RabbitMQ Exporter

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All about the RabbitMQ exporter - so you can safely and reliably monitor metrics from the widely adopted open source message broker RabbitMQ, a lightweight, easy-to-deploy mission-critical software.

About RabbitMQ

RabbitMQ is a widely adopted open source message broker. A message broker is software that enables applications, systems, and services to communicate with each other and exchange information.

RabbitMQ is lightweight, easy to deploy on premises and in the cloud, and able to handle millions of users and transactions. It can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements. It supports multiple messaging protocols - AMQP 1.0, MQTT, STOMP.

Since it is a mission-critical piece of software that binds the applications, monitoring is a must. A RabbitMQ exporter is required to monitor and expose the RabbitMQ metrics. It queries RabbitMQ, scraps the data, and exposes the metrics to a Kubernetes service endpoint that can further be scrapped by Prometheus to ingest the time series data. For monitoring of RabbitMQ we use an external Prometheus exporter, which is maintained by the Prometheus Community. On deployment this exporter scraps sizable metrics from RabbitMQ and helps users get crucial information about the message broker which is difficult to get from RabbitMQ directly. 

For this setup, we are using bitnami rabbitmq helm charts to start the cluster. 

RabbitMQ has a built-in Prometheus plugin as well as an official Prometheus exporter - below we are explaining the setup of both.

RabbitMQ with Prometheus Exporter

How do you set up an exporter for Prometheus?

With the latest version of Prometheus (2.33 as of February 2022), there are three ways to set up a Prometheus exporter: 

Method 1 - Native

Supported by Prometheus since the beginning
To set up an exporter in native way a Prometheus config needs to be updated to add the target.
A sample configuration:

# scrape_config job   - job_name: rabbitmq-staging      scrape_interval: 45s      scrape_timeout:  30s      metrics_path: "/metrics"      static_configs:      - targets:        - <RabbitMQ endpoint>
Code language: PHP (php)
Method 2 - Service Discovery

This method is applicable for Kubernetes deployment only
With this, a default scrap config can be added to the prometheus.yaml file and an annotation can be added to the exporter service. With this, Prometheus will automatically start scrapping the data from the services with the mentioned path.

Prometheus.yaml

     - job_name: kubernetes-services         scrape_interval: 15s         scrape_timeout: 10s         kubernetes_sd_configs:         - role: service         relabel_configs:         # Example relabel to scrape only endpoints that have         # prometheus.io/scrape: "true" annotation.         - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]           action: keep           regex: true         #  prometheus.io/path: "/scrape/path" annotation.         - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]           action: replace           target_label: __metrics_path__           regex: (.+)         #  prometheus.io/port: "80" annotation.         - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]           action: replace           target_label: __address__           regex: (.+)(?::\d+);(\d+)           replacement: $1:$2
Code language: PHP (php)

Exporter service:

 annotations:     prometheus.io/path: /metrics     prometheus.io/scrape: "true"
Code language: PHP (php)
Method 3 - Prometheus Operator

Setting up a service monitor
The Prometheus operator supports an automated way of scraping data from the exporters by setting up a service monitor Kubernetes object. A sample service monitor for RabbitMQ can be found here. These are the necessary steps:

Step 1

Add/update Prometheus operator’s selectors. By default, the Prometheus operator comes with empty selectors which will select every service monitor available in the cluster for scrapping the data.

To check your Prometheus configuration:

Kubectl get prometheus -n <namespace> -o yaml
Code language: HTML, XML (xml)

A sample output will look like this.

ruleNamespaceSelector: {} ruleSelector: matchLabels: app: kube-prometheus-stack release: kps scrapeInterval: 1m scrapeTimeout: 10s securityContext: fsGroup: 2000 runAsGroup: 2000 runAsNonRoot: true runAsUser: 1000 serviceAccountName: kps-kube-prometheus-stack-prometheus serviceMonitorNamespaceSelector: {} serviceMonitorSelector: matchLabels: release: kps
Code language: CSS (css)

Here you can see that this Prometheus configuration is selecting all the service monitors with the label release = kps

So with this, if you are modifying the default Prometheus operator configuration for service monitor scrapping, make sure you use the right labels in your service monitor as well.

Step 2

Add a service monitor and make sure it has a matching label and namespace for the Prometheus service monitor selectors (serviceMonitorNamespaceSelector & serviceMonitorSelector).

