bitnamicharts/rabbitmq Docker 镜像 - 轩辕镜像

Bitnami Secure Images Helm chart for RabbitMQ

RabbitMQ is an open source general-purpose message broker that is designed for consistent, highly-available messaging scenarios (both synchronous and asynchronous).

Overview of RabbitMQ

Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

TL;DR

console
helm install my-release oci://registry-1.docker.io/bitnamicharts/rabbitmq

Tip: Did you know that this app is also available as a Kubernetes App on the Azure Marketplace? Kubernetes Apps are the easiest way to deploy Bitnami on AKS. Click here to see the listing on Azure Marketplace.

Why use Bitnami Secure Images?

Those are hardened, minimal CVE images built and maintained by Bitnami. Bitnami Secure Images are based on the cloud-optimized, security-hardened enterprise OS Photon Linux. Why choose BSI images?

• Hardened secure images of popular open source software with Near-Zero Vulnerabilities
• Vulnerability Triage & Prioritization with VEX Statements, KEV and EPSS Scores
• Compliance focus with FIPS, STIG, and air-gap options, including secure bill of materials (SBOM)
• Software supply chain provenance attestation through in-toto
• First class support for the internet’s favorite Helm charts

Each image comes with valuable security metadata. You can view the metadata in our public catalog here. Note: Some data is only available with commercial subscriptions to BSI.

!Alt text !Alt text

If you are looking for our previous generation of images based on Debian Linux, please see the Bitnami Legacy registry.

Introduction

This chart bootstraps a RabbitMQ deployment on a Kubernetes cluster using the Helm package manager.

Prerequisites

• Kubernetes 1.23+
• Helm 3.8.0+
• PV provisioner support in the underlying infrastructure

Installing the Chart

To install the chart with the release name my-release:

console
helm install my-release oci://REGISTRY_NAME/REPOSITORY_NAME/rabbitmq

Note: You need to substitute the placeholders REGISTRY_NAME and REPOSITORY_NAME with a reference to your Helm chart registry and repository. For example, in the case of Bitnami, you need to use REGISTRY_NAME=registry-1.docker.io and REPOSITORY_NAME=bitnamicharts.

The command deploys RabbitMQ on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation.

Tip: List all releases using helm list

Configuration and installation details

Resource requests and limits

Bitnami charts allow setting resource requests and limits for all containers inside the chart deployment. These are inside the resources value (check parameter table). Setting requests is essential for production workloads and these should be adapted to your specific use case.

To make this process easier, the chart contains the resourcesPreset values, which automatically sets the resources section according to different presets. Check these presets in the bitnami/common chart. However, in production workloads using resourcesPreset is discouraged as it may not fully adapt to your specific needs. Find more information on container resource management in the official Kubernetes documentation.

Prometheus metrics

This chart can be integrated with Prometheus by setting metrics.enabled to true. This enable the rabbitmq_prometheus plugin and expose a metrics endpoints in all pods and the RabbitMQ service. The service will have the necessary annotations to be automatically scraped by Prometheus.

Prometheus requirements

It is necessary to have a working installation of Prometheus or Prometheus Operator for the integration to work. Install the Bitnami Prometheus helm chart or the Bitnami Kube Prometheus helm chart to easily have a working Prometheus in your cluster.

Integration with Prometheus Operator

The chart can deploy ServiceMonitor objects for integration with Prometheus Operator installations. There are different ServiceMonitor objects per RabbitMQ endpoins. The chart includes:

• metrics.serviceMonitor.default for the /metrics endpoint.
• metrics.serviceMonitor.perObject for the /metrics/per-object endpoint.
• metrics.serviceMonitor.detailed for the /metrics/detailed endpoint.

Enable each ServiceMonitor by setting metrics.serviceMonitor.*.enabled=true. Ensure that the Prometheus Operator CustomResourceDefinitions are installed in the cluster or it will fail with the following error:

text
no matches for kind "ServiceMonitor" in version "monitoring.coreos.com/v1"

Install the Bitnami Kube Prometheus helm chart for having the necessary CRDs and the Prometheus Operator.

Rolling vs Immutable tags

It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.

Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.

