Kamon is a monitoring toolkit for applications running on the JVM. It gives you Metrics, Tracing and Context Propagation APIs without locking you to any specific vendor. All Kamon APIs are completely decoupled from the services that can receive the data, be it StatsD, Prometheus, Kamino, Datadog, Zipkin, Jaeger or any other supported reporter, with Kamon you instrument your application once and report anywhere you want.
From a bird’s eye view, Kamon can be decomposed in three main components: the core APIs for metrics, tracing and context propagation; the automatic instrumentation modules and the reporting modules. Your services’ code will only ever interact with Kamon’s APIs and abstract you away from how and where the collected data will end up going to.
Dear community, yesterday Diego and Ivan had a call to discuss a bit of what we think the future of Kamon should look like and we wanted to summarize the ideas and share with the community.
Today we are announcing Kamon 1.1.0 with a couple bugfixes and a small but important improvement on context propagation, plus several minor updates on other modules that sort of went under the table for Akka, Akka Remote, Akka HTTP, Play Framework, Http4s and our sbt-aspectj-runner plugin.
Dear people from the community, we are extremely pleased to announce that after months of efforts, Kamon 1.0 is finally out!. If you are already running Kamon 0.6.x or you are part of the adventurers who are already using 1.0.0-RCs in production, then it’s time to upgrade!
Dear community, we just published Kamon 0.6.3 which has a few minor bug fixes.
Steffen Gebert of Emnify talks about monitoring Akka with Kamon 1.0.
Hugh Simpson talks about Kamon and Jaeger from context propagation to tracing.
Kamon's Ivan Topolnjak is talking about Distributed Tracing at the combined meetup of Akka Meetup Würzburg & DevOps Meetup Würzburg.
This talk was recorded at Scala Swarm Conference 2017 in Porto, Portugal. Subscribe to our YouTube channel and follow us on Twitter https://twitter.com/ScalaSwarmConf and https://scala-swarm.org website for more information.
This talk was recorded at BeeScala 2016 in Ljubljana, Slovenia. Follow along on Twitter @BeeScalaConf and on the website for more information http://bee-scala.org.