Atlas Stream Processing Adds AWS Regions, VPC Peering, & More!

Since announcing the general availability of Atlas Stream Processing—MongoDB’s native stream processing solution—it’s been exciting to see development teams across technology, retail, and manufacturing begin to run production stream processing workloads critical to their businesses.

Today, we’re announcing four key updates to Atlas Stream Processing.

Support for AWS Regions across the US, Europe, and APAC

First, we’re thrilled to announce that Atlas Stream Processing now supports eight new AWS regions. This expansion enhances deployment flexibility across the US, Europe, and APAC. Adding these new AWS regions broadens our reach and opens up a world of possibilities for users. We’re committed to further expanding our reach by adding more regions and cloud providers in the future.

Newly supported regions launched today include:

Adding these new AWS regions for Atlas Stream Processing is the latest example of the close partnership between MongoDB and AWS. For example, over the past year, MongoDB announced integrations with Amazon Bedrock and Amazon Q Developer; MongoDB was named an AWS Generative AI Competency Partner; we launched the MongoDB AI Applications Program—which helps customers rapidly build AI applications—with AWS and other tech leaders; and MongoDB was named the AWS Technology Partner of the Year at the AWS Partner Summit Taiwan.

Support for VPC peering

Next, Atlas Stream Processing now supports VPC peering for self-hosted Apache Kafka on AWS and Amazon Managed Streaming for Apache Kafka (AWS MSK).

VPC peering is a secure method for connecting between virtual private clouds. As stream processing solutions like Atlas Stream Processing inherently connect to external data sources outside of MongoDB, the ability to make these connections as if your resources are on the same private network is a critical security requirement for many organizations.

Users can select from any VPC peer configured within an Atlas project when setting up Kafka connections. Because peering is at the stream processing connection level, developers can configure Atlas Stream Processing to consume events from one Kafka cluster and produce them to another in a different VPC. Note that this feature has an additional cost. You can learn more in our documentation.

Expanded support for Apache Kafka

Third, we’re expanding capabilities for Apache Kafka in this release. Kafka is one of two key data sources Atlas Stream Processing supports today. One of Kafka’s strengths is its flexibility, allowing developers to customize configurations to suit various use cases, including those that rely on continuous stream processing.

That flexibility can also create complexity, but Atlas Stream Processing focuses on making Kafka’s critical features easily accessible using the MongoDB Query API.

By adding support for Kafka keys, developers can now read and write Kafka keys on their events, which enables filtering, partitioning, and aggregating based on key values. This ability provides greater control over routing processed data and is powerful for many stream processing use cases.

Expanded Atlas Admin API support

Lastly, we have added support for creating and deleting stream processors, as well as fetching operational stats of stream processors using the Atlas Admin API. Developers relying on the Admin API as a primary interface for interacting with Atlas will find this a welcome addition for managing their stream processors. Learn more in the documentation.

With these new capabilities—additional AWS region support, VPC peering, the ability to use Kafka keys, and improved stream processing support for the Atlas Admin API—we’ve made it easier than ever for developers to integrate stream processing into their applications. We’re excited to see the innovative ways you’ll use these features.

Source: Read More