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RabbitMQ - Classic Collector

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The RabbitMQ app is a unified logs and metrics app that helps you monitor the availability, performance, health, and resource utilization of your RabbitMQ messaging clusters. Preconfigured dashboards provide insight into cluster status, exchanges, queues, nodes and error logs.

Sample log messages

Kubernetes environments
{
"Timestamp":1623650644120,
"log":"2021-06-14 06:04:02.885 [debug] <0.3106.0> Asked to [re-]register this node (rabbit@rabbitmq-1) with epmd...",
"Stream":"stdout",
"time":"2021-06-14T06:04:04.115318516Z"
}

Collecting Logs and Metrics for RabbitMQ

This section provides instructions for configuring log and metric collection for the Sumo Logic App for RabbitMQ.

Step 1: Configure Fields in Sumo Logic

Create the following Fields in Sumo Logic prior to configuring collection. This ensures that your logs and metrics are tagged with relevant metadata, which is required by the app dashboards. For information on setting up fields, see Sumo Logic Fields.

If you're using RabbitMQ in a Kubernetes environment, create the fields:

  • pod_labels_component
  • pod_labels_environment
  • pod_labels_messaging_system
  • pod_labels_messaging_cluster

Step 2: Configure Collection for RabbitMQ

Sumo Logic supports collection of logs and metrics data from RabbitMQ in both Kubernetes and non-Kubernetes environments.

Please click on the appropriate links below based on the host environment.

In Kubernetes environments, we use the Telegraf Operator, which is packaged with our Kubernetes collection. You can learn more about it here.The diagram below illustrates how data is collected from RabbitMQ in a Kubernetes environment. In the architecture shown below, there are four services that make up the metric collection pipeline: Telegraf, Telegraf Operator, Prometheus, and Sumo Logic Distribution for OpenTelemetry Collector.

rabbitmq-telegraf-operator

The first service in the metrics pipeline is Telegraf. Telegraf collects metrics from RabbitMQ. Note that we’re running Telegraf in each pod we want to collect metrics from as a sidecar deployment for example, Telegraf runs in the same pod as the containers it monitors. Telegraf uses the RabbitMQ input plugin to obtain metrics. (For simplicity, the diagram doesn’t show the input plugins.) The injection of the Telegraf sidecar container is done by the Telegraf Operator. Prometheus pulls metrics from Telegraf and sends them to Sumo Logic Distribution for OpenTelemetry Collector which enriches metadata and sends metrics to Sumo Logic.

In the logs pipeline, Sumo Logic Distribution for OpenTelemetry Collector collects logs written to standard out and forwards them to another instance of Sumo Logic Distribution for OpenTelemetry Collector, which enriches metadata and sends logs to Sumo Logic.

Prerequisites

It’s assumed that you are using the latest helm chart version. If not, upgrade using the instructions here.

Configure Metrics Collection

This section explains the steps to collect RabbitMQ metrics from a Kubernetes environment.

In Kubernetes environments, we use the Telegraf Operator, which is packaged with our Kubernetes collection. You can learn more on this here. Follow the steps listed below to collect metrics from a Kubernetes environment:

  1. Set up Kubernetes Collection with the Telegraf Operator
  2. On your RabbitMQ Pods, add the following annotations:
 annotations:
telegraf.influxdata.com/class: sumologic-prometheus
prometheus.io/scrape: "true"
prometheus.io/port: "9273"
telegraf.influxdata.com/inputs: |+
[[inputs.rabbitmq]]
url = "http://localhost:15672"
username = "<username_CHANGE_ME>"
password = "<password_CHANGE_ME>"
insecure_skip_verify = false
queue_name_include = []
queue_name_exclude = []
[inputs.rabbitmq.tags]
environment="prod_CHANGE_ME"
component="messaging"
messaging_system="rabbitmq"
messaging_cluster="rabbitmq_on_k8s_CHANGE_ME"

Please enter values for the following parameters (marked in CHANGE_ME above):

