Application performance management w/ open...
summary
A methodology that turns per-transaction JSON (response time, error codes, URL path, DB query, rows, size) into event analytics by shipping Packetbeat -> optionally Redis/Logstash -> Elasticsearch and visualizing in Kibana; uses percentile aggregations and latency histograms to surface 99th-percentile offenders and top-N slow RPC methods, supports drilling from aggregated views to raw transactions, proves viable at production scale (installations exceeding one million events/sec), open source under the Apache license and integrated into Elastic.
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chapters (27)
- 0:00Intro
- 0:42Scaling
- 1:27Conway's law
- 1:43First org chart
- 2:23Microservices
- 3:50Evolution
- 4:47Operational monitoring
- 5:46Requirements
- 6:39Start from the communication
- 7:52Packetbeat shipper
- 9:01The traditional way
- 10:01Packetbeat . ELK
- 10:44Why ELK?
- 12:55Percentile values over time
- 13:57Percentiles aggregation
- 15:16Date histogram nested with percentiles
- 15:46Kibana config
- 16:08Latency histogram
- 16:41Histogram by response time
- 17:37Add a date histogram
- 19:10Slowest RPC methods
- 20:53Order by 99th percentile
- 21:47Tips
- 23:05Future plans
- 23:53Joining Elastic
- 24:59The Beats
- 25:40Stay in touch
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