diff --git a/website/docs/docs/cloud/connect-data-platform/about-connections.md b/website/docs/docs/cloud/connect-data-platform/about-connections.md
index 6f2f140b724..89dd13808ec 100644
--- a/website/docs/docs/cloud/connect-data-platform/about-connections.md
+++ b/website/docs/docs/cloud/connect-data-platform/about-connections.md
@@ -20,9 +20,12 @@ dbt Cloud can connect with a variety of data platform providers including:
- [Starburst or Trino](/docs/cloud/connect-data-platform/connect-starburst-trino)
- [Teradata](/docs/cloud/connect-data-platform/connect-teradata)
-You can connect to your database in dbt Cloud by clicking the gear in the top right and selecting **Account Settings**. From the Account Settings page, click **+ New Project**.
+To connect to your database in dbt Cloud:
-
+1. Click your account name at the bottom of the left-side menu and click **Account settings**
+2. Select **Projects** from the top left, and from there click **New Project**
+
+
These connection instructions provide the basic fields required for configuring a data platform connection in dbt Cloud. For more detailed guides, which include demo project data, read our [Quickstart guides](https://docs.getdbt.com/guides)
@@ -41,7 +44,7 @@ Connections created with APIs before this change cannot be accessed with the [la
Warehouse connections are an account-level resource. As such you can find them under **Accounts Settings** > **Connections**:
-
+
Warehouse connections can be re-used across projects. If multiple projects all connect to the same warehouse, you should re-use the same connection to streamline your management operations. Connections are assigned to a project via an [environment](/docs/dbt-cloud-environments).
diff --git a/website/docs/docs/cloud/connect-data-platform/connect-amazon-athena.md b/website/docs/docs/cloud/connect-data-platform/connect-amazon-athena.md
index 0b2f844ccac..f1009f61274 100644
--- a/website/docs/docs/cloud/connect-data-platform/connect-amazon-athena.md
+++ b/website/docs/docs/cloud/connect-data-platform/connect-amazon-athena.md
@@ -5,7 +5,7 @@ description: "Configure the Amazon Athena data platform connection in dbt Cloud.
sidebar_label: "Connect Amazon Athena"
---
-# Connect Amazon Athena
+# Connect Amazon Athena
Your environment(s) must be on ["Versionless"](/docs/dbt-versions/versionless-cloud) to use the Amazon Athena connection.
diff --git a/website/docs/docs/cloud/git/authenticate-azure.md b/website/docs/docs/cloud/git/authenticate-azure.md
index 42028bf993b..5278c134f72 100644
--- a/website/docs/docs/cloud/git/authenticate-azure.md
+++ b/website/docs/docs/cloud/git/authenticate-azure.md
@@ -13,9 +13,9 @@ If you use the dbt Cloud IDE or dbt Cloud CLI to collaborate on your team's Azur
Connect your dbt Cloud profile to Azure DevOps using OAuth:
-1. Click the gear icon at the top right and select **Profile settings**.
-2. Click **Linked Accounts**.
-3. Next to Azure DevOps, click **Link**.
+1. Click your account name at the bottom of the left-side menu and click **Account settings**
+2. Scroll down to **Your profile** and select **Personal profile**.
+3. Go to the **Linked accounts** section in the middle of the page.
4. Once you're redirected to Azure DevOps, sign into your account.
diff --git a/website/docs/docs/collaborate/project-recommendations.md b/website/docs/docs/collaborate/project-recommendations.md
index 12007c6b88b..c9499579e54 100644
--- a/website/docs/docs/collaborate/project-recommendations.md
+++ b/website/docs/docs/collaborate/project-recommendations.md
@@ -20,7 +20,7 @@ The Recommendations overview page includes two top-level metrics measuring the t
- **Model test coverage** — The percent of models in your project (models not from a package or imported via dbt Mesh) with at least one dbt test configured on them.
- **Model documentation coverage** — The percent of models in your project (models not from a package or imported via dbt Mesh) with a description.
-
+
## List of rules
The following table lists the rules currently defined in the `dbt_project_evaluator` [package](https://hub.getdbt.com/dbt-labs/dbt_project_evaluator/latest/).
diff --git a/website/docs/docs/dbt-versions/release-notes.md b/website/docs/docs/dbt-versions/release-notes.md
index ae6ed5f01a4..010042ea49f 100644
--- a/website/docs/docs/dbt-versions/release-notes.md
+++ b/website/docs/docs/dbt-versions/release-notes.md
@@ -19,18 +19,6 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
\* The official release date for this new format of release notes is May 15th, 2024. Historical release notes for prior dates may not reflect all available features released earlier this year or their tenancy availability.
## October 2024
-
-- **Behavior change:** [Multi-factor authentication](/docs/cloud/manage-access/mfa) is now enforced on all users who log in with username and password credentials.
-- **Enhancement**: The dbt Semantic Layer JDBC now allows users to paginate `semantic_layer.metrics()` and `semantic_layer.dimensions()` for metrics and dimensions using `page_size` and `page_number` parameters. Refer to [Paginate metadata calls](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) for more information.
-- **Enhancement**: The dbt Semantic Layer JDBC now allows you to filter your metrics to include only those that contain a specific substring, using the `search` parameter. If no substring is provided, the query returns all metrics. Refer to [Fetch metrics by substring search](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) for more information.
-- **Fix**: The [dbt Semantic Layer Excel integration](/docs/cloud-integrations/semantic-layer/excel) now correctly surfaces errors when a query fails to execute. Previously, it was not clear why a query failed to run.
-- **Fix:** Previously, POST requests to the Jobs API with invalid `cron` strings would return HTTP response status code 500s but would update the underlying entity. Now, POST requests to the Jobs API with invalid `cron` strings will result in status code 400s, without the underlying entity being updated.
-- **Fix:** Fixed an issue where the `Source` view page in dbt Explorer did not correctly display source freshness status if older than 30 days.
-- **Fix:** The UI now indicates when the description of a model is inherited from a catalog comment.
-- **Behavior change:** User API tokens have been deprecated. Update to [personal access tokens](/docs/dbt-cloud-apis/user-tokens) if you have any still in use.
-- **New**: The dbt Cloud IDE supports signed commits for Git, available for Enterprise plans. You can sign your Git commits when pushing them to the repository to prevent impersonation and enhance security. Supported Git providers are GitHub and GitLab. Refer to [Git commit signing](/docs/cloud/dbt-cloud-ide/git-commit-signing.md) for more information.
-- **New:** With dbt Mesh, you can now enable bidirectional dependencies across your projects. Previously, dbt enforced dependencies to only go in one direction. dbt checks for cycles across projects and raises errors if any are detected. For details, refer to [Cycle detection](/docs/collaborate/govern/project-dependencies#cycle-detection). There's also the [Intro to dbt Mesh](/best-practices/how-we-mesh/mesh-1-intro) guide to help you learn more best practices.
-
Documentation for new features and functionality announced at Coalesce 2024:
@@ -54,8 +42,17 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
- [Python SDK](https://docs.getdbt.com/docs/dbt-cloud-apis/sl-python) is now generally available
-
-
+
+- **Behavior change:** [Multi-factor authentication](/docs/cloud/manage-access/mfa) is now enforced on all users who log in with username and password credentials.
+- **Enhancement**: The dbt Semantic Layer JDBC now allows users to paginate `semantic_layer.metrics()` and `semantic_layer.dimensions()` for metrics and dimensions using `page_size` and `page_number` parameters. Refer to [Paginate metadata calls](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) for more information.
+- **Enhancement**: The dbt Semantic Layer JDBC now allows you to filter your metrics to include only those that contain a specific substring, using the `search` parameter. If no substring is provided, the query returns all metrics. Refer to [Fetch metrics by substring search](/docs/dbt-cloud-apis/sl-jdbc#querying-the-api-for-metric-metadata) for more information.
+- **Fix**: The [dbt Semantic Layer Excel integration](/docs/cloud-integrations/semantic-layer/excel) now correctly surfaces errors when a query fails to execute. Previously, it was not clear why a query failed to run.
+- **Fix:** Previously, POST requests to the Jobs API with invalid `cron` strings would return HTTP response status code 500s but would update the underlying entity. Now, POST requests to the Jobs API with invalid `cron` strings will result in status code 400s, without the underlying entity being updated.
+- **Fix:** Fixed an issue where the `Source` view page in dbt Explorer did not correctly display source freshness status if older than 30 days.
+- **Fix:** The UI now indicates when the description of a model is inherited from a catalog comment.
+- **Behavior change:** User API tokens have been deprecated. Update to [personal access tokens](/docs/dbt-cloud-apis/user-tokens) if you have any still in use.
+- **New**: The dbt Cloud IDE supports signed commits for Git, available for Enterprise plans. You can sign your Git commits when pushing them to the repository to prevent impersonation and enhance security. Supported Git providers are GitHub and GitLab. Refer to [Git commit signing](/docs/cloud/dbt-cloud-ide/git-commit-signing.md) for more information.