  • telegraf.influxdata.com/inputs. This contains the required configuration for the Telegraf RabbitMQ Input plugin. Please refer to this doc for more information on configuring the RabbitMQMongoDB input plugin for Telegraf. Note: As telegraf will be run as a sidecar the host should always be localhost.
    • In the input plugins section [[inputs.rabbitmq]]:
      • url - The URL of the RabbitMQ server for Management HTTP Endpoint. Please see this doc for more information on additional parameters for configuring the RabbitMQ input plugin for Telegraf.
      • username: The Username of RabbitMQ's admin account. The default is “guest”.
      • password: The password of RabbitMQ's admin account. The default is “guest”.
    • In the tags section [inputs.rabbitmq.tags]:
      • environment. This is the deployment environment where the RabbitMQ cluster identified by the value of servers resides. For example: dev, prod or qa. While this value is optional we highly recommend setting it.
      • messaging_cluster - Enter a name to identify this RabbitMQ cluster. This cluster name will be shown in the Sumo Logic dashboards.

Do not modify the following values set by this configuration as it will cause the Sumo Logic app to not function correctly.

  • telegraf.influxdata.com/class: sumologic-prometheus. This instructs the Telegraf operator what output to use. This should not be changed.
  • prometheus.io/scrape: "true". This ensures our Prometheus will scrape the metrics.
  • prometheus.io/port: "9273". This tells prometheus what ports to scrape on. This should not be changed.
  • telegraf.influxdata.com/inputs
    • In the tags section, [inputs.rabbitmq.tags]:
      • component: “messaging” - This value is used by Sumo Logic apps to identify application components.
      • messaging_system: “rabbitmq” - This value identifies the messaging system.

For all other parameters, see this doc for more parameters that can be configured in the Telegraf agent globally.

  1. Sumo Logic Kubernetes collection will automatically start collecting metrics from the pods having the labels and annotations defined in the previous step.
  2. Verify metrics in Sumo Logic.

Configure Logs Collection

This section explains the steps to collect RabbitMQ logs from a Kubernetes environment.

  1. Add labels on your RabbitMQ pods to capture logs from standard output. Make sure that the logs from RabbitMQ are sent to stdout. For more details see this doc. Follow the instructions below to capture RabbitMQRabbitMQ logs from stdout on Kubernetes.
    1. Apply following labels to the RabbitMQ pods:
    environment: "prod_CHANGE_ME"
    component: "messaging"
    messaging_system: "rabbitmq"
    messaging_cluster: "rabbitmq_on_k8s_CHANGE_ME"

Enter in values for the following parameters (marked CHANGE_ME above):

  • environment. This is the deployment environment where the RabbitMQ cluster identified by the value of servers resides. For example: dev, prod or qa. While this value is optional we highly recommend setting it.
  • messaging_cluster. Enter a name to identify this RabbitMQ cluster. This cluster name will be shown in the Sumo Logic dashboards.

Do not modify the following values as it will cause the Sumo Logic app to not function correctly.

  • component: “messaging”. This value is used by Sumo Logic apps to identify application components.
  • messaging_system: “rabbitmq”. This value identifies the messaging system.

For all other parameters see this doc for more parameters that can be configured in the Telegraf agent globally.

