Configure disk-backed message buffer behavior
Important
This setting requires modifying the Broker resource and can only be configured at initial deployment time using the Azure CLI or Azure Portal. A new deployment is required if Broker configuration changes are needed. To learn more, see Customize default Broker.
The disk-backed message buffer feature is used for efficient management of message queues within the MQTT broker distributed MQTT broker. The benefits include:
Efficient queue management: In an MQTT broker, each subscriber is associated with a message queue. The speed a subscriber processes messages directly impacts the size of the queue. If a subscriber processes messages slowly or if they disconnect but request an MQTT persistent session, the queue can grow larger than the available memory.
Data preservation for persistent sessions: The disk-backed message buffer feature ensures that when a queue exceeds the available memory, it's seamlessly buffered to disk. This feature prevents data loss and supports MQTT persistent sessions, allowing subscribers to resume their sessions with their message queues intact upon reconnection. The disk is used as ephemeral storage and serves as a spillover from memory. Data written to disk isn't durable and is lost when the pod exits, but as long as at least one pod in each backend chain remains functional, the broker as a whole doesn't lose any data.
Handling connectivity challenges: Cloud connectors are treated as subscribers with persistent sessions that can face connectivity challenges when unable to communicate with external systems like Event Grid MQTT broker due to network disconnect. In such scenarios, messages (PUBLISHes) accumulate. The MQTT broker intelligently buffers these messages to memory or disk until connectivity is restored, ensuring message integrity.
By default, the disk-backed message buffer feature is disabled. In this case, messages remain in memory, and back pressure is applied to clients as the reader pool or scratch pool reaches the limit as defined by the subscriber queue limit.
Configuring the disk-backed message buffer is essential for maintaining a robust and reliable message queuing system, especially in scenarios where message processing speed and connectivity are critical.
Note
The MQTT broker writes data to disk exactly as received from clients, without additional encryption. Securing the disk is essential to protect the data stored by the broker.
Configuration options
To configure the disk-backed message buffer, edit the diskBackedMessageBuffer
section in the Broker resource. Currently this is only supported using the --broker-config-file
flag when you deploy the Azure IoT Operations using the az iot ops create
command.
To get started, prepare a Broker config file following the DiskBackedMessageBuffer API reference.
For example, the simplest configuration involves only specifying the max size. In this case, an emptyDir
volume is mounted. The maxSize
value is used as the size limit of the emptyDir
volume. But this is the least preferred option giving the limitations of emptyDir
volume.
{
"diskBackedMessageBuffer": {
"maxSize": "<SIZE>"
}
}
To get a better disk-backed message buffer configuration, specify an ephemeral volume or persistent volume claim to mount a dedicated storage volume for your message buffer. For example:
{
"diskBackedMessageBuffer": {
"maxSize": "<SIZE>",
"ephemeralVolumeClaimSpec": {
"storageClassName": "<NAME>",
"accessModes": [
"<MODE>"
]
}
}
}
{
"persistentVolumeClaimSpec": {
"maxSize": "<SIZE>",
"ephemeralVolumeClaimSpec": {
"storageClassName": "<NAME>",
"accessModes": [
"<MODE>"
]
}
}
}
Tailor the broker message buffer options by adjusting the following settings:
Configure the volume: Specify a volume claim template to mount a dedicated storage volume for your message buffer.
Select a storage class: Define the desired StorageClass using the
storageClassName
property.Define access modes: Determine the access modes you need for your volume. For more information, see persistent volume access modes.
Use the following sections to understand the different volume modes:
- Ephemeral volume is the preferred option,
- Persistent volume is preferred next, and
emptyDir
volume least preferred.
Both persistent and ephemeral volumes are generally provided by the same storage classes. If both options are available, choose ephemeral. Note that ephemeral volumes require Kubernetes 1.23 or higher.
Tip
Specifying a Ephemeral Volume Claim (EVC) or Persistent Volume Claim (PVC) template lets you to use a storage class of your choice, increasing flexibility for some deployment scenarios. For example, Persistent Volumes (PVs) provisioned using a PVC template appear in commands like kubectl get pv
, which can be useful for inspecting the cluster state.
If your Kubernetes nodes lack sufficient local disk space for the message buffer, use a storage class that provides network storage like Azure Blobs. However, it's generally better to use local disk with a smaller maxSize
value, as the message buffer benefits from fast access and doesn't require durability.
Deploy Azure IoT Operations with disk-backed message buffer
To use disk-backed message buffer, deploy Azure IoT Operations using the az iot ops create
command with the --broker-config-file
flag. See the following command (other parameters omitted for brevity):
az iot ops create ... --broker-config-file <FILE>.json
This setting cannot be changed after deployment. To change the disk-backed message buffer configuration, redeploy the Azure IoT Operations instance.
Ephemeral volume
Ephemeral volume is the preferred option for your message buffer.
For ephemeral volume, follow the advice in the Considerations for storage providers section.
The value of the ephemeralVolumeClaimSpec
property is used as the ephemeral.volumeClaimTemplate.spec
property of the volume in the StatefulSet specs of the backend chains.
For example, to use an ephemeral volume with a capacity of 1 gigabyte, specify the following parameters in your Broker resource:
{
"diskBackedMessageBuffer": {
"maxSize": "1G",
"ephemeralVolumeClaimSpec": {
"storageClassName": "foo",
"accessModes": [
"ReadWriteOnce"
]
}
}
}
Persistent volume
Persistent volume is the next preferred option for your message buffer after ephemeral volume.
For persistent volume, follow the advice in Considerations for storage providers section.
The value of the persistentVolumeClaimSpec
property is used as the volumeClaimTemplates.spec
property of the StatefulSet specs of the backend chains.
For example, to use a persistent volume with a capacity of 1 gigabyte, specify the following parameters in your Broker resource:
{
"diskBackedMessageBuffer": {
"maxSize": "1G",
"persistentVolumeClaimSpec": {
"storageClassName": "foo",
"accessModes": [
"ReadWriteOnce"
]
}
}
}
emptyDir
volume
An emptyDir volume is the least preferred option after persistent volume.
Only use emptyDir volume when using a cluster with filesystem quotas. For more information, see details in the Filesystem project quota tab. If the feature isn't enabled, the cluster does periodic scanning that doesn't enforce any limit and allows the host node to fill disk space and mark the whole host node as unhealthy.
For example, to use an emptyDir volume with a capacity of 1 gigabyte, specify the following parameters in your Broker resource:
{
"diskBackedMessageBuffer": {
"maxSize": "1G"
}
}
Considerations for storage providers
Consider the behavior of your chosen storage provider. For example, when using providers like rancher.io/local-path
. If the provider doesn't support limits, filling up the volume consumes the node's disk space. This could lead to Kubernetes marking the node and all associated pods as unhealthy. It's crucial to understand how your storage provider behaves in such scenarios.
Disabled
If you don't want to use the disk-backed message buffer, don't include the diskBackedMessageBufferSettings
property in your Broker resource. This is also the default behavior.
Persistence
It's important to understand that the disk-backed message buffer feature isn't synonymous with persistence. In this context, persistence refers to data that survives across pod restarts. However, this feature provides temporary storage space for data to be saved to disk, preventing memory overflows and data loss during pod restarts.