Set pod affinity

This chart allows you to set your custom affinity using the affinity parameter. Find more information about Pod's affinity in the kubernetes documentation.

As an alternative, you can use of the preset configurations for pod affinity, pod anti-affinity, and node affinity available at the bitnami/common chart. To do so, set the podAffinityPreset, podAntiAffinityPreset, or nodeAffinityPreset parameters.

Scale horizontally

To horizontally scale this chart once it has been deployed, two options are available:

• Use the kubectl scale command.
• Upgrade the chart modifying the replicaCount parameter.

text
    replicaCount=3
    auth.password="$RABBITMQ_PASSWORD"
    auth.erlangCookie="$RABBITMQ_ERLANG_COOKIE"

NOTE: It is mandatory to specify the password and Erlang cookie that was set the first time the chart was installed when upgrading the chart. Otherwise, new pods won't be able to join the cluster.

When scaling down the solution, unnecessary RabbitMQ nodes are automatically stopped, but they are not removed from the cluster. These nodes must be manually removed via the rabbitmqctl forget_cluster_node command.

For instance, if RabbitMQ was initially installed with three replicas and then scaled down to two replicas, run the commands below (assuming that the release name is rabbitmq and the clustering type is hostname):

console
    kubectl exec rabbitmq-0 --container rabbitmq -- rabbitmqctl forget_cluster_node ***
    kubectl delete pvc data-rabbitmq-2

NOTE: It is mandatory to specify the password and Erlang cookie that was set the first time the chart was installed when upgrading the chart.

Securing traffic using TLS

To enable TLS support, first generate the certificates as described in the RabbitMQ documentation for SSL certificate generation.

Once the certificates are generated, you have two alternatives:

• Create a secret with the certificates and associate the secret when deploying the chart
• Include the certificates in the values.yaml file when deploying the chart

Set the auth.tls.failIfNoPeerCert parameter to false to allow a TLS connection if the client fails to provide a certificate.

Set the auth.tls.sslOptionsVerify to verify_peer to force a node to perform peer verification. When set to verify_none, peer verification will be disabled and certificate exchange won't be performed.

This chart also facilitates the creation of TLS secrets for use with the Ingress controller (although this is not mandatory). There are several common use cases:

• Generate certificate secrets based on chart parameters.
• Enable externally generated certificates.
• Manage application certificates via an external service (like cert-manager).
• Create self-signed certificates within the chart (if supported).

In the first two cases, a certificate and a key are needed. Files are expected in .pem format.

Here is an example of a certificate file:

NOTE: There may be more than one certificate if there is a certificate chain.

text
-----BEGIN CERTIFICATE-----
MIID6TCCAtGgAwIBAgIJAIaCwivkeB5EMA0GCSqGSIb3DQEBCwUAMFYxCzAJBgNV
...
jScrvkiBO65F46KioCL9h5tDvomdU1aqpI/CBzhvZn1c0ZTf87tGQR8NK7v7
-----END CERTIFICATE-----

Here is an example of a certificate key:

text
-----BEGIN RSA PRIVATE KEY-----
MIIEogIBAAKCAQEAvLYcyu8f3skuRyUgeeNpeDvYBCDcgq+LsWap6zbX5f8oLqp4
...
wrj2wDbCDCFmfqnSJ+dKI3vFLlEz44sAV8jX/kd4Y6ZTQhlLbYc=
-----END RSA PRIVATE KEY-----

• If using Helm to manage the certificates based on the parameters, copy these values into the certificate and key values for a given *.ingress.secrets entry.
• If managing TLS secrets separately, it is necessary to create a TLS secret with name INGRESS_HOSTNAME-tls (where INGRESS_HOSTNAME is a placeholder to be replaced with the hostname you set using the *.ingress.hostname parameter).
• If your cluster has a cert-manager add-on to automate the management and issuance of TLS certificates, add to *.ingress.annotations the corresponding ones for cert-manager.
• If using self-signed certificates created by Helm, set both *.ingress.tls and *.ingress.selfSigned to true.

Load custom definitions

It is possible to load a RabbitMQ definitions file to configure RabbitMQ. Follow the steps below:

Because definitions may contain RabbitMQ credentials, store the JSON as a Kubernetes secret. Within the secret's data, choose a key name that corresponds with the desired load definitions filename (i.e. load_definition.json) and use the JSON object as the value.

