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Liberating your mainframe data with Confluent and Google Cloud

October 4, 2021
Dustin Shammo

Mainframe Solutions Specialist, Google Cloud

Jeremy Hogan

Cloud Partner Solutions Architect, Confluent

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Are you looking for the best way to migrate and replicate your mainframe data? Google Cloud and Confluent have teamed up to provide an end-to-end solution for connecting your mainframe application data with the advanced analytics capabilities of Google Cloud.

In this article, we will discuss how you can use Confluent Connect to replicate messages from IBM MQ and Db2 to Google Cloud. This allows you to work with your mainframe data in the cloud, and enables you to build new applications and analytical capabilities using Google Cloud’s machine learning solutions. You also benefit by reducing impact on your production mainframe workloads, and reducing general purpose compute costs. In other words, you can continue using your mainframe to run your mission-critical business workloads while setting your data in motion for innovation.

Here’s an example use case that demonstrates how using the Confluent MQ connector with Google Cloud can impact your bottom line. One of our customers is saving millions of dollars per year on mainframe cycles by leveraging z Integrated Information Processor (zIIP) engines for data processing.

Moving these workloads to zIIP, off of GP (general purpose) compute, and away from CHINIT (Channel Initiator) routes directly leads to reduced MSU licensing. As an example, a customer in the financial services industry saw a 50% reduction in CPU usage per message. These cost savings can enable you to direct budget resources toward differentiating activities, such as commercializing your valuable mainframe data to open up new revenue streams and improve customer service.

On the technical side, Confluent guarantees exactly-once message semantics, preserves message order and unleashes that data to be accessed by existing and new applications that need a high throughput, low latency event driven architecture. This means that you can rely on the accuracy and consistency of your data in Google Cloud as if you were querying it directly from your mainframe database.


Once you have this data in your Confluent cluster, you can leverage  the combined capabilities of Confluent and Google Cloud. You can modernize the way your consumers access your data by providing a single, standard source of truth without impacting production services. Confluent integrates directly with Apigee, Google Cloud’s API platform for developing and managing APIs.

Because Confluent integrates with BigQuery, you can also leverage the advanced analytical capabilities of BigQuery ML and Vertex AI to realize value from your latent mainframe data, and build new systems of insight that were not possible on the mainframe. And most of all, you can open up new avenues for innovation by allowing consumers to access the data when they need it, speeding up time to value and enabling faster business decisions.

You now have a bridge to cloud for your mainframe application data. Get started by deploying Confluent from the Google Cloud marketplace.

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