Configure Language Understanding Docker containers
Important
LUIS will be retired on October 1st 2025 and starting April 1st 2023 you will not be able to create new LUIS resources. We recommend migrating your LUIS applications to conversational language understanding to benefit from continued product support and multilingual capabilities.
The Language Understanding (LUIS) container runtime environment is configured using the docker run
command arguments. LUIS has several required settings, along with a few optional settings. Several examples of the command are available. The container-specific settings are the input mount settings and the billing settings.
Configuration settings
This container has the following configuration settings:
Required | Setting | Purpose |
---|---|---|
Yes | ApiKey | Used to track billing information. |
No | ApplicationInsights | Allows you to add Azure Application Insights telemetry support to your container. |
Yes | Billing | Specifies the endpoint URI of the service resource on Azure. |
Yes | Eula | Indicates that you've accepted the license for the container. |
No | Fluentd | Write log and, optionally, metric data to a Fluentd server. |
No | Http Proxy | Configure an HTTP proxy for making outbound requests. |
No | Logging | Provides ASP.NET Core logging support for your container. |
Yes | Mounts | Read and write data from host computer to container and from container back to host computer. |
Important
The ApiKey
, Billing
, and Eula
settings are used together, and you must provide valid values for all three of them; otherwise your container won't start. For more information about using these configuration settings to instantiate a container, see Billing.
ApiKey setting
The ApiKey
setting specifies the Azure resource key used to track billing information for the container. You must specify a value for the ApiKey and the value must be a valid key for the Azure AI services resource specified for the Billing
configuration setting.
This setting can be found in the following places:
- Azure portal: Azure AI services Resource Management, under Keys
- LUIS portal: Keys and Endpoint settings page.
Do not use the starter key or the authoring key.
ApplicationInsights setting
The ApplicationInsights
setting allows you to add Azure Application Insights telemetry support to your container. Application Insights provides in-depth monitoring of your container. You can easily monitor your container for availability, performance, and usage. You can also quickly identify and diagnose errors in your container.
The following table describes the configuration settings supported under the ApplicationInsights
section.
Required | Name | Data type | Description |
---|---|---|---|
No | InstrumentationKey |
String | The instrumentation key of the Application Insights instance to which telemetry data for the container is sent. For more information, see Application Insights for ASP.NET Core. Example: InstrumentationKey=123456789 |
Billing setting
The Billing
setting specifies the endpoint URI of the Azure AI services resource on Azure used to meter billing information for the container. You must specify a value for this configuration setting, and the value must be a valid endpoint URI for an Azure AI services resource on Azure. The container reports usage about every 10 to 15 minutes.
This setting can be found in the following places:
- Azure portal: Azure AI services Overview, labeled
Endpoint
- LUIS portal: Keys and Endpoint settings page, as part of the endpoint URI.
Required | Name | Data type | Description |
---|---|---|---|
Yes | Billing |
string | Billing endpoint URI. For more information on obtaining the billing URI, see gather required parameters. For more information and a complete list of regional endpoints, see Custom subdomain names for Azure AI services. |
Eula setting
The Eula
setting indicates that you've accepted the license for the container. You must specify a value for this configuration setting, and the value must be set to accept
.
Required | Name | Data type | Description |
---|---|---|---|
Yes | Eula |
String | License acceptance Example: Eula=accept |
Azure AI services containers are licensed under your agreement governing your use of Azure. If you do not have an existing agreement governing your use of Azure, you agree that your agreement governing use of Azure is the Microsoft Online Subscription Agreement, which incorporates the Online Services Terms. For previews, you also agree to the Supplemental Terms of Use for Microsoft Azure Previews. By using the container you agree to these terms.
Fluentd settings
Fluentd is an open-source data collector for unified logging. The Fluentd
settings manage the container's connection to a Fluentd server. The container includes a Fluentd logging provider, which allows your container to write logs and, optionally, metric data to a Fluentd server.
The following table describes the configuration settings supported under the Fluentd
section.
Name | Data type | Description |
---|---|---|
Host |
String | The IP address or DNS host name of the Fluentd server. |
Port |
Integer | The port of the Fluentd server. The default value is 24224. |
HeartbeatMs |
Integer | The heartbeat interval, in milliseconds. If no event traffic has been sent before this interval expires, a heartbeat is sent to the Fluentd server. The default value is 60000 milliseconds (1 minute). |
SendBufferSize |
Integer | The network buffer space, in bytes, allocated for send operations. The default value is 32768 bytes (32 kilobytes). |
TlsConnectionEstablishmentTimeoutMs |
Integer | The timeout, in milliseconds, to establish a SSL/TLS connection with the Fluentd server. The default value is 10000 milliseconds (10 seconds). If UseTLS is set to false, this value is ignored. |
UseTLS |
Boolean | Indicates whether the container should use SSL/TLS for communicating with the Fluentd server. The default value is false. |
HTTP proxy credentials settings
If you need to configure an HTTP proxy for making outbound requests, use these two arguments:
Name | Data type | Description |
---|---|---|
HTTP_PROXY | string | The proxy to use, for example, http://proxy:8888 <proxy-url> |
HTTP_PROXY_CREDS | string | Any credentials needed to authenticate against the proxy, for example, username:password . This value must be in lower-case. |
<proxy-user> |
string | The user for the proxy. |
<proxy-password> |
string | The password associated with <proxy-user> for the proxy. |
docker run --rm -it -p 5000:5000 \
--memory 2g --cpus 1 \
--mount type=bind,src=/home/azureuser/output,target=/output \
<registry-location>/<image-name> \
Eula=accept \
Billing=<endpoint> \
ApiKey=<api-key> \
HTTP_PROXY=<proxy-url> \
HTTP_PROXY_CREDS=<proxy-user>:<proxy-password> \
Logging settings
The Logging
settings manage ASP.NET Core logging support for your container. You can use the same configuration settings and values for your container that you use for an ASP.NET Core application.
