Updating upgrade guide (#5001)

Closes #4998

## What are you changing in this pull request and why?

Updating the 1.8 migration guide with:
- Unit tests
- New installation workflow
- Global config quick hits

## Checklist
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so my content adheres to these guidelines.
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- [ ] Add a checklist item for anything that needs to happen before this
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Adding or removing pages (delete if not applicable):
- [ ] Add/remove page in `website/sidebars.js`
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- [ ] Run link testing locally with `npm run build` to update the links
that point to deleted pages

website/docs/docs/dbt-versions/core-upgrade/01-upgrading-to-v1.8.md

@@ -12,23 +12,53 @@ displayed_sidebar: "docs"
 - [Cloud upgrade guide](/docs/dbt-versions/upgrade-dbt-version-in-cloud)
 - Release schedule (coming soon)
 
-:::tip Keep on latest version, always
-
-Starting this year, let dbt Labs handle version upgrades for you. With dbt Cloud, you can get early access to new functionality before it lands in the final release of dbt Core v1.8 and without the need of managing your own version upgrades. For more details, refer to [Upgrade Core version in Cloud](/docs/dbt-versions/upgrade-dbt-version-in-cloud).
+## What to know before upgrading
 
-The **Keep on latest version** setting is currently available in beta for select dbt Cloud customers, rolling out to wider availability through February and March.
+dbt Labs is committed to providing backward compatibility for all versions 1.x, except for any changes explicitly mentioned on this page. If you encounter an error upon upgrading, please let us know by [opening an issue](https://github.com/dbt-labs/dbt-core/issues/new).
 
-For users of dbt Core, the v1.8.0-b1 release of `dbt-core` & dbt Labs-maintained adapters is planned for February 28.
+dbt Labs plans to release dbt Core v1.8.0-b1 and dbt Labs-maintained adapters on February 28th, 2024.
 
-:::
+## Keep on the latest version in dbt Cloud
 
-## What to know before upgrading
+With dbt Cloud, you can get early access to many new features and functionality before it's in the Generally Available (GA) release of dbt Core v1.8 without the need to manage version upgrades. For more details, refer to [Upgrade Core version in Cloud](/docs/dbt-versions/upgrade-dbt-version-in-cloud).
 
-dbt Labs is committed to providing backward compatibility for all versions 1.x, with the exception of any changes explicitly mentioned below. If you encounter an error upon upgrading, please let us know by [opening an issue](https://github.com/dbt-labs/dbt-core/issues/new).
+The **Keep on latest version** setting is currently available in closed beta for select dbt Cloud customers and will have wider availability in March of 2024.
 
 ## New and changed features and functionality
 
-Features and functionality new in dbt v1.8
+Features and functionality new in dbt v1.8.
+
+### New dbt Core adapter installation procedure
+
+Before v1.8, when you installed an adapter, you would automatically get `dbt-core` installed along with the adapter package (if you didn’t already have an existing, compatible version of dbt-core).
+
+Beginning in v1.8, the [dbt adapters and dbt Core have been decoupled](https://github.com/dbt-labs/dbt-adapters/discussions/87). As a result, you must install _both_ dbt-core and the desired adapter. A new `pip` installation needs to look like this:
+
+```shell
+pip install dbt-core dbt-ADAPTER_NAME
+```
+
+For example, you would use the following command if you use Snowflake:
+```shell
+pip install dbt-core dbt-snowflake
+```
+
+### Unