justinmclean commented on code in PR #92: URL: https://github.com/apache/gravitino-site/pull/92#discussion_r2377279328
########## blog/2025-09-24-gravitino-1-0-0-release-notes.mdx: ########## @@ -0,0 +1,128 @@ +--- +title: Apache Gravitino 1.0.0 - From Metadata Management to Contextual Engineering +slug: gravitino-1-0-0-release-notes +authors: [jerryshao] +tags: [apache,gravitino,metadata,multicloud,model,security,government] +--- + +Apache Gravitino was designed from day one to provide a unified framework for metadata management across heterogeneous sources, regions, and clouds—what we define as the metadata lake (or metalake). Throughout its evolution, Gravitino has extended support to multiple data modalities, including tabular metadata from Apache Hive, Apache Iceberg, MySQL, and PostgreSQL; unstructured assets from HDFS and S3; streaming and messaging metadata from Apache Kafka; and metadata for machine learning models. To further strengthen governance in Gravitino, we have also integrated advanced capabilities, including tagging, audit logging, and end-to-end lineage capture. + +After all enterprise metadata has been centralized through Gravitino, it forms a data brain: a structured, queryable, and semantically enriched representation of data assets. This enables not only consistent metadata access but also contextual reasoning and automation across systems. As we approach the 1.0 milestone, our focus shifts from pure metadata storage to metadata-driven contextual engineering—a foundation we call the Metadata-driven Action System. + +The release of Apache Gravitino 1.0.0 marks a significant engineering step forward, with robust APIs, extensible connectors, enhanced governance primitives, improved scalability and reliability in distributed environments. In the following sections, I will dive into the new features and architectural improvements introduced in Gravitino 1.0.0. + +## Metadata-driven action system + +In 1.0.0, we have introduced 3 new components, with which we can build jobs to accomplish the metadata-driven actions, like table compaction, TTL data management, PII identification, etc. These 3 new components are: statistics system, policy system, and job system. + +Taking table compaction as an example: + +* Firstly, users can define the table compaction policy in Gravitino and associate this policy with the tables that need to be compacted. +* Then, users can save the statistics of the table to Gravitino. +* Also, users can define a job template for the compaction. +* Lastly, users can use the statistics with the defined policy to generate the compaction parameters and use these parameters to trigger a compaction job based on the defined job templates. + +### Statistics system + +The statistics system is a new component for the statistics store and retrieval. You can define and store the table/partition level statistics in Gravitino, and also fetch them through Gravitino for different purposes. +For the details of how we design this component, please see [#7268](https://github.com/apache/gravitino/issues/7268). For how to use the statistics system, you can refer to the documentation [here](https://gravitino.apache.org/docs/1.0.0/manage-statistics-in-gravitino/). + +### Policy system + +The policy system helps you define action rules in Gravitino, like compaction rules or TTL rules. The defined policy can be associated with the entities, which means these rules will be enforced on the dedicated metadata. Users can leverage these enforced polices to decide how to trigger an action on the dedicated metadata. + +Please refer to the policy system [documentation](https://gravitino.apache.org/docs/1.0.0/manage-policies-in-gravitino) to know how to use it. If you want to know more about the implementation details of the policy system, please see [#7139](https://github.com/apache/gravitino/issues/7139). + +### Job system + +The job system is another system for you to submit and run jobs through Gravitino. Users can +register a job template, then trigger a job based on the specific job template. Gravitino will help to submit the job to the dedicated job executor, like Apache Airflow. Gravitino can manage the job lifecycle and save the job status in it. With the job system, users can run a self-defined job to accomplish a metadata-driven action system. + +The job system is still in active development. In 1.0.0, we have an initial version to support running the jobs as a local process. If you want to know more about the design details, you can follow issue [#7154](https://github.com/apache/gravitino/issues/7154). Also, a user-facing documentation can be found [here](https://gravitino.apache.org/docs/1.0.0/manage-jobs-in-gravitino). + +The whole metadata-driven action system is still in an alpha phase for version 1.0.0. The community will continue to evolve the code and take the Iceberg table maintenance as a reference implementation in the next version. Please stay tuned. + +## Agent-ready through the MCP server + +MCP is a powerful protocol to bridge the gap between human languages and machine interfaces. With MCP, users can use natural language to communicate with the LLM, and the LLM can understand the context and invoke the right tools. + +With Gravitino 1.0.0, the community officially delivered the MCP server for Gravitino. Users can launch it as a remote or local MCP server and connect to the different MCP applications, like Cursor and Claude Desktop. Also, we exposed all the metadata-related interfaces as tools, which can be called by MCP clients. + +With the Gravitino MCP server, users can manage and govern the metadata, as well as achieve metadata-driven actions by using natural language. Please follow issue [#7483](https://github.com/apache/gravitino/issues/7483) for more details. Also, you can check the [documentation](https://gravitino.apache.org/docs/1.0.0/gravitino-mcp-server) to know how to start the MCP server locally or in Docker. + +## Unified access control framework + +Gravitino introduced the RBAC system in the previous version, but it only offers users the ability to grant privileges to roles and users, without enforcing access control when manipulating the secure objects. In 1.0.0, we complete this missing piece in Gravitino. + +For now, users can set access control policies through our RBAC system and enforce the control when accessing secure objects. For the details, you can check out the umbrella issue [#6762](https://github.com/apache/gravitino/issues/6762). Review Comment: Suggested change: Currently, users can set access control policies through our RBAC system and enforce these controls when accessing secure objects. For details, you can refer to the umbrella issue [#6762](https://github.com/apache/gravitino/issues/6762). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