Sample configuration:

apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: annotations: meta.helm.sh/release-name: rabbitmq-exporter meta.helm.sh/release-namespace: monitor creationTimestamp: "2022-04-04T10:22:52Z" generation: 1 labels: app: prometheus-rabbitmq-exporter app.kubernetes.io/managed-by: Helm chart: prometheus-rabbitmq-exporter-1.1.0 heritage: Helm release: kps name: rabbitmq-exporter-prometheus-rabbitmq-exporter namespace: monitor resourceVersion: "86677099" uid: 55943299-a8ed-4553-9cdb-cc784176aea8 spec: endpoints: - interval: 15s port: rabbitmq-exporter selector: matchLabels: app: prometheus-rabbitmq-exporter release: rabbitmq-exporter
Code language: JavaScript (javascript)

Here you can see we have a matching label on the service monitor release = kps that we are specifying in the Prometheus operator scrapping configuration.

Metrics

The following ones are handpicked metrics that will give insights for RabbitMQ operations.

  1. Server is up
    As the name suggests, this metric will expose the state of the RabbitMQ process and whether it is up or down.
    ➡ The key of the exporter metric is “rabbitmq_up”.
    ➡ The value of the metric is a boolean - 1 or 0 which symbolizes if RabbitMQ is up or down respectively.  
  1. Overflowing queue
    Queues are a fundamental component of any message broker. All messages that are getting pushed or read by RabbitMQ must belong to one of the queues.
    Users would never want to choke the queue. If the queue is filled up to the maximum capacity, it can no longer accept new messages.
    To get the total number of the ready messages in the queue.
    ➡ The metric Key  is “rabbitmq_queue_messages_ready_total”
    ➡ The value will be number of the messages, ex: “rabbitmq_queue_messages_ready_total  157”
  1.  Too many connections
    RabbitMQ acts as a broker between a publisher and a subscriber. Every client to the queue opens a connection with RabbitMQ. Each new one requires resources from the underlying machine and puts burden on the hardware as well as software. Therefore, the number of connections to RabbitMQ should be limited to avoid any discrepancy in the service.
    ➡ metric “ rabbitmq_connectionsTotal” gives the total active connections on RabbitMQ
    ➡ The number should be calculated based on the resources allocated to the RabbitMQ service
  1. Active queue
    As the name suggests the metrics will give insight into how many active queues are present in RabbitMQ that are handling the data. 
    A message can be enqueued (added) and dequeued (removed). It is important to monitor the active queue.
    ➡ meric “rabbitmq_queuesTotal” exposes the number of active queues
  1. Total number of consumers
    As the name suggests, this metric will provide insight into how many consumers a queue has. Consumers in RabbitMQ are those targets which consume the message from the queue.
    ➡ metric  “rabbitmq_consumersTotal” exposes the total number of active consumers on a queue

RabbitMQ with built-in Prometheus plugin
(no exporter needed)

Additionally, there is a solution to monitor RabbitMQ by using the built-in Prometheus plugin from RabbitMQ. Our recommendation is to use both options.

How to install plugin, choose official metrics, and set alerts

RabbitMQ version V3.8.0 and above supports the way to enable a built-in Prometheus metrics plugin that will expose all RabbitMQ metrics in Prometheus format to an endpoint that Prometheus can scrap by enabling the auto-discovery or by creating a service monitor. To enable the RabbitMQ plugin via Helm charts, set the metrics enabled to “true”.

helm install <release name> bitnami/rabbitmq --set metrics.enabled=true
Code language: HTML, XML (xml)

More details about the plugin can be found here.

In the case of standard Prometheus installation, once the plugin is enabled in RabbitMQ, annotations need to be added to RabbitMQ (if you are using the RabbitMQ chart it will be added automatically). Here are the annotations:

annotations: prometheus.io/path: /metrics prometheus.io/scrape: "true"
Code language: PHP (php)

These annotations should be added on the pod level. Now Prometheus will automatically start scraping the data if the pod discovery is enabled.
Prometheus configuration for pod discovery:

- job_name: "kubernetes-pods" kubernetes_sd_configs: - role: pod
Code language: JavaScript (javascript)

In the case of the Prometheus Operator, once the plugin is enabled in RabbitMQ, the service monitor needs to be enables. For this, run the following command:

helm upgrade ---install <release name> bitnami/rabbitmq --set metrics.enabled=true --set metrics.serviceMonitor.enabled=true
Code language: JavaScript (javascript)

Once the service monitor is created, the Prometheus operator will start scrapping the metrics automatically in the default configuration.

