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We are excited to announce the public preview of Kafka Input and Output with Azure Stream Analytics! A couple of months ago, we shared with the data community our initiative to build a low-code feature that allows customers to connect directly to their Kafka clusters. Our previous announcement is here: Private Preview of Kafka Input and Output with Azure Stream Analytics - Microsoft Community Hub.
Since then, we have made a couple of updates to ensure we offer the best experience to our customers.
Improved Debugging:
A main pain point of using Kafka is the steep learning curve. We have updated the Kafka connector to offer customers a richer debugging experience. Configure your job and validate the correctness of your parameters by running a connection test. Azure Stream Analytics confirms a successful connection and a more detailed error message if there is a mishap, allowing you to troubleshoot effectively.
Connect to Confluent Cloud:
A typical scenario we noted when we announced the feature is that customers wanted to connect to Confluent Cloud Kafka clusters and replicate data into Azure. Customers can seamlessly connect to Confluent Cloud Kafka using the API Key associated with their Kafka topic. You can learn more by visiting our documentation on configuring Azure Stream Analytics with Confluent Cloud:
Connect to Kafka On-Prem:
Coupled with using a virtual network, customers can securely build connections to their on-premises Kafka clusters by using private links. Azure Stream Analytics makes replicating data to the cloud a seamless experience with the Kafka connectors. Azure Stream Analytics is a job service, so you do not have to spend time managing clusters, and downtime concerns are alleviated with a 99.99% SLA (Service Level Agreement) at the job level. To learn more about using a virtual network with Azure Stream Analytics, visit the documentation:
Limitation:
The minimum version of Kafka that you can configure Azure Stream Analytics to connect to is version 0.10.
Conclusion:
Using Azure Stream Analytics to connect to your Kafka clusters, whether hosted on-prem or in the cloud, provides a low-code means to stream your data without needing user-hosted code while meeting business compliance standards. Azure Stream Analytics meets security and business compliance requirements for mission-critical workloads.
Visit the public documentation for using Azure Stream Analytics with Kafka to learn more:
Feedback:
For direct assistance with using Kafka with Azure Stream Analytics, please email askasa@microsoft.com.
Continue reading...
Since then, we have made a couple of updates to ensure we offer the best experience to our customers.
Improved Debugging:
A main pain point of using Kafka is the steep learning curve. We have updated the Kafka connector to offer customers a richer debugging experience. Configure your job and validate the correctness of your parameters by running a connection test. Azure Stream Analytics confirms a successful connection and a more detailed error message if there is a mishap, allowing you to troubleshoot effectively.
Connect to Confluent Cloud:
A typical scenario we noted when we announced the feature is that customers wanted to connect to Confluent Cloud Kafka clusters and replicate data into Azure. Customers can seamlessly connect to Confluent Cloud Kafka using the API Key associated with their Kafka topic. You can learn more by visiting our documentation on configuring Azure Stream Analytics with Confluent Cloud:
- Stream data from Confluent Cloud Kafka with Azure Stream Analytics
- Stream data from Azure Stream Analytics into Confluent Cloud
Connect to Kafka On-Prem:
Coupled with using a virtual network, customers can securely build connections to their on-premises Kafka clusters by using private links. Azure Stream Analytics makes replicating data to the cloud a seamless experience with the Kafka connectors. Azure Stream Analytics is a job service, so you do not have to spend time managing clusters, and downtime concerns are alleviated with a 99.99% SLA (Service Level Agreement) at the job level. To learn more about using a virtual network with Azure Stream Analytics, visit the documentation:
Limitation:
The minimum version of Kafka that you can configure Azure Stream Analytics to connect to is version 0.10.
Conclusion:
Using Azure Stream Analytics to connect to your Kafka clusters, whether hosted on-prem or in the cloud, provides a low-code means to stream your data without needing user-hosted code while meeting business compliance standards. Azure Stream Analytics meets security and business compliance requirements for mission-critical workloads.
Visit the public documentation for using Azure Stream Analytics with Kafka to learn more:
Feedback:
For direct assistance with using Kafka with Azure Stream Analytics, please email askasa@microsoft.com.
Continue reading...