Merge branch 'ly-docs-repo-caching' of github.com:dbt-labs/docs.getdb…

…t.com into ly-docs-repo-caching

website/docs/docs/build/cumulative-metrics.md

@@ -38,10 +38,7 @@ metrics:
 
 ## Limitations
 Cumulative metrics are currently under active development and have the following limitations:
-
-1. You can only use the [`metric_time` dimension](/docs/build/dimensions#time) to check cumulative metrics. If you don't use `metric_time` in the query, the cumulative metric will return incorrect results because it won't perform the time spine join. This means you cannot reference time dimensions other than the `metric_time` in the query.
-2. If you use `metric_time` in your query filter but don't include "start_time" and "end_time," cumulative metrics will left-censor the input data. For example, if you query a cumulative metric with a 7-day window with the filter `{{ TimeDimension('metric_time') }} BETWEEN '2023-08-15' AND '2023-08-30' `, the values for `2023-08-15` to `2023-08-20` return missing or incomplete data. This is because we apply the `metric_time` filter to the aggregation input. To avoid this, you must use `start_time` and `end_time` in the query filter.
-
+- You are required to use [`metric_time` dimension](/docs/build/dimensions#time) when querying cumulative metrics. If you don't use `metric_time` in the query, the cumulative metric will return incorrect results because it won't perform the time spine join. This means you cannot reference time dimensions other than the `metric_time` in the query.
 
 ## Cumulative metrics example
 

website/docs/docs/core/about-core-setup.md

@@ -14,7 +14,7 @@ dbt Core is an [open-source](https://github.com/dbt-labs/dbt-core) tool that ena
 - [Connecting to a data platform](/docs/core/connect-data-platform/profiles.yml)
 - [How to run your dbt projects](/docs/running-a-dbt-project/run-your-dbt-projects)
 
-To learn about developing dbt projects in dbt Cloud or dbt Core, refer to [Develop dbt](/docs/cloud/about-develop-dbt).
-- **Note** — dbt Cloud provides a command line interface with the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation). Both the open-sourced dbt Core and the dbt Cloud CLI are command line tools that let you run dbt commands. The key distinction is the dbt Cloud CLI is tailored for dbt Cloud's infrastructure and integrates with all its [features](/docs/cloud/about-cloud/dbt-cloud-features).
+To learn about developing dbt projects in dbt Cloud, refer to [Develop with dbt Cloud](/docs/cloud/about-develop-dbt).
+  - dbt Cloud provides a command line interface with the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation). Both dbt Core and the dbt Cloud CLI are command line tools that let you run dbt commands. The key distinction is the dbt Cloud CLI is tailored for dbt Cloud's infrastructure and integrates with all its [features](/docs/cloud/about-cloud/dbt-cloud-features).
 
 If you need a more detailed first-time setup guide for specific data platforms, read our [quickstart guides](https://docs.getdbt.com/guides).

website/docs/docs/dbt-versions/release-notes/02-Nov-2023/repo-caching.md

@@ -1,6 +1,6 @@
 ---
 title: "New: Support for Git repository caching"
-description: "November 2023: New option in dbt Cloud to enable Git repository caching for your job runs."
+description: "November 2023: dbt Cloud can cache your project's code (as well as other dbt packages) to ensure runs can begin despite an upstream Git provider's outage."
 sidebar_label: "New: Support for Git repository caching"
 sidebar_position: 07
 tags: [Nov-2023]

website/snippets/_cloud-environments-info.md

@@ -36,7 +36,7 @@ Both development and deployment environments have a section called **General Set
 
 ### Repo caching 
 
-At the start of every job run, dbt Cloud clones the project's Git repository so it has the latest versions of the project code and package code. 
+At the start of every job run, dbt Cloud clones the project's Git repository so it has the latest versions of your project's code and runs `dbt deps` to install your dependencies. 
 
 For improved reliability and performance on your job runs, you can enable dbt Cloud to keep a cache of the project's Git repository. So, if there's a third-party outage (for example, a GitHub outage) that causes the cloning operation to fail, dbt Cloud will instead use the cached copy of the repository so your jobs can continue running as scheduled. 
 

website/vercel.json

@@ -2,11 +2,15 @@
   "cleanUrls": true,
   "trailingSlash": false,
   "redirects": [
+    {
+      "source": "/docs/cloud/dbt-cloud-ide",
+      "destination": "/docs/cloud/dbt-cloud-ide/develop-in-the-cloud",
+      "permanent": true
+    },
     {
       "source": "/docs/core/installation",
       "destination": "/docs/core/installation-overview",
       "permanent": true
-
     },
     {
       "source": "/docs/cloud/about-cloud-develop",