Some important metrics

  1. Server is up
    As the name suggests, this metric will expose the state of the RabbitMQ process and whether it is up or down.
    ➡ The key of the exporter metric is “rabbitmq_up”.
    ➡ The value of the metric is a boolean - 1 or 0 which symbolizes if RabbitMQ is up or down respectively.  
  1. Cluster down
    Tis metric exposes the state of the RabbitMQ cluster.
    ➡ The key of the exporter metric is “rabbitmq_running
    ➡ The value of the metric is a number that symbolizes the number of nodes in the RabbitMQ cluster.
  1.  Out of memory
    The memory status of RabbitMQ is exposed through this metric.
    ➡ The key of the exporter metric is “rabbitmq_node_mem_used” and “rabbitmq_node_mem_limit
    ➡ The value of the metric is a number that symbolizes the number of available memory
  1. Too many connections
    RabbitMQ acts as a broker between a publisher and a subscriber. Every client to the queue opens a connection with RabbitMQ. Each new one requires resources from the underlying machine and puts burden on the hardware as well as software. Therefore, the number of connections to RabbitMQ should be limited to avoid any discrepancy in the service.
    ➡  metric “ rabbitmq_connectionsTotal” gives the total active connections on RabbitMQ
    ➡ The number should be calculated based on the resources allocated to the RabbitMQ service
  1. Cluster partitions down
    This metric exposes the RabbitMQ partition status.
    ➡ The key of the exporter metric is “rabbitmq_partitions
    ➡ The value of the metric is a number that symbolizes a number of the network partition created

Some critical alerts

  1. Alert - Rabbit MQ Down
- alert: RabbitmqDown expr: rabbitmq_up{service="{{ template "rabbitmq.fullname" . }}"} == 0 for: 5m labels: severity: error annotations: summary: Rabbitmq down (instance {{ "{{ $labels.instance }}" }}) description: RabbitMQ node down
Code language: JavaScript (javascript)
  1. Alert - Rabbit MQ Cluster Down
- alert: ClusterDown expr: | sum(rabbitmq_running{service="{{ template "rabbitmq.fullname" . }}"}) < {{ .Values.replicaCount }} for: 5m labels: severity: error annotations: summary: Cluster down (instance {{ "{{ $labels.instance }}" }}) description: | Less than {{ .Values.replicaCount }} nodes running in RabbitMQ cluster VALUE = {{ "{{ $value }}" }}
Code language: JavaScript (javascript)
  1.  Alert - RabbitMQ Partition
- alert: ClusterPartition expr: rabbitmq_partitions{service="{{ template "rabbitmq.fullname" . }}"} > 0 for: 5m labels: severity: error annotations: summary: Cluster partition (instance {{ "{{ $labels.instance }}" }}) description: | Cluster partition VALUE = {{ "{{ $value }}" }}
Code language: JavaScript (javascript)
  1.   Alert - RabbitMQ is out of memory
- alert: OutOfMemory expr: | rabbitmq_node_mem_used{service="{{ template "rabbitmq.fullname" . }}"} / rabbitmq_node_mem_limit{service="{{ template "rabbitmq.fullname" . }}"} * 100 > 90 for: 5m labels: severity: warning annotations: summary: Out of memory (instance {{ "{{ $labels.instance }}" }}) description: | Memory available for RabbmitMQ is low (< 10%)\n VALUE = {{ "{{ $value }}" }} LABELS: {{ "{{ $labels }}" }}
Code language: JavaScript (javascript)
  1.  Alert - Too many connections
- alert: TooManyConnections expr: rabbitmq_connectionsTotal{service="{{ template "rabbitmq.fullname" . }}"} > 1000 for: 5m labels: severity: warning annotations: summary: Too many connections (instance {{ "{{ $labels.instance }}" }}) description: | RabbitMQ instance has too many connections (> 1000) VALUE = {{ "{{ $value }}" }}\n LABELS: {{ "{{ $labels }}" }}
Code language: JavaScript (javascript)

Alerts can be enabled, disabled, altered, or added using the helm chart here.

Dashboard

This is the dashboard that has been used.

This concludes our discussion of the RabbitMQ exporter! If you have any questions, you can reach our team via support@nexclipper.io and stay tuned for further exporter reviews and tips coming soon.

  • rabbitmq/rabbitmq-prometheus
  • rabbitmq_prometheus plugin
  • rabbitmq/rabbitmq-prometheus

    https://github.com/rabbitmq/rabbitmq-prometheus

    This was migrated to https://github.com/rabbitmq/rabbitmq-server

    All issues have been transferred, archiving.