The following logging providers are supported by the container:
Provider | Purpose |
---|---|
Console | The ASP.NET Core Console logging provider. All of the ASP.NET Core configuration settings and default values for this logging provider are supported. |
Debug | The ASP.NET Core Debug logging provider. All of the ASP.NET Core configuration settings and default values for this logging provider are supported. |
Disk | The JSON logging provider. This logging provider writes log data to the output mount. |
This container command stores logging information in the JSON format to the output mount:
docker run --rm -it -p 5000:5000 \
--memory 2g --cpus 1 \
--mount type=bind,src=/home/azureuser/output,target=/output \
<registry-location>/<image-name> \
Eula=accept \
Billing=<endpoint> \
ApiKey=<api-key> \
Logging:Disk:Format=json \
Mounts:Output=/output
This container command shows debugging information, prefixed with dbug
, while the container is running:
docker run --rm -it -p 5000:5000 \
--memory 2g --cpus 1 \
<registry-location>/<image-name> \
Eula=accept \
Billing=<endpoint> \
ApiKey=<api-key> \
Logging:Console:LogLevel:Default=Debug
Disk logging
The Disk
logging provider supports the following configuration settings:
Name | Data type | Description |
---|---|---|
Format |
String | The output format for log files. Note: This value must be set to json to enable the logging provider. If this value is specified without also specifying an output mount while instantiating a container, an error occurs. |
MaxFileSize |
Integer | The maximum size, in megabytes (MB), of a log file. When the size of the current log file meets or exceeds this value, a new log file is started by the logging provider. If -1 is specified, the size of the log file is limited only by the maximum file size, if any, for the output mount. The default value is 1. |
For more information about configuring ASP.NET Core logging support, see Settings file configuration.
Mount settings
Use bind mounts to read and write data to and from the container. You can specify an input mount or output mount by specifying the --mount
option in the docker run command.
The LUIS container doesn't use input or output mounts to store training or service data.
The exact syntax of the host mount location varies depending on the host operating system. Additionally, the host computer's mount location may not be accessible due to a conflict between permissions used by the docker service account and the host mount location permissions.
The following table describes the settings supported.
Required | Name | Data type | Description |
---|---|---|---|
Yes | Input |
String | The target of the input mount. The default value is /input . This is the location of the LUIS package files. Example: --mount type=bind,src=c:\input,target=/input |
No | Output |
String | The target of the output mount. The default value is /output . This is the location of the logs. This includes LUIS query logs and container logs. Example: --mount type=bind,src=c:\output,target=/output |
Example docker run commands
The following examples use the configuration settings to illustrate how to write and use docker run
commands. Once running, the container continues to run until you stop it.
- These examples use the directory off the
C:
drive to avoid any permission conflicts on Windows. If you need to use a specific directory as the input directory, you may need to grant the docker service permission. - Do not change the order of the arguments unless you are very familiar with docker containers.
- If you are using a different operating system, use the correct console/terminal, folder syntax for mounts, and line continuation character for your system. These examples assume a Windows console with a line continuation character
^
. Because the container is a Linux operating system, the target mount uses a Linux-style folder syntax.
Replace {argument_name} with your own values:
Placeholder | Value | Format or example |
---|---|---|
{API_KEY} | The endpoint key of the LUIS resource on the Azure LUIS Keys page. |
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx |
{ENDPOINT_URI} | The billing endpoint value is available on the Azure LUIS Overview page. |
See gather required parameters for explicit examples. |
Note
New resources created after July 1, 2019, will use custom subdomain names. For more information and a complete list of regional endpoints, see Custom subdomain names for Azure AI services.
Important
The Eula
, Billing
, and ApiKey
options must be specified to run the container; otherwise, the container won't start. For more information, see Billing.
The ApiKey value is the Key from the Keys and Endpoints page in the LUIS portal and is also available on the Azure Azure AI services
resource keys page.
Basic example
The following example has the fewest arguments possible to run the container:
docker run --rm -it -p 5000:5000 --memory 4g --cpus 2 ^
--mount type=bind,src=c:\input,target=/input ^
--mount type=bind,src=c:\output,target=/output ^
mcr.microsoft.com/azure-cognitive-services/luis:latest ^
Eula=accept ^
Billing={ENDPOINT_URL} ^
ApiKey={API_KEY}
ApplicationInsights example
The following example sets the ApplicationInsights argument to send telemetry to Application Insights while the container is running:
docker run --rm -it -p 5000:5000 --memory 6g --cpus 2 ^
--mount type=bind,src=c:\input,target=/input ^
--mount type=bind,src=c:\output,target=/output ^
mcr.microsoft.com/azure-cognitive-services/luis:latest ^
Eula=accept ^
Billing={ENDPOINT_URL} ^
ApiKey={API_KEY} ^
InstrumentationKey={INSTRUMENTATION_KEY}
Logging example
The following command sets the logging level, Logging:Console:LogLevel
, to configure the logging level to Information
.
docker run --rm -it -p 5000:5000 --memory 6g --cpus 2 ^
--mount type=bind,src=c:\input,target=/input ^
--mount type=bind,src=c:\output,target=/output ^
mcr.microsoft.com/azure-cognitive-services/luis:latest ^
Eula=accept ^
Billing={ENDPOINT_URL} ^
ApiKey={API_KEY} ^
Logging:Console:LogLevel:Default=Information
Next steps
- Review How to install and run containers
- Refer to Troubleshooting to resolve issues related to LUIS functionality.
- Use more Azure AI containers