  1. (Optional) Collecting RabbitMQ Logs from a Log File. Follow the steps below to capture RabbitMQ logs from a log file on Kubernetes.
    1. Determine the location of the RabbitMQ log file on Kubernetes. This can be determined from the RabbitMQ.conf for your RabbitMQ cluster along with the mounts on the RabbitMQ pods.
    2. Install the Sumo Logic tailing sidecar operator.
    3. Add the following annotation in addition to the existing annotations.
    annotations:
    tailing-sidecar: sidecarconfig;<mount>:<path_of_RabbitMQ_log_file>/<RabbitMQ_log_file_name>
    Example:
    annotations:
    tailing-sidecar: sidecarconfig;data:/var/log/rabbitmq/rabbitmq.log
    1. Make sure that the RabbitMQ pods are running and annotations are applied by using the command:
kubectl describe pod <RabbitMQ_pod_name>
  1. Sumo Logic Kubernetes collection will automatically start collecting logs from the pods having the annotations defined above.
  2. Add an FER to normalize the fields in Kubernetes environments. Labels created in Kubernetes environments automatically are prefixed with pod_labels. To normalize these for our app to work, we need to create a Field Extraction Rule if not already created for Messaging Application Components. To do so:
    1. Go to Manage Data > Logs > Field Extraction Rules.
    2. Click the + Add button on the top right of the table.
    3. The Add Field Extraction Rule form will appear:
    4. Enter the following options:
    • Rule Name. Enter the name as App Observability - Messaging.
    • Applied At. Choose Ingest Time
    • Scope. Select Specific Data
    • Scope: Enter the following keyword search expression:
    pod_labels_environment=* pod_labels_component=messaging pod_labels_messaging_system=* pod_labels_messaging_cluster=*
    • Parse Expression.Enter the following parse expression:
    | if (!isEmpty(pod_labels_environment), pod_labels_environment, "") as environment
    | pod_labels_component as component
    | pod_labels_messaging_system as messaging_system
    | pod_labels_messaging_cluster as messaging_cluster
    1. Click Save to create the rule.

Installing Monitors

These instructions assume you have already set up collection as described in the Collect Logs and Metrics for RabbitMQ.

Sumo Logic has provided pre-packaged alerts available through Sumo Logic monitors to help you proactively determine if a RabbitMQ cluster is available and performing as expected. These monitors are based on metric and log data and include pre-set thresholds that reflect industry best practices and recommendations. For more information about individual alerts, see RabbitMQ Alerts.

To install these monitors, you must have the Manage Monitors role capability.

You can install monitors by importing a JSON file or using a Terraform script.

There are limits to how many alerts can be enabled. For more information, see Monitors for details.

Method A: Install Monitors by importing a JSON file

  1. Download the JSON file that describes the monitors.
  2. The JSON contains the alerts that are based on Sumo Logic searches that do not have any scope filters and therefore will be applicable to all RabbitMQ clusters, the data for which has been collected via the instructions in the previous sections. However, if you would like to restrict these alerts to specific clusters or environments, update the JSON file by replacing the text messaging_cluster=* with <Your Custom Filter>. Custom filter examples:
    • For alerts applicable only to a specific cluster, your custom filter would be: messaging_cluster=dev-rabbitmq01
    • For alerts applicable to all clusters that start with RabbitMQ-prod, your custom filter would be: messaging_cluster=RabbitMQ-prod*
    • For alerts applicable to a specific cluster within a production environment, your custom filter would be: messaging_cluster=dev-rabbitmq01 AND environment=prod (This assumes you have set the optional environment tag while configuring collection)
  3. Go to Manage Data > Alerts > Monitors.
  4. Click Add.
  5. Click Import.
  6. On the Import Content popup, enter RabbitMQ in the Name field, paste in the JSON into the the popup, and click Import.
  7. The monitors are created in a "RabbitMQ" folder. The monitors are disabled by default. See the Monitors topic for information about enabling monitors and configuring notifications or connections.

Method B: Install Monitors using a Terraform script

  1. Generate an access key and access ID for a user that has the Manage Monitors role capability. For instructions see Access Keys.
  2. Download Terraform 0.13 or later, and install it.
  3. Download the Sumo Logic Terraform package for MySQL monitors: The alerts package is available in the Sumo Logic GitHub repository. You can either download it using the git clone command or as a zip file.
  4. Alert Configuration: After extracting the package, navigate to the terraform-sumologic-sumo-logic-monitor/monitor_packages/RabbitMQ/ directory.

