HiveMQ enables real-time IoT observability from device to cloud

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Landshut, Germany – HiveMQ, a global provider in enterprise MQTT solutions, announced the availability of the HiveMQ Distributed Tracing Extension, a new feature that makes it possible to trace and debug MQTT data streams from device to cloud and back. Complete IoT observability requires insight into three pillars: metrics, traces and logs. HiveMQ has added Distributed Tracing to help organisations achieve end-to-end observability and make their IoT applications more performant and resilient.

Distributed Tracing is a way to trace events and achieve a high-level overview of a message’s journey through multiple, complex systems. With the Distributed Tracing Extension, HiveMQ is the MQTT broker to add OpenTelemetry support to provide complete transparency for every publish message that uses the HiveMQ MQTT broker. OpenTelemetry is an open standard for instrumentation that allows for interoperability across all services so organisations can achieve visibility over their entire system.

“We’re the first MQTT broker to enable true IoT observability so customers can trace MQTT data and gather diagnostic information in real-time rather than after the fact,” says Christian Götz, CEO and co-founder of HiveMQ. “IoT observability is key as it allows customers to quickly identify latency bottlenecks or reasons for failure in critical transactions and decrease the time spent resolving these issues.”

HiveMQ offers integration into a broad range of application performance monitoring (APM) tools such as Datadog, Dynatrace and Honeycomb, or open source alternatives like Grafana Tempo. APM tools are being adopted rapidly but when used alone they typically have a blind spot around the MQTT data which leads to poor observability of applications. With the Distributed Tracing Extension, HiveMQ has solved that problem to unlock more value from expensive APM investments and shorten the time required to discover and resolve issues.

“In a complex architecture, customers often don’t know where to start when they experience a problem,” adds Götz. “Say opening the car door with a mobile application is taking 5 to 10 seconds instead of 1 second. A detailed look at where the message request traveled and how long it took at each step makes it easy to identify the root cause of latency so it can be fixed.”

HiveMQ 4.9 includes the Distributed Tracing Extension and is available now. For more information visit Distributed Tracing blog post.

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