Update reference-yaml-deployment-managed-online.md

Improve note for max_concurrent_requests

Author: aishanibhalla

articles/machine-learning/reference-yaml-deployment-managed-online.md

@@ -53,7 +53,7 @@ The source JSON schema can be found at https://azuremlschemas.azureedge.net/late
 | Key | Type | Description | Default value |
 | --- | ---- | ----------- | ------------- |
 | `request_timeout_ms` | integer | The scoring timeout in milliseconds. | `5000` |
-| `max_concurrent_requests_per_instance` | integer | The maximum number of concurrent requests per instance allowed for the deployment. <br><br> **Note:** Your model must be configured to handle concurrent requests. To do so, pass `WORKER_COUNT: <int>` as an environment variable. For more information about `WORKER_COUNT`, see [AzureML Inference Server Parameters](how-to-inference-server-http.md#server-parameters) <br><br> **Note:** Set to the number of requests that your model can process concurrently on a single node. Setting this value higher than your model's actual concurrency can lead to higher latencies. Setting this value too low may lead to under utilized nodes. Setting too low may also result in requests being rejected with a 429 HTTP status code, as the system will opt to fail fast. For more information, see [Troubleshooting online endpoints: HTTP status codes](how-to-troubleshoot-online-endpoints.md#http-status-codes). | `1` |
+| `max_concurrent_requests_per_instance` | integer | The maximum number of concurrent requests per instance allowed for the deployment. <br><br> **Note:** If you're using [AzureML Inference Server](how-to-inference-server-http.md) or [AzureML Inference Images](concept-prebuilt-docker-images-inference.md), your model must be configured to handle concurrent requests. To do so, pass `WORKER_COUNT: <int>` as an environment variable. For more information about `WORKER_COUNT`, see [AzureML Inference Server Parameters](how-to-inference-server-http.md#server-parameters) <br><br> **Note:** Set to the number of requests that your model can process concurrently on a single node. Setting this value higher than your model's actual concurrency can lead to higher latencies. Setting this value too low may lead to under utilized nodes. Setting too low may also result in requests being rejected with a 429 HTTP status code, as the system will opt to fail fast. For more information, see [Troubleshooting online endpoints: HTTP status codes](how-to-troubleshoot-online-endpoints.md#http-status-codes). | `1` |
 | `max_queue_wait_ms` | integer | The maximum amount of time in milliseconds a request will stay in the queue. | `500` |
 
 ### ProbeSettings