Managed RabbitMQ Service

RabbitMQ is a robust message broker that plays a crucial role in modern distributed systems. Our Managed RabbitMQ Service simplifies the deployment and management of RabbitMQ clusters, ensuring reliability and scalability for your messaging needs.

Deployment Details

The service utilizes official RabbitMQ operator. This ensures the reliability and seamless operation of your RabbitMQ instances.

storageClass is annotated as immutable in the chart schema — see docs/storage-immutability.md for the contract and which consumers enforce it.

Parameters

Common parameters

NameDescriptionTypeValue
replicasNumber of RabbitMQ replicas.int3
resourcesExplicit CPU and memory configuration for each RabbitMQ replica. Every resource left unset here is taken from resourcesPreset.object{}
resources.cpuCPU available to each replica.quantity""
resources.memoryMemory (RAM) available to each replica.quantity""
resourcesPresetDefault sizing preset. It supplies every resource resources does not set, not only a resources left empty entirely.strings1.nano
sizePersistent Volume Claim size available for application data.quantity10Gi
storageClassStorageClass used to store the data.string""
externalEnable external access from outside the cluster.boolfalse
versionRabbitMQ major.minor version to deploystringv4.2

Application-specific parameters

NameDescriptionTypeValue
usersUsers configuration map.map[string]object{}
users[name].passwordPassword for the user.string""
vhostsVirtual hosts configuration map.map[string]object{}
vhosts[name].rolesVirtual host roles list.object{}
vhosts[name].roles.adminList of admin users.[]string[]
vhosts[name].roles.readonlyList of readonly users.[]string[]

Parameter examples and reference

resources and resourcesPreset

resources sets explicit CPU and memory configurations for each replica. When left empty, the preset defined in resourcesPreset is applied.

resources:
  cpu: 4000m
  memory: 4Gi

resourcesPreset sets named CPU and memory configurations for each replica. This setting is ignored if the corresponding resources value is set.

Presets follow a cloud-style <series>.<size> naming convention. Five series cover the full CPU-to-memory ratio range (t1 1:0.5, c1 1:1, s1 1:2, u1 1:4, m1 1:8) and each series ships eight sizes (nano through 4xlarge). The legacy flat names (nano, micro, small, medium, large, xlarge, 2xlarge) remain accepted as deprecated aliases of their 1:1 instance-type equivalents.

See docs/operations/resource-presets.md for the full size matrix and the legacy-to-instance-type mapping.