agentofreality

The project was announced through standard Microsoft channels by Mark Russinovich and is part of the Microsoft Collaboration on GitHub. But we are predominantly an open source project from the Azure Incubations team which has a history of releasing open source projects. So we don't feel the need to constantly remind everybody that we are a Microsoft project and team.

The documentation site is missing some content that wasn't ready in time for the release but it includes AKS install instructions as well as additional Source and Reaction docs. These will be out soon.

If you know that customer that uses EKS and Cosmos Gremlin, please let us know, we would also be over the moon.

People often use CDC to replicate, consolidate, filter, and transform data. And sometimes they use it as a source of change events to build components/services that look for specific data changes and do something when they detect those changes. This kind of components/services tend to be more complex to build, operate, and maintain than expected. Especially if they bring together data from multiple sources, have complex criteria, need to react in near real-time, be secure, and resilient. Most people that have had to build these can probably agree that they would like it to be less complex.

Drasi was created so people don't have to build this kind of component/service. They just write a Continuous Query (in Cypher), and then configure it to connect to supported Data Sources and Reactions (which do something when changes are detected).

Drasi manages the connection to the Source systems to get the low-level changes when they occur (sometimes using the Debezium library), maintains a perpetually accurate result set for the Continuous Query, and every time a source change results in a change to the Continuous Query result, Drasi generates a diff and sends it to the set of subscribed Reactions. The Reactions do something with those diffs depending on their purpose e.g. update a database, post an event, send an email, send a text message. All of this with no code in a platform that can scale to support many such queries.

There is more to it, but a good starting point is if you ever think to yourself that you want to query a database and then compare the results to a previous query result, and you want to do this periodically, you might consider Drasi as an alternative.

In the coming weeks we will get more of our Sources and Reactions documented as well as docs on how to create custom Sources and Reactions. In the short term, if people have Sources and Reactions they want so they can integrate with a wider range of up and downstream systems, we would love to help support their efforts in developing these.

The main current dependency is having a K8s cluster.