+- **New:** With dbt Mesh, you can now enable bidirectional dependencies across your projects. Previously, dbt enforced dependencies to only go in one direction. dbt checks for cycles across projects and raises errors if any are detected. For details, refer to [Cycle detection](/docs/collaborate/govern/project-dependencies#cycle-detection). There's also the [Intro to dbt Mesh](/best-practices/how-we-mesh/mesh-1-intro) guide to help you learn more best practices.
- **New**: The [dbt Semantic Layer Python software development kit](/docs/dbt-cloud-apis/sl-python) is now [generally available](/docs/dbt-versions/product-lifecycles). It provides users with easy access to the dbt Semantic Layer with Python and enables developers to interact with the dbt Semantic Layer APIs to query metrics/dimensions in downstream tools.
- **Enhancement**: You can now add a description to a singular data test in dbt Cloud Versionless. Use the [`description` property](/reference/resource-properties/description) to document [singular data tests](/docs/build/data-tests#singular-data-tests). You can also use [docs block](/docs/build/documentation#using-docs-blocks) to capture your test description. The enhancement will be included in upcoming dbt Core 1.9 release.
- **New**: Introducing the [microbatch incremental model strategy](/docs/build/incremental-microbatch) (beta), available in dbt Cloud Versionless and will soon be supported in dbt Core 1.9. The microbatch strategy allows for efficient, batch-based processing of large time-series datasets for improved performance and resiliency, especially when you're working with data that changes over time (like new records being added daily). To enable this feature in dbt Cloud, set the `DBT_EXPERIMENTAL_MICROBATCH` environment variable to `true` in your project.
diff --git a/website/docs/reference/dbt-commands.md b/website/docs/reference/dbt-commands.md
index 8386cf61731..ca9a7725eb2 100644
--- a/website/docs/reference/dbt-commands.md
+++ b/website/docs/reference/dbt-commands.md
@@ -11,7 +11,7 @@ A key distinction with the tools mentioned, is that dbt Cloud CLI and IDE are de
## Parallel execution
-dbt Cloud allows for parallel execution of commands, enhancing efficiency without compromising data integrity. This enables you to run multiple commands at the same time, however it's important to understand which commands can be run in parallel and which can't.
+dbt Cloud allows for concurrent execution of commands, enhancing efficiency without compromising data integrity. This enables you to run multiple commands at the same time. However, it's important to understand which commands can be run in parallel and which can't.
In contrast, [`dbt-core` _doesn't_ support](/reference/programmatic-invocations#parallel-execution-not-supported) safe parallel execution for multiple invocations in the same process, and requires users to manage concurrency manually to ensure data integrity and system stability.
diff --git a/website/docs/reference/programmatic-invocations.md b/website/docs/reference/programmatic-invocations.md
index 09e41b1789f..61250e6debb 100644
--- a/website/docs/reference/programmatic-invocations.md
+++ b/website/docs/reference/programmatic-invocations.md
@@ -25,9 +25,9 @@ for r in res.result:
## Parallel execution not supported
-[`dbt-core`](https://pypi.org/project/dbt-core/) doesn't support [safe parallel execution](/reference/dbt-commands#parallel-execution) for multiple invocations in the same process. This means it's not safe to run multiple dbt commands at the same time. It's officially discouraged and requires a wrapping process to handle sub-processes. This is because:
+[`dbt-core`](https://pypi.org/project/dbt-core/) doesn't support [safe parallel execution](/reference/dbt-commands#parallel-execution) for multiple invocations in the same process. This means it's not safe to run multiple dbt commands concurrently. It's officially discouraged and requires a wrapping process to handle sub-processes. This is because:
-- Running simultaneous commands can unexpectedly interact with the data platform. For example, running `dbt run` and `dbt build` for the same models simultaneously could lead to unpredictable results.
+- Running concurrent commands can unexpectedly interact with the data platform. For example, running `dbt run` and `dbt build` for the same models simultaneously could lead to unpredictable results.
- Each `dbt-core` command interacts with global Python variables. To ensure safe operation, commands need to be executed in separate processes, which can be achieved using methods like spawning processes or using tools like Celery.
To run [safe parallel execution](/reference/dbt-commands#available-commands), you can use the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation) or [dbt Cloud IDE](/docs/cloud/dbt-cloud-ide/develop-in-the-cloud), both of which does that additional work to manage concurrency (multiple processes) on your behalf.
diff --git a/website/docusaurus.config.js b/website/docusaurus.config.js
index b68e2e8ec5c..9fe63267d61 100644
--- a/website/docusaurus.config.js
+++ b/website/docusaurus.config.js
@@ -209,7 +209,7 @@ var siteSettings = {
>