Next, specify the load_definitions property as an extraConfiguration pointing to the load definition file path within the container (i.e. /app/load_definition.json) and set loadDefinition.enable to true. Any load definitions specified will be available within in the container at /app.

NOTE: Loading a definition will take precedence over any configuration done through Helm values.

If needed, you can use extraSecrets to let the chart create the secret for you. This way, you don't need to manually create it before deploying a release. These secrets can also be templated to use supplied chart values. Here is an example:

yaml
auth:
  password: CHANGEME
extraSecrets:
  load-definition:
    load_definition.json: |
      {
        "users": [
          {
            "name": "{{ .Values.auth.username }}",
            "password": "{{ .Values.auth.password }}",
            "tags": "administrator"
          }
        ],
        "vhosts": [
          {
            "name": "/"
          }
        ]
      }
loadDefinition:
  enabled: true
  existingSecret: load-definition
extraConfiguration: |
  load_definitions = /app/load_definition.json

Update credentials

The Bitnami RabbitMQ chart, when upgrading, reuses the secret previously rendered by the chart or the one specified in auth.existingSecret. To update credentials, use one of the following:

• Run helm upgrade specifying a new password in auth.password and auth.updatePassword=true.
• Run helm upgrade specifying a new secret in auth.existingSecret and auth.updatePassword=true.

Configure LDAP support

LDAP support can be enabled in the chart by specifying the ldap.* parameters while creating a release. For example:

text
ldap.enabled="true"
ldap.server="my-ldap-server"
ldap.port="389"
ldap.user_dn_pattern="cn=${username},dc=example,dc=org"

If ldap.tls.enabled is set to true, consider using ldap.port=636 and checking the settings in the advancedConfiguration chart parameters.

Configure memory high watermark

It is possible to configure a memory high watermark on RabbitMQ to define memory thresholds using the memoryHighWatermark.* parameters. To do so, you have two alternatives:

• Set an absolute limit of RAM to be used on each RabbitMQ node, as shown in the configuration example below:

text
memoryHighWatermark.enabled="true"
memoryHighWatermark.type="absolute"
memoryHighWatermark.value="512Mi"

• Set a relative limit of RAM to be used on each RabbitMQ node. To enable this feature, define the memory limits at pod level too. An example configuration is shown below:

text
memoryHighWatermark.enabled="true"
memoryHighWatermark.type="relative"
memoryHighWatermark.value="0.4"
resources.limits.memory="2Gi"

Add extra environment variables

In case you want to add extra environment variables (useful for advanced operations like custom init scripts), you can use the extraEnvVars property.

yaml
extraEnvVars:
  - name: LOG_LEVEL
    value: error

Alternatively, you can use a ConfigMap or a Secret with the environment variables. To do so, use the .extraEnvVarsCM or the extraEnvVarsSecret properties.

Configure the default user/vhost

If you want to create default user/vhost and set the default permission. you can use extraConfiguration:

yaml
auth:
  username: default-user
extraConfiguration: |-
  default_vhost = default-vhost
  default_permissions.configure = .*
  default_permissions.read = .*
  default_permissions.write = .*

Use plugins

The Bitnami Docker RabbitMQ image ships a set of plugins by default. By default, this chart enables rabbitmq_management and rabbitmq_peer_discovery_k8s since they are required for RabbitMQ to work on K8s.

To enable extra plugins, set the extraPlugins parameter with the list of plugins you want to enable. In addition to this, the communityPlugins parameter can be used to specify a list of URLs (separated by spaces) for custom plugins for RabbitMQ.

text
communityPlugins="[***]"
extraPlugins="my-custom-plugin"

Advanced logging

In case you want to configure RabbitMQ logging set logs value to false and set the log config in extraConfiguration following the official documentation.

