Update stream-analytics-define-kafka-input.md

Author: enkrumah

articles/stream-analytics/stream-analytics-define-kafka-input.md

@@ -1,16 +1,16 @@
 ---
 title: Stream data from Kafka into Azure Stream Analytics
-description: Learn about setting up Azure Stream Analytics as a consumer from kafka
+description: Learn about setting up Azure Stream Analytics as a consumer from Kafka
 author: enkrumah
 ms.author: ebnkruma
 ms.service: stream-analytics
 ms.topic: conceptual
-ms.date: 09/25/2023
+ms.date: 09/26/2023
 ---
 
 # Stream data from Kafka into Azure Stream Analytics (Preview)
 
-Kafka is a distributed streaming platform used to publish and subscribe to streams of records. Kafka is designed to allow your apps to process records as they occur. It is an open-source system developed by the Apache Software Foundation written in Java and Scala. 
+Kafka is a distributed streaming platform used to publish and subscribe to streams of records. Kafka is designed to allow your apps to process records as they occur. It is an open-source system developed by the Apache Software Foundation and written in Java and Scala. 
 
 The following are the major use cases: 
 * Messaging 
@@ -19,41 +19,42 @@ The following are the major use cases:
 * Log Aggregation 
 * Stream Processing 
 
-Azure Stream Analytics allows you to connect directly to kafka clusters to ingest data.The solution is low code and entirely managed by the Azure Stream Analytics team at Microsoft, allowing it to meet business compliance standards. The Kafka Adapters are backward compatible and support all Kafka versions with the latest client release starting from version 0.10. Users can connect to Kafka clusters inside a VNET and Kafka clusters with a public endpoint depending on the configurations. The configuration relies on existing Kafka configuration conventions.
+Azure Stream Analytics lets you connect directly to Kafka clusters to ingest data. The solution is low code and entirely managed by the Azure Stream Analytics team at Microsoft, allowing it to meet business compliance standards. The Kafka Adapters are backward compatible and support all versions with the latest client release starting from version 0.10. Users can connect to Kafka clusters inside a VNET and Kafka clusters with a public endpoint, depending on the configurations. The configuration relies on existing Kafka configuration conventions.
 
 ### Compression
 
-Supported compression types are: None, Gzip, Snappy, LZ4 and Zstd compression.
+Supported compression types are None, Gzip, Snappy, LZ4, and Zstd.
 
 ## Authentication and Encryption
 
 You can use four types of security protocols to connect to your Kafka clusters:
-| Property name  | Description                                                                                                                                                                                                       |
-|----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| mTLS           | encryption and authentication                                                                                                                                                                                     |
-| SASL_SSL       | It combines two different security mechanisms - SASL (Simple Authentication and Security Layer) and SSL (Secure Sockets Layer) - to ensure both authentication and encryption are in place for data transmission. |
-| Kafka topic    | A unit of your Kafka cluster you want to write events to.                                                                                                                                                         |
-| SASL_PLAINTEXT | standard authentication with username and password without encryption                                                                                                                                             |
-| None           | The serialization format (JSON, CSV, Avro, Parquet) of the incoming data stream.                                                                                                                                  |
+
+|Property name   |Description   |
+|----------|-----------|
+|mTLS     |encryption and authentication       |
+|SASL_SSL |It combines two different security mechanisms - SASL (Simple Authentication and Security Layer) and SSL (Secure Sockets Layer) - to ensure both authentication and encryption are in place for data transmission.   |
+|Kafka topic |A unit of your Kafka cluster you want to write events to. |
+|SASL_PLAINTEXT |standard authentication with username and password without encryption |
+|None |The serialization format (JSON, CSV, Avro, Parquet) of the incoming data stream. |
 
 
 > [!IMPORTANT]
-> Confluent Cloud supports authenticating using API Keys, OAuth, or SAML single sign-on (SSO). Azure Stream Analytics do not currently support these authentication options. There will be a update in the near future to supporting authenticating to confluent cloud using API Keys.
+> Confluent Cloud supports authenticating using API Keys, OAuth, or SAML single sign-on (SSO). Azure Stream Analytics does not currently support these authentication options. There will be an update shortly to support authenticating to the confluent cloud using API Keys.
 > 
 
