Reveal deep insights into what your Reactive system is doing
Reactive systems are the next major evolution of the Internet. They allow for applications to be responsive, scalable and resilient by building on a fully message-driven foundation; but though the Reactive approach enables us to build highly scalable and resilient microservices-based applications, it also introduces new challenges in how to monitor them.
The issue is that almost every current monitoring tool relies on a stack frame-based approach where using the stack trace can provide good answers to what caused exceptional states. In asynchronous, message-driven distributed applications, this approach no longer provides any useful information about issues because the path to where you are is no longer available and you don’t know where your code will execute. We therefore need to invent new approaches for how to monitor these types of applications and get information about bottlenecks, hotspots and performance degradation.
During this session by Lightbend experts Henrik Engström and Duncan Devore , we take a look at the traditional approach to monitoring synchronous applications, what it takes to successfully monitor asynchronous, microservices-based applications, and show Lightbend Reactive Platform's expanding capabilities for monitoring actors, flows, circuit breakers and more with popular UI dashboards and backends.
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What's coming in Monitoring 2.0
Lightbend Monitoring 2.0 features changes to make it easier to get started.
- Now agent based: While the previous version was based on pre-instrumented JAR files, the 2.0 release is now Java agent based and enables instrumentation of more libraries.
- Better Maven and Gradle support: now integrate more simply with Maven, Gradle and sbt, letting teams get started faster.
- Expanding tracking: Monitoring of Dispatchers, Thread Pools, and “Flows” a.k.a. Futures and Streams add better visualization support for open source Akka 2.3.x and 2.4.x and Lagom circuit breaker
- Support for more UI dashboards and backends: StatsD, Coda Hale Metrics, Dropwizard Metrics, SLF4J, Takipi, Elasticsearch, Grafana and Kibana