DataGalaxy is a Data & AI governance platform built for the speed of modern business. It helps organizations align strategy, technology, and execution to drive data-driven success. Learn more: https://www.datagalaxy.com/en/
This article is a reprint of the original article found on the CNCF website here, as written by the DataGalaxy team.

Challenge

Our organization was facing significant challenges with our existing legacy codebase. Over time, the code had become increasingly difficult to maintain, hindering our ability to deliver value to clients. We needed a fresh start with a modernized, structured approach that would enable us to scale seamlessly. To address this, we decided to migrate our project to a modular monolith architecture, allowing us to maintain consistency while enabling gradual evolution toward a more service-oriented model.

Beyond the architectural overhaul, we also sought to enhance our analytics capabilities. Our existing tracking mechanisms were insufficient to provide valuable insights into feature usage and platform state. Without a reliable way to collect, store, and analyze data efficiently, decision-making was often based on incomplete or outdated information. We needed a more dynamic and event-driven approach to analytics.

Finally, we aimed to introduce trustworthy AI-powered features. To boost adoption and automate data governance, our platform required AI-driven automation such as intelligent content generation and translation. But integrating AI in a scalable and fault-tolerant manner was a challenge. Ensuring reliability while minimizing disruptions was key to making AI a core component of our platform.

Solution

To tackle these challenges, we leveraged Dapr’s powerful capabilities, particularly Pub/Sub and Service-to-Service invocation. By incorporating Dapr, we streamlined the transition from our legacy system to a modern modular monolith. Dapr abstracted away the complexity of building resilient and scalable services, allowing our developers to focus on business logic rather than infrastructure concerns. This drastically reduced the effort needed to implement robust communication patterns, making our migration smoother and more efficient.

For analytics, we adopted an event-driven approach powered by Dapr’s Pub/Sub. We now publish structured JSON event payloads into our data lake, where our data team can easily consume and process them. This has empowered us to generate in-depth analytics dashboards, providing real-time insights into platform usage and user behavior. The ease of integration and scalability of this solution has transformed how we monitor and optimize our product.

Incorporating AI into our platform was also made seamless with Dapr. We use Pub/Sub to send data requiring AI processing – such as translation tasks or content generation – to our central AI cluster. The platform then return results asynchronously, ensuring fault tolerance and resiliency. This approach has allowed us to integrate AI-driven features without compromising system stability or performance, making AI a reliable and scalable component of our offering.

Impact

Being a leader in data governance and dealing with millions and millions of metadata objects, DataGalaxy needed a trustful solution for the scale up in analytics and AI – as these capacities begin to be the drivers of user adoption and data governance support.

By adopting a standardized modular monolith architecture with Dapr, our development teams have experienced a significant boost in productivity. Developers can now focus on feature development without being bogged down by legacy constraints. The streamlined architecture has improved maintainability, making it easier to onboard new team members and accelerate development cycles.

The shift to event-driven analytics has provided us with deeper insights into platform usage. With more precise feature tracking, we can make data-driven decisions that align with market trends and user needs. This has allowed us to continuously refine and optimize our platform, ensuring we stay competitive in an ever-evolving industry.

Finally, integrating AI through resilient asynchronous communication has enhanced our platform’s capabilities while reducing operational risks. AI-driven automation has improved efficiency and reliability, allowing us to deliver smarter and more automated features. As a result, our platform is now better positioned in the market, offering cutting-edge AI capabilities while maintaining high availability and stability.

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For more technical insights into the DataGalaxy implementation of Dapr, check out the full write up on the CNCF site.