Using Elastic ML to Observe Your Kuma API Observability Metrics

Using Elastic ML to Observe Your Kuma API Observability Metrics

Dec 10, 2021

Observability is catching on these days as the de-facto way to provide visibility into essential aspects of systems. It would be unwise for you not to leverage it with Kuma service mesh — the place that allows your services to communicate with the rest of the world. However, many observability solutions restrict themselves to the works: simple metric collection that provides them with dashboards. Expecting users to simply sit on their chairs and look at those metrics all day long is an invitation to failure, as we know that one can only do so much when they get tired and bored.

This talk will change the status quo and show how you can work smart by combining the flexibility of Kuma with the power of the Elastic Stack to ingest, store and analyze massive amounts of data. Join to learn how to collect metrics from Kuma via Prometheus, bring these metrics into @Elastic search using Metricbeat and create machine learning jobs to look for anomalies that can alert you when something interesting happens.

Watch the full recording from Kong Summit 2021 here:

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0:00 Intro

2:30 Modern Observability

3:20 Enabling Metrics, Logs and Tracing on Kuma

4:28 Loading Metrics from Kuma to Elastic

6:46 Using Elastic Metricbeat

7:58 Using the OpenTelemetry Collector

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#011y #ServiceMesh #Elastic #Metricbeat #KumaMesh #KongSummit