Edit the rabbitmq.auto.tfvars file and add the Sumo Logic Access Key and Access ID from Step 1 and your Sumo Logic deployment. If you're not sure of your deployment, see Sumo Logic Endpoints and Firewall Security.

access_id   = "<SUMOLOGIC ACCESS ID>"
access_key = "<SUMOLOGIC ACCESS KEY>"
environment = "<SUMOLOGIC DEPLOYMENT>"

The Terraform script installs the alerts without any scope filters, if you would like to restrict the alerts to specific clusters or environments, update the rabbitmq_data_source variable. For example:

  • To configure alerts for A specific cluster, set rabbitmq_data_source to something like: messaging_cluster=rabbitmq.prod.01
  • To configure alerts for All clusters in an environment, set rabbitmq_data_source to something like: environment=prod
  • To configure alerts for Multiple clusters using a wildcard, set rabbitmq_data_source to something like: messaging_cluster=rabbitmq-prod*
  • To configure alerts for A specific cluster within a specific environment, set rabbitmq_data_source to something like: messaging_cluster=rabbitmq-1 and environment=prod. This assumes you have configured and applied Fields as described in Step 1: Configure Fields of the Sumo Logic of the Collect Logs and Metrics for RabbitMQ.

All monitors are disabled by default on installation. To enable all of the monitors, set the monitors_disabled parameter to false.

By default, the monitors will be located in a "RabbitMQ" folder on the Monitors page. To change the name of the folder, update the monitor folder name in the folder variable in the rabbitmq.auto.tfvars file.

  1. If you want the alerts to send email or connection notifications, edit the rabbitmq_notifications.auto.tfvars file to populate the connection_notifications and email_notifications sections. Examples are provided below.

In the variable definition below, replace <CONNECTION_ID> with the connection ID of the Webhook connection. You can obtain the Webhook connection ID by calling the Monitors API.

Pagerduty connection example
connection_notifications = [
{
connection_type = "PagerDuty",
connection_id = "<CONNECTION_ID>",
payload_override = "{\"service_key\": \"your_pagerduty_api_integration_key\",\"event_type\": \"trigger\",\"description\": \"Alert: Triggered {{TriggerType}} for Monitor {{Name}}\",\"client\": \"Sumo Logic\",\"client_url\": \"{{QueryUrl}}\"}",
run_for_trigger_types = ["Critical", "ResolvedCritical"]
},
{
connection_type = "Webhook",
connection_id = "<CONNECTION_ID>",
payload_override = "",
run_for_trigger_types = ["Critical", "ResolvedCritical"]
}
]

For information about overriding the payload for different connection types, see Set Up Webhook Connections.

Email notifications example
email_notifications = [
{
connection_type = "Email",
recipients = ["abc@example.com"],
subject = "Monitor Alert: {{TriggerType}} on {{Name}}",
time_zone = "PST",
message_body = "Triggered {{TriggerType}} Alert on {{Name}}: {{QueryURL}}",
run_for_trigger_types = ["Critical", "ResolvedCritical"]
}
]
  1. Install Monitors:
    1. Navigate to the terraform-sumologic-sumo-logic-monitor/monitor_packages/rabbitmq/ directory and run terraform init. This will initialize Terraform and download the required components.
    2. Run terraform plan to view the monitors that Terraform will create or modify.
    3. Run terraform apply.

Installing the RabbitMQ App

This section demonstrates how to install the RabbitMQ App.

  1. From the App Catalog, search for and select the RabbitMQ app.
  2. Select the version of the service you're using and click Add to Library.
note

Version selection is not available for all apps.

  1. To install the app, complete the following fields.
    1. App Name. You can retain the existing name, or enter a name of your choice for the app.

    2. Data Source. Choose Enter a Custom Data Filter, and enter a custom RabbitMQ cluster filter. Examples:
      1. For all RabbitMQ clusters: messaging_cluster=*
      2. For a specific cluster: messaging_cluster=rabbitmq.dev.01
      3. Clusters within a specific environment: messaging_cluster=rabbitmq-1 and environment=prod. This assumes you have set the optional environment tag while configuring collection.
  2. Advanced. Select the Location in Library (the default is the Personal folder in the library), or click New Folder to add a new folder.
  3. Click Add to Library.

Once an app is installed, it will appear in your Personal folder, or other folder that you specified. From here, you can share it with your organization.

Panels will start to fill automatically. It's important to note that each panel slowly fills with data matching the time range query and received since the panel was created. Results won't immediately be available, but with a bit of time, you'll see full graphs and maps.

