addign release note

website/docs/docs/dbt-versions/release-notes.md

@@ -20,6 +20,7 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
 
 ## October 2024
 
+- **Enhancement**: In dbt Cloud versionless and Core 1.9, we now infer a model's `primary_key` based on configured data tests and/or constraints within `manifest.json`. The inferred `primary_key`is visible in dbt Explorer.  Read about the [order dbt infers columns can be used as primary key of a model](https://github.com/dbt-labs/dbt-core/blob/7940ad5c7858ff11ef100260a372f2f06a86e71f/core/dbt/contracts/graph/nodes.py#L534-L541). 
 - **Enhancement**: In dbt Cloud Versionless, snapshots defined in SQL files can now use `config` defined in `schema.yml` YAML files. This update resolves the previous limitation that required snapshot properties to be defined exclusively in `dbt_project.yml` and/or a `config()` block within the SQL file. This enhancement will be included in the upcoming dbt Core v1.9 release.
 - **New:** dbt Explorer now includes trust signal icons, which is currently available as a [Preview](/docs/dbt-versions/product-lifecycles#dbt-cloud). Trust signals offer a quick, at-a-glance view of data health when browsing your dbt models in Explorer. These icons indicate whether a model is **Healthy**, **Caution**, **Degraded**, or **Unknown**. For accurate health data, ensure the resource is up-to-date and has had a recent job run. Refer to [Trust signals](/docs/collaborate/explore-projects#trust-signals-for-resources) for more information. 
 - **New:** Auto exposures are now available in Preview in dbt Cloud. Auto-exposures helps users understand how their models are used in downstream analytics tools to inform investments and reduce incidents. It imports and auto-generates exposures based on Tableau dashboards, with user-defined curation. To learn more, refer to [Auto exposures](/docs/collaborate/auto-exposures).