses JMeter’s backend listener to write directly to Elasticsearch (reducing disk usage and adding custom fields and trace modes), and discusses deployment considerations like ES/Kibana bottlenecks, scaling with multiple Beats per load generator, and provides ready-to-use configs and dashboards.
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chapters (11)
- 0:00ELK Stack intro
- 3:39ELK Stack components
- 7:41Filebeat for metrics
- 10:07Logstash processing
- 12:58Backend listener alt
- 17:14Kibana Discovery
- 21:10Metrics charts
- 25:20Kibana dashboards
- 26:50ELK advanced uses
- 29:32ELK vs old approach
- 31:42Q&A
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