 
 ### Key Vault Integration
 
 > [!NOTE]
-> When using truststore certificates with mTLS or SASL_SSL security protocols, you must have Azure KeyVault and managed identity configured for your Azure Stream Analytics job.
+> When using trust store certificates with mTLS or SASL_SSL security protocols, you must have Azure KeyVault and managed identity configured for your Azure Stream Analytics job.
 >
 
-Azure Stream Analytics integrates seamlessly with Azure Key Vault to access stored secrets needed for authentication and encryption when using mTLS or SASL_SSL security protocols. Your Azure Stream Analytics job connects to Azure Key Vault using managed identity to ensure secure connection and avoid exfiltration of secrets.
+Azure Stream Analytics integrates seamlessly with Azure Key Vault to access stored secrets needed for authentication and encryption when using mTLS or SASL_SSL security protocols. Your Azure Stream Analytics job connects to Azure Key Vault using managed identity to ensure a secure connection and avoid the exfiltration of secrets.
 
-You can store the certificates as Key Vault certificate or Key Vault secret. Private keys are in PEM format.
+You can store the certificates as Key Vault certificates or Key Vault secrets. Private keys are in PEM format.
 
 ### Key Vault Integration
-When configuring your Azure Stream Analytics job to connect to your Kafka clusters, depending on your configuration, you may have to configure your job to be able to access your Kafka clusters which are behind a firewall or inside a virtual network. Please visit the Azure Stream Analytics VNET documentation to learn more about configuring private endpoints to access resources which are inside a virtual network or behind a firewall.
+When configuring your Azure Stream Analytics job to connect to your Kafka clusters, depending on your configuration, you may have to configure your job to access your Kafka clusters, which are behind a firewall or inside a virtual network. You can visit the Azure Stream Analytics VNET documentation to learn more about configuring private endpoints to access resources inside a virtual network or behind a firewall.
 
 
 ### Configuration
@@ -62,18 +63,20 @@ The following table lists the property names and their description for creating
 | Property name                | Description                                                                                                             |
 |------------------------------|-------------------------------------------------------------------------------------------------------------------------|
 | Input/Output Alias            | A friendly name used in queries to reference your input or output                                                       |
-| Bootstrap server addresses   | A list of host/port pairs to use for establishing the connection to the Kafka cluster.                                  |
+| Bootstrap server addresses   | A list of host/port pairs to establish the connection to the Kafka cluster.                                  |
 | Kafka topic                  | A unit of your Kafka cluster you want to write events to.                                                               |
-| Security Protocol            | How you want to connect to your Kafka cluster. Azure Stream Analytics supports: mTLS, SASL_SSL, SASL_PLAINTEXT or None. |
+| Security Protocol            | How you want to connect to your Kafka cluster. Azure Stream Analytics supports mTLS, SASL_SSL, SASL_PLAINTEXT or None. |
 | Event Serialization format   | The serialization format (JSON, CSV, Avro, Parquet, Protobuf) of the incoming data stream.                              |
 
+
+
 ### Limitations
-* When configuring your Azure Stream Analytics jobs to use VNET/SWIFT, your job must be configured with a minimum of six (6) streaming units. 
+* When configuring your Azure Stream Analytics jobs to use VNET/SWIFT, your job must be configured with at least six (6) streaming units. 
 * When using mTLS or SASL_SSL with Azure Key Vault, you must convert your Java Key Store to PEM format. 
 * The minimum version of Kafka you can configure Azure Stream Analytics to connect to is version 0.10.
 
 > [!NOTE]
-> For direct on using the Azure Stream Analytics kafka adapter, please reach out to [[email protected]](mailto:[email protected]).
+> For direct help with using the Azure Stream Analytics Kafka adapter, please reach out to [[email protected]](mailto:[email protected]).
 >