An example:

yaml
logs: false # custom logging
extraConfiguration: |
  log.default.level = warning
  log.file = false
  log.console = true
  log.console.level = warning
  log.console.formatter = json

How to Avoid Deadlocked Deployments After a Cluster-Wide Restart

RabbitMQ nodes assume their peers come back online within five minutes (by default). When the OrderedReady pod management policy is used with a readiness probe that implicitly requires a fully booted node, the deployment can deadlock:

• Kubernetes will expect the first node to pass a readiness probe
• The readiness probe may require a fully booted node
• The node will fully boot after it detects that its peers have come online
• Kubernetes will not start any more pods until the first one boots

The following combination of deployment settings avoids the problem:

• Use podManagementPolicy: "Parallel" to boot multiple cluster nodes in parallel
• Use rabbitmq-diagnostics ping for readiness probe

To learn more, please consult RabbitMQ documentation guides:

• RabbitMQ Clustering guide: Node Restarts
• RabbitMQ Clustering guide: Restarts and Readiness Probes
• Recommendations for Operator-less (DIY) deployments to Kubernetes

Do Not Force Boot Nodes on a Regular Basis

Note that forcing nodes to boot is not a solution and doing so can be dangerous. Forced booting is a last resort mechanism in RabbitMQ that helps make remaining cluster nodes recover and rejoin each other after a permanent loss of some of their former peers. In other words, forced booting a node is an emergency event recovery procedure.

Known issues

• Changing the password through RabbitMQ's UI can make the pod fail due to the default liveness probes. If you do so, remember to make the chart aware of the new password. Updating the default secret with the password you set through RabbitMQ's UI will automatically recreate the pods. If you are using your own secret, you may have to manually recreate the pods.

Backup and restore

To back up and restore Helm chart deployments on Kubernetes, you need to back up the persistent volumes from the source deployment and attach them to a new deployment using Velero, a Kubernetes backup/restore tool. Find the instructions for using Velero in this guide.

Persistence

The Bitnami RabbitMQ image stores the RabbitMQ data and configurations at the /opt/bitnami/rabbitmq/var/lib/rabbitmq/ path of the container.

The chart mounts a Persistent Volume at this location. By default, the volume is created using dynamic volume provisioning. An existing PersistentVolumeClaim can also be defined.

Use existing PersistentVolumeClaims

1. Create the PersistentVolume
2. Create the PersistentVolumeClaim
3. Install the chart

console
helm install my-release --set persistence.existingClaim=PVC_NAME oci://REGISTRY_NAME/REPOSITORY_NAME/rabbitmq

Note: You need to substitute the placeholders REGISTRY_NAME and REPOSITORY_NAME with a reference to your Helm chart registry and repository. For example, in the case of Bitnami, you need to use REGISTRY_NAME=registry-1.docker.io and REPOSITORY_NAME=bitnamicharts.

Adjust permissions of the persistence volume mountpoint

As the image runs as non-root by default, it is necessary to adjust the ownership of the persistent volume so that the container can write data into it.

By default, the chart is configured to use Kubernetes Security Context to automatically change the ownership of the volume. However, this feature does not work in all Kubernetes distributions. As an alternative, this chart supports using an initContainer to change the ownership of the volume before mounting it in the final destination.

You can enable this initContainer by setting volumePermissions.enabled to true.

Prometheus Metrics

RabbitMQ has built-in support for Prometheus metrics exposed at GET /metrics. However, these metrics are all cluster-wide, and do not show any per-queue or per-node metrics.

To get per-object metrics, there is a second metrics endpoint at GET /metrics/detailed that accepts query parameters to choose which metric families you would like to see. For instance, you can pass family=node_coarse_metrics&family=queue_coarse_metrics to see per-node and per-queue metrics, but with no need to see Erlang, connection, or channel metrics.

Additionally, there is a third metrics endpoint: GET /metrics/per-object. which returns all per-object metrics. However, this can be computationally expensive on a large cluster with many objects, and so RabbitMQ docs suggest using GET /metrics/detailed mentioned above to filter your scraping and only fetch the per-object metrics that are needed for a given monitoring application.

Because they expose different sets of data, a valid use case is to scrape metrics from both GET /metrics and GET /metrics/detailed, ingesting both cluster-level and per-object metrics. The metrics.serviceMonitor.default and metrics.serviceMonitor.detailed values support configuring a ServiceMonitor that targets one or both of these metrics.

Parameters

Global parameters

_Note: the README for this chart is longer than the DockerHub length limit of 25000, so it has been trimmed. The full README can be found at [***]