    Build
    Grafana Dashboards

    Prometheus Exporter of Core RabbitMQ Metrics

    Getting Started

    This is a Prometheus exporter of core RabbitMQ metrics, developed by the RabbitMQ core team. It is largely a "clean room" design that reuses some prior work from Prometheus exporters done by the community.

    Project Maturity

    This plugin is new as of RabbitMQ 3.8.0.

    Documentation

    See Monitoring RabbitMQ with Prometheus and Grafana.

    Installation

    This plugin is included into RabbitMQ 3.8.x releases. Like all plugins, it has to be enabled before it can be used:

    To enable it with rabbitmq-plugins:

    rabbitmq-plugins enable rabbitmq_prometheus

    Usage

    See the documentation guide.

    Default port used by the plugin is 15692 and the endpoint path is at /metrics. To try it with curl:

    curl -v -H "Accept:text/plain" "http://localhost:15692/metrics"

    In most environments there would be no configuration necessary.

    See the entire list of metrics exposed via the default port.

    Configuration

    This exporter supports the following options via a set of prometheus.* configuration keys:

    Sample configuration snippet:

    # these values are defaults prometheus.return_per_object_metrics = false prometheus.path = /metrics prometheus.tcp.port =  15692

    When metrics are returned per object, nodes with 80k queues have been measured to take 58 seconds to return 1.9 million metrics in a 98MB response payload. In order to not put unnecessary pressure on your metrics system, metrics are aggregated by default.

    When debugging, it may be useful to return metrics per object (unaggregated). This can be enabled on-the-fly, without restarting or configuring RabbitMQ, using the following command:

    rabbitmqctl eval 'application:set_env(rabbitmq_prometheus, return_per_object_metrics, true).' 

    To go back to aggregated metrics on-the-fly, run the following command:

    rabbitmqctl eval 'application:set_env(rabbitmq_prometheus, return_per_object_metrics, false).' 

    Contributing

    See CONTRIBUTING.md.

    Makefile

    This project uses erlang.mk, running make help will return erlang.mk help.

    To see all custom targets that have been documented, run make h.

    For Bash shell autocompletion, run eval "$(make autocomplete)", then type make a<TAB> to see all Make targets starting with the letter a, e.g.:

    $ make a<TAB ac               all.coverdata    app-build        apps             apps-eunit       asciidoc-guide   autocomplete all              app              app-c_src        apps-ct          asciidoc         asciidoc-manual

    Copyright

    (c) 2007-2020 VMware, Inc. or its affiliates.

  • rabbitmq_prometheus plugin

    RabbitMQ with built-in Prometheus plugin
    (no exporter needed)

    Additionally, there is a solution to monitor RabbitMQ by using the built-in Prometheus plugin from RabbitMQ. Our recommendation is to use both options.

    How to install plugin, choose official metrics, and set alerts

    RabbitMQ version V3.8.0 and above supports the way to enable a built-in Prometheus metrics plugin that will expose all RabbitMQ metrics in Prometheus format to an endpoint that Prometheus can scrap by enabling the auto-discovery or by creating a service monitor. To enable the RabbitMQ plugin via Helm charts, set the metrics enabled to “true”.

    helm install <release name> bitnami/rabbitmq --set metrics.enabled=true

    More details about the plugin can be found here.

    In the case of standard Prometheus installation, once the plugin is enabled in RabbitMQ, annotations need to be added to RabbitMQ (if you are using the RabbitMQ chart it will be added automatically). Here are the annotations:

    annotations:
        prometheus.io/path: /metrics
        prometheus.io/scrape: "true"

    These annotations should be added on the pod level. Now Prometheus will automatically start scraping the data if the pod discovery is enabled.
    Prometheus configuration for pod discovery:

    - job_name: "kubernetes-pods"
    
        kubernetes_sd_configs:
          - role: pod
    

    In the case of the Prometheus Operator, once the plugin is enabled in RabbitMQ, the service monitor needs to be enables. For this, run the following command:

    helm upgrade ---install <release name> bitnami/rabbitmq --set metrics.enabled=true --set metrics.serviceMonitor.enabled=true

    Once the service monitor is created, the Prometheus operator will start scrapping the metrics automatically in the default configuration.

