Nurturing Innovation: Our Approach to Feature Deployment from Open-Source Milvus to Zilliz Cloud
Authored by James Luan, VP of Engineering at Zilliz
At Zilliz, our commitment to innovation and community collaboration is at the core of our mission. Milvus, our open-source project, reflects this dedication. As developers, we chose to open source Milvus because it is vital to have the freedom to try out software to see if it does what we need it to do for our development efforts. Even within Milvus, we purposely chose to use several open-source projects (NATS, Kafka, Minio, etc) and, where possible, contribute back to those projects.
As I write this, I recall Richard Stallman, the founder of the free Unix-style operating system GNU and a prominent advocate in the open-source movement, emphasizing the four essential freedoms of open source:
The freedom to run the program as they want to, for any purpose.
The freedom to study how the program works and change it so it does what you want. Must have access to the source code.
The freedom to redistribute – to help your neighbor.
The freedom to redistribute copies of modified versions. By doing this, you can give the whole community a chance to benefit from your changes. Access to the source code is a precondition for this.
These freedoms are important and are the underlying belief that allow us to strive to deliver features rapidly, ensuring the community benefits from the latest advancements in vector database technology.
However, our commitment to excellence extends beyond speed. Transitioning features from Milvus to Zilliz Cloud involves a meticulous process guided by three fundamental principles:
1. Iteration with Precision:
We believe in iterating quickly to align our developments with the community's needs. Sometimes, Milvus serves as a testing ground, allowing us to receive valuable feedback and make informed decisions.
2. Testing the Waters:
Occasionally, features that are not yet deemed production-ready might land in Milvus. These features, though not finalized, are ready for testing and feedback. We value the insights from the community in refining these elements. This practice has helped us to make improvements on features and even abandon some features all together.
3. Quality Over Speed:
Our commitment to excellence means we do not compromise on quality. Before migrating features to Zilliz Cloud, we ensure they meet robust standards. With this commitment, sometimes we find ourselves in a spot where there may be a few months where the features in Milvus have yet to be deployed in Zilliz Cloud, which can disappoint our customers. We understand the importance of a seamless experience and are dedicated to minimizing gaps between Milvus releases and their deployment in Zilliz Cloud.
We strive to streamline the transition from Milvus to Zilliz Cloud efficiently, promptly providing our users with cutting-edge features. However, we must highlight that we achieve this without compromising the quality assurance necessary for a robust, reliable platform. We commit to communicating any distinctions between Milvus and Zilliz Cloud through our documentation, blogs, and Discord channels. While we'll do our best to cover all aspects, we acknowledge that oversight may occur, and we encourage the community to bring it to our attention so that we can address it promptly.
We appreciate the collaboration with our community, and your feedback is instrumental in shaping the future of Milvus and Zilliz Cloud. Together, we're building something extraordinary.
Thank you for being a part of our journey.
James LuanJames Luan is the VP of Engineering at Zilliz. With a master's degree in computer engineering from Cornell University, he has extensive experience as a Database Engineer at Oracle, Hedvig, and Alibaba Cloud. James played a crucial role in developing HBase, Alibaba Cloud's open-source database, and Lindorm, a self-developed NoSQL database. He is also a respected member of the Technical Advisory Committee of LF AI & Data Foundation, contributing his expertise to shaping the future of AI and data technologies.
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