Viewing RabbitMQ Dashboards

Dashboard Filters with Template Variables

Template variables provide dynamic dashboards that rescope data on the fly. As you apply variables to troubleshoot through your dashboard, you can view dynamic changes to the data for a fast resolution to the root cause. For more information, see the Filter with template variables help page.

Overview

The RabbitMQ - Overview dashboard gives you an at-a-glance view of your RabbitMQ deployment across brokers, queues, exchanges, and messages.

Use this dashboard to:

  • Analyze Memory and disk utilization.
  • Gain insights into pushing messages for your RabbitMQ server.
  • Gain insights into delivery messages for your RabbitMQ server.
  • Determine the number of nodes, connections, exchanges, consume, queues, unack messages, total messages, across each cluster and ensure they match with expectations
  • Analysis of near errors.
RabbitMQ dashboards

Node

The RabbitMQ - Node dashboard helps you Get an at-a-glance view of the state of the nodes in the RabbitMQ cluster.

Use this dashboard to:

  • Monitor the number of open file descriptors.
  • Monitor uptime of nodes.
  • Determine the amount of ram transaction, disk transaction.
  • Determine the amount of garbage collection per second.
  • Monitor current memory usage
RabbitMQ dashboards

Queue

The RabbitMQ - Queue dashboard provides an at-a-glance view of the state of your queues in your RabbitMQ clusters.

Use this dashboard to:

  • Monitor number of consumers on queues
  • Gain insights into pushing messages rate for queues of your RabbitMQ cluster.
  • Gain insights into delivery messages rate for queues of your RabbitMQ cluster.
  • Determine the amount of slave nodes for queues.
  • Monitor memory usage of queues over time.
  • Determine the number of error messages on queues.
RabbitMQ dashboards

Exchanges

The RabbitMQ - Exchanges dashboard provides an at-a-glance view of the state of your exchanges in your RabbitMQ clusters.

Use this dashboard to:

  • Monitor number of total messages published in exchanges
  • Monitor number of total messages published out exchanges
  • Gain insights into message publish Rate in exchanges of your RabbitMQ cluster.
  • Gain insights into message publish Rate out exchanges of your RabbitMQ cluster.
RabbitMQ dashboards

Logs

This dashboard helps you quickly analyze your RabbitMQ error logs across all clusters.

Use this dashboard to:

  • Identify critical events in your RabbitMQ cluster.
  • Examine trends to detect spikes in Error or Fatal events
  • Monitor Broker added/started and shutdown events in your cluster.
  • Quickly determine patterns across all logs in a given RabbitMQ cluster.
RabbitMQ dashboards

RabbitMQ Alerts

Sumo Logic provides out-of-the-box alerts available via Sumo Logic monitors. These alerts are built based on logs and metrics datasets and have preset thresholds based on industry best practices and recommendations.

Alert NameAlert DescriptionTrigger Type (Critical / Warning)Alert Condition Recover Condition
RabbitMQ - High Memory Usage This alert fires when memory usage on a node in a RabbitMQ cluster is high. Critical > = 80 < 80
RabbitMQ - No Consumers This alert fires when a RabbitMQ queue has no consumers. Critical < 1 > = 1
RabbitMQ - High Disk Usage This alert fires when there is high disk usage on a node in a RabbitMQ cluster. Critical > = 80 < 80
RabbitMQ - High Number of File Descriptors in use This alert fires when the percentage of file descriptors used by a node in a RabbitMQ cluster is high. Critical > = 90 < 90
RabbitMQ - Node Down This alert fires when a node in the RabbitMQ cluster is down. Critical > = 1 < 1
RabbitMQ - Too Many Connections This alert fires when there are too many connections to a node in a RabbitMQ cluster. Critical > = 1000 < 1000
RabbitMQ - Too Many Un-acknowledged Messages This alert fires when we detect that there are too many un-acknowledged messages on a node in a RabbitMQ cluster. Critical > = 1000 < 1000
RabbitMQ - Un-routable Messages This alert fires when we detect that a node in the RabbitMQ cluster has un-routable messages Critical > = 1 < 1
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