To detect stuck consumers or unhealthy brokers, a RabbitMQ team needs measurements about queues, connections and nodes. The historical kbudde RabbitMQ Exporter queried the broker’s management interface and exposed those observations to Prometheus. That exporter is now end of life and limited to RabbitMQ 3. RabbitMQ’s own Prometheus plugin provides a different collection path; moving to it requires checking metric names and alert behavior so a working scrape does not hide a lost monitoring signal.
Current guidance
The historical chart’s metadata points to kbudde/rabbitmq_exporter. That upstream now carries an explicit end-of-life notice and says it only works with RabbitMQ 3, directing RabbitMQ 4 users to the official exporter. This retirement is scoped to that external exporter, not to RabbitMQ or Prometheus monitoring generally.
RabbitMQ’s own documentation describes the rabbitmq_prometheus plugin and maintained dashboard conventions. Moving to that endpoint changes how metrics are collected: the old exporter queried the management interface, while the built-in plugin exposes broker metrics directly. Metric names, labels, aggregation and per-entity detail must be compared rather than assuming existing alerts remain equivalent.
Inventory which queue, connection and node alerts the old exporter supplied, enable a controlled target endpoint and map those queries to the new metrics. Test both normal traffic and a deliberately stopped consumer; review cardinality before enabling detailed queue metrics broadly. Keep broker version migration separate from monitoring migration where possible. No RabbitMQ upgrade or dashboard-equivalence test was executed for this advisory.
Historical upstream link check · 2026-10-09
The recorded upstream address responded successfully (HTTP 200) on 2026-10-09. GitHub confirms that helm/charts is archived: this is a historical chart distribution, not evidence that the application itself is retired. Link availability does not certify the historical installation instructions or current security support.
Website availability is separate from project, chart and image support. Use the current guidance and primary sources on this page to assess the distribution.
Historical Kubedex content
Preserved for context. Commands, versions, prices and results below reflect the original research.
rabbitmq_exporter is a Prometheus exporter for rabbitmq metrics. This chart bootstraps a rabbitmq_exporter deployment on a Kubernetes cluster using the Helm package manager.
This document is intended to guide you on which RabbitMQ and system metrics are most important to monitor. Monitoring your RabbitMQ installation is an effective means to intercept issues before they affect the rest of your environment and, eventually, your users.
Infrastructure and Kernel Metrics
First step towards a useful monitoring system starts with infrastructure and kernel metrics. There are quite a few of them but some are more important than others. The following metrics should be monitored on all nodes in a RabbitMQ cluster and, if possible, all nodes that host applications:
- CPU (idle, user, system, iowait)
- Memory (free, cached, buffered)
- Disk I/O (reads & writes per unit time, I/O wait percentages)
- Free Disk Space
- File descriptors used by beam.smp vs. max system limit
- Network throughput (bytes received, bytes sent) vs. maximum network link throughput
- VM statistics (dirty page flushes, writeback volume)
- System load average (/proc/loadavg)
There is no shortage of existing tools (such as Graphite or Datadog) that collect infrastructure and kernel metrics, store and visualize them over periods of time.
RabbitMQ Metrics
The RabbitMQ management plugin provides a starting point for monitoring RabbitMQ metrics. One limitation, however, is that only up to one day’s worth of metrics are stored. Storing historical metrics can be an important tool to determine the root cause of issues affecting your users or to plan for future capacity.
RabbitMQ metrics are made available through the HTTP API via the api/queues/vhost/qname endpoint. It is recommended to collect metrics at 60-second intervals because more frequent collection may place too much load on the RabbitMQ server and negatively affect performance.
RabbitMQ Features
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Asynchronous Messaging
Supports multiple messaging protocols, message queuing, delivery acknowledgment, flexible routing to queues, multiple exchange type.
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Developer Experience
Deploy with BOSH, Chef, Docker, and Puppet. Develop cross-language messaging with favorite programming languages such as Java, .NET, PHP, Python, JavaScript, Ruby, Go, and many others.
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Distributed Deployment
Deploy as clusters for high availability and throughput; federate across multiple availability zones and regions.
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Enterprise & Cloud Ready
Pluggable authentication, authorization, supports TLS and LDAP. Lightweight and easy to deploy in public and private clouds.
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Tools & Plugins
A diverse array of tools and plugins supporting continuous integration, operational metrics, and integration to other enterprise systems. Flexible plug-in approach for extending RabbitMQ functionality.
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Management & Monitoring
HTTP-API, command line tool, and UI for managing and monitoring RabbitMQ.
RabbitMQ Commercial Services
Commercial Distribution
Pivotal Software produces a commercial distribution called Pivotal RabbitMQ, as well as a version that deploys in Pivotal Cloud Foundry. These distributions include all of the features of the open source version, with RabbitMQ for Pivotal Cloud Foundry providing some additional management features. Support agreements are part of the commercial licensing.
Support + Hosting
Pivotal Software provides support for open source RabbitMQ. The following companies provide technical support and/or cloud hosting of open source RabbitMQ: CloudAMQP, Erlang Solutions, Google Cloud Platform. RabbitMQ can also be deployed in AWS and Microsoft Azure.
Training
The following companies provide free, virtual, or instructor-led courses for RabbitMQ: Pivotal Software, Erlang Solutions, NetCom Learning, Skills Matter, LearnQuest and Open Source Architect.
Sources & further reading
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