Pipeline: output: azure logs: style

pipeline/outputs/azure_logs_ingestion.md

@@ -1,44 +1,42 @@
 ---
-description: 'Send logs to Azure Log Analytics using Logs Ingestion API with DCE and DCR'
+description: Send logs to Azure Log Analytics using Logs Ingestion API
 ---
 
 # Azure Logs Ingestion API
 
-Azure Logs Ingestion plugin allows you to ingest your records using [Logs Ingestion API in Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/logs-ingestion-api-overview) to supported [Azure tables](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/logs-ingestion-api-overview#supported-tables) or to [custom tables](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/create-custom-table#create-a-custom-table) that you create.
+Azure Logs Ingestion plugin lets you ingest your records using [Logs Ingestion API in Azure Monitor](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/logs-ingestion-api-overview) to supported [Azure tables](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/logs-ingestion-api-overview#supported-tables) or to [custom tables](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/create-custom-table#create-a-custom-table) that you create.
 
 The Logs ingestion API requires the following components:
 
 - A Data Collection Endpoint (DCE)
 - A Data Collection Rule (DCR) and
 - A Log Analytics Workspace
 
-> Note: According to [this document](https://github.com/MicrosoftDocs/azure-docs/blob/main/articles/azure-monitor/logs/logs-ingestion-api-overview.md#components), all resources should be in the same region.
+To visualize the basic logs ingestion operation, see the following image:
 
-To visualize basic Logs Ingestion operation, see the following image:
+![Log ingestion overview](../../.gitbook/assets/azure-logs-ingestion-overview.png)
 
-![](../../.gitbook/assets/azure-logs-ingestion-overview.png)
-
-To get more details about how to set up these components, please refer to the following documentations:
+To get more details about how to set up these components, refer to the following documentation:
 
 - [Azure Logs Ingestion API](https://docs.microsoft.com/en-us/azure/log-analytics/)
 - [Send data to Azure Monitor Logs with Logs ingestion API (setup DCE, DCR and Log Analytics)](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/tutorial-logs-ingestion-portal)
 
-## Configuration Parameters
+## Configuration parameters
 
 | Key           | Description                | Default |
 | :------------ | :------------------------- | :------ |
-| tenant\_id    | _Required_ - The tenant ID of the AAD application. ||
-| client\_id    | _Required_ - The client ID of the AAD application. ||
-| client\_secret| _Required_ - The client secret of the AAD application ([App Secret](https://docs.microsoft.com/en-us/azure/active-directory/develop/howto-create-service-principal-portal#option-2-create-a-new-application-secret)). ||
-| dce\_url      | _Required_ - Data Collection Endpoint(DCE) URL. ||
-| dcr\_id       | _Required_ - Data Collection Rule (DCR) immutable ID (see [this document](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/tutorial-logs-ingestion-portal#collect-information-from-the-dcr) to collect the immutable id) ||
-| table\_name   | _Required_ - The name of the custom log table (include the `_CL` suffix as well if applicable) ||
-| time\_key     | _Optional_ - Specify the key name where the timestamp will be stored. | `@timestamp` |
-| time\_generated | _Optional_ - If enabled, will generate a timestamp and append it to JSON. The key name is set by the 'time_key' parameter. | `true` |
-| compress      | _Optional_ - Enable HTTP payload gzip compression. | `true` |
-| workers | The number of [workers](../../administration/multithreading.md#outputs) to perform flush operations for this output. | `0` |
-
-## Getting Started
+| `tenant_id`    | The tenant ID of the Azure Active Directory (AAD) application. | _none_ |
+| `client_id`    | The client ID of the AAD application. | _none_ |
+| `client_secret`| The client secret of the AAD application ([App Secret](https://docs.microsoft.com/en-us/azure/active-directory/develop/howto-create-service-principal-portal#option-2-create-a-new-application-secret)). | _none_ |
+| `dce_url`      | Data Collection Endpoint(DCE) URL. | _none_ |
+| `dcr_id`       | Data Collection Rule (DCR) [immutable ID](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/tutorial-logs-ingestion-portal#collect-information-from-the-dcr). | _none_ |
+| `table_name`   | The name of the custom log table (include the `_CL` suffix as well if applicable) | _none_ |
+| `time_key`     | Optional. Specify the key name where the timestamp will be stored. | `@timestamp` |
+| `time_generated` | Optional. If enabled, will generate a timestamp and append it to JSON. The key name is set by the `time_key` parameter. | `true` |
+| `compress`      | Optional. Enable HTTP payload gzip compression. | `true` |
+| `workers` | The number of [workers](../../administration/multithreading.md#outputs) to perform flush operations for this output. | `0` |
+
+## Get started
 
 To send records into an Azure Log Analytics using Logs Ingestion API the following resources needs to be created:
 
@@ -47,11 +45,11 @@ To send records into an Azure Log Analytics using Logs Ingestion API the followi
 - Either an [Azure tables](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/logs-ingestion-api-overview#supported-tables) or [custom tables](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/create-custom-table#create-a-custom-table)
 - An app registration with client secrets (for DCR access).
 
-You can follow [this guideline](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/tutorial-logs-ingestion-portal) to set up the DCE, DCR, app registration and a custom table.
+Follow [this guideline](https://learn.microsoft.com/en-us/azure/azure-monitor/logs/tutorial-logs-ingestion-portal) to set up the DCE, DCR, app registration and a custom table.
 
-### Configuration File
+### Configuration file
 
-Use this configuration to quickly get started:
+Use this configuration file to get started:
 
 {% tabs %}
 {% tab title="fluent-bit.yaml" %}
@@ -62,9 +60,9 @@ pipeline:
     - name: tail
       path: /path/to/your/sample.log
       tag: sample
-      key: RawData      
-    
-    # Or use other plugins  
+      key: RawData
+
+    # Or use other plugins
     #- name: cpu
     #  tag: sample
 
@@ -73,12 +71,12 @@ pipeline:
       match: sample
       # Add a json key named "Application":"fb_log"
       add: Application fb_log
-      
+
   outputs:
     # Enable this section to see your json-log format
     #- name: stdout
     #  match: '*'
-    
+
     - name: azure_logs_ingestion
       match: sample
       client_id: XXXXXXXX-xxxx-yyyy-zzzz-xxxxyyyyzzzzxyzz
@@ -135,4 +133,4 @@ pipeline:
 {% endtab %}
 {% endtabs %}
 
-Set up your DCR transformation accordingly based on the json output from fluent-bit's pipeline (input, parser, filter, output).
+Set up your DCR transformation based on the JSON output from the Fluent Bit pipeline (input, parser, filter, output).

vale-styles/FluentBit/Headings.yml

@@ -14,6 +14,7 @@ exceptions:
   - API
   - APIs
   - Azure
+  - Azure Logs Ingestion API
   - BuildKite
   - CircleCI
   - CLI