    Some important metrics

    1. Server is up
      As the name suggests, this metric will expose the state of the RabbitMQ process and whether it is up or down.
      ➡ The key of the exporter metric is “rabbitmq_up”.
      ➡ The value of the metric is a boolean - 1 or 0 which symbolizes if RabbitMQ is up or down respectively.  
    1. Cluster down
      Tis metric exposes the state of the RabbitMQ cluster.
      ➡ The key of the exporter metric is “rabbitmq_running
      ➡ The value of the metric is a number that symbolizes the number of nodes in the RabbitMQ cluster.
    1.  Out of memory
      The memory status of RabbitMQ is exposed through this metric.
      ➡ The key of the exporter metric is “rabbitmq_node_mem_used” and “rabbitmq_node_mem_limit
      ➡ The value of the metric is a number that symbolizes the number of available memory
    1. Too many connections
      RabbitMQ acts as a broker between a publisher and a subscriber. Every client to the queue opens a connection with RabbitMQ. Each new one requires resources from the underlying machine and puts burden on the hardware as well as software. Therefore, the number of connections to RabbitMQ should be limited to avoid any discrepancy in the service.
      ➡  metric “ rabbitmq_connectionsTotal” gives the total active connections on RabbitMQ
      ➡ The number should be calculated based on the resources allocated to the RabbitMQ service
    1. Cluster partitions down
      This metric exposes the RabbitMQ partition status.
      ➡ The key of the exporter metric is “rabbitmq_partitions
      ➡ The value of the metric is a number that symbolizes a number of the net
  • RabbitMQ Exporter Helm Chart
  • RabbitMQ Exporter Helm Chart

    helm repo add Prometheus-community https://prometheus-community.github.io/helm-charts
    
    helm repo update
    
    helm install [RELEASE_NAME] prometheus-community/prometheus-rabbitmq-exporter
    

    rabbitmq.url: Defines Rabbit MQ Listening URL.
    rabbitmq.user: Rabbit MQ connection User.
    rabbitmq.password: RabbitMQ password.

      capabilities: bert,no_sort
      include_queues: ".*"
      include_vhost: ".*"
      skip_queues: "^$"
      skip_verify: "false"
      skip_vhost: "^$"
      exporters: "exchange,node,overview,queue"
      output_format: "TTY"
      timeout: 30
      max_queues: 0

    # or use the service monitor
    prometheus:
      monitor:
        enabled: true
        additionalLabels:
          release: kps
        interval: 15s
        namespace: []
      rules:
        enabled: true
        additionalLabels:
          release: kps
          app: kube-prometheus-stack

    rabbitmq:
      url: http://ncmq-rabbitmq-hana.nc.svc.cluster.local:15672
      user: guest
      password: guest
      # If existingPasswordSecret is set then password is ignored
      existingPasswordSecret: ~
      existingPasswordSecretKey: password
      capabilities: bert,no_sort
      include_queues: ".*"
      include_vhost: ".*"
      skip_queues: "^$"
      skip_verify: "false"
      skip_vhost: "^$"
      exporters: "exchange,node,overview,queue"
      output_format: "TTY"
      timeout: 30
      max_queues: 0
    
    ## Additional labels to set in the Deployment object. Together with standard labels from
    ## the chart
    additionalLabels: {}
    
    podLabels: {}
    
    
    # Either use Annotation
    annotations:
      prometheus.io/scrape: "true"
      prometheus.io/path: "/metrics"
      prometheus.io/port: "9419"
    
    
    # or use the service monitor
    prometheus:
      monitor:
        enabled: true
        additionalLabels:
          release: kps
        interval: 15s
        namespace: []
      rules:
        enabled: true
        additionalLabels:
          release: kps
          app: kube-prometheus-stack

    annotations:
        prometheus.io/path: /metrics
        prometheus.io/scrape: "true"
  • rabbitmq/rabbitmq-prometheus: alerts
  • rabbitmq_prometheus plugin: alerts
  • rabbitmq/rabbitmq-prometheus: alerts

    After digging into all the valuable metrics, this section explains in detail how we can get critical alerts.

    PromQL is a query language for the Prometheus monitoring system. It is designed for building powerful yet simple queries for graphs, alerts, or derived time series (aka recording rules). PromQL is designed from scratch and has zero common grounds with other query languages used in time series databases, such as SQL in TimescaleDB, InfluxQL, or Flux. More details can be found here.

    Prometheus comes with a built-in Alert Manager that is responsible for sending alerts (could be email, Slack, or any other supported channel) when any of the trigger conditions is met. Alerting rules allow users to define alerts based on Prometheus query expressions. They are defined based on the available metrics scraped by the exporter. Click here for a good source for community-defined alerts.

    A general alert looks as follows:

    – alert:(Alert Name)
    expr: (Metric exported from exporter) >/</==/<=/=> (Value)
    for: (wait for a certain duration between first encountering a new expression output vector element and counting an alert as firing for this element)
    labels: (allows specifying a set of additional labels to be attached to the alert)
    annotation: (specifies a set of informational labels that can be used to store longer additional information)

    Some of the recommended RabbitMQ alerts are:

  • rabbitmq_prometheus plugin: alerts

    Some critical alerts

    1. Alert - Rabbit MQ Down
      - alert: RabbitmqDown
        expr: rabbitmq_up{service="{{ template "rabbitmq.fullname" . }}"} == 0
        for: 5m
        labels:
          severity: error
        annotations:
          summary: Rabbitmq down (instance {{ "{{ $labels.instance }}" }})
          description: RabbitMQ node down
    1. Alert - Rabbit MQ Cluster Down
      - alert: ClusterDown
        expr: |
          sum(rabbitmq_running{service="{{ template "rabbitmq.fullname" . }}"})
          < {{ .Values.replicaCount }}
        for: 5m
        labels:
          severity: error
        annotations:
          summary: Cluster down (instance {{ "{{ $labels.instance }}" }})
          description: |
              Less than {{ .Values.replicaCount }} nodes running in RabbitMQ cluster
              VALUE = {{ "{{ $value }}" }}
    1.  Alert - RabbitMQ Partition
      - alert: ClusterPartition
        expr: rabbitmq_partitions{service="{{ template "rabbitmq.fullname" . }}"} > 0
        for: 5m
        labels:
          severity: error
        annotations:
          summary: Cluster partition (instance {{ "{{ $labels.instance }}" }})
          description: |
              Cluster partition
              VALUE = {{ "{{ $value }}" }}
    1.   Alert - RabbitMQ is out of memory
      - alert: OutOfMemory
        expr: |
          rabbitmq_node_mem_used{service="{{ template "rabbitmq.fullname" . }}"}
          / rabbitmq_node_mem_limit{service="{{ template "rabbitmq.fullname" . }}"}
          * 100 > 90
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: Out of memory (instance {{ "{{ $labels.instance }}" }})
          description: |
              Memory available for RabbmitMQ is low (< 10%)\n  VALUE = {{ "{{ $value }}" }}
              LABELS: {{ "{{ $labels }}" }}
    1.  Alert - Too many connections
      - alert: TooManyConnections
        expr: rabbitmq_connectionsTotal{service="{{ template "rabbitmq.fullname" . }}"} > 1000
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: Too many connections (instance {{ "{{ $labels.instance }}" }})
          description: |
              RabbitMQ instance has too many connections (> 1000)
              VALUE = {{ "{{ $value }}" }}\n  LABELS: {{ "{{ $labels }}" }}

    Alerts can be enabled, disabled, altered, or added using the helm chart here.

  • RabbitMQ Exporter Grafana
  • RabbitMQ Prometheus Plugin Grafana
  • RabbitMQ Exporter Grafana

    Graphs are easier to understand and more user-friendly than a row of numbers. For this purpose, users can plot their time series data in visualized format using Grafana.

    Grafana is an open-source dashboarding tool used for visualizing metrics with the help of customizable and illustrative charts and graphs. It connects very well with Prometheus and makes monitoring easy and informative. Dashboards in Grafana are made up of panels, with each panel running a PromQL query to fetch metrics from Prometheus.
    Grafana supports community-driven graphs for most of the widely used software, which can be directly imported to the Grafana Community.

    NexClipper uses the Redis Database by the downager dashboard, which is widely accepted and has a lot of useful panels.

    What is a Panel?

    Panels are the most basic component of a dashboard and can display information in various ways, such as gauge, text, bar chart, graph, and so on. They provide information in a very interactive way. Users can view every panel separately and check the value of metrics within a specific time range. 
    The values on the panel are queried using PromQL, which is Prometheus Query Language. PromQL is a simple query language used to query metrics within Prometheus. It enables users to query data, aggregate and apply arithmetic functions to the metrics, and then further visualize them on panels.

    Here an example panel:

    Showing system up/down with other consumer-related information

  • RabbitMQ Prometheus Plugin Grafana

    Dashboard

    This is the dashboard that has been used.

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Jerry Lee
Jerry Lee
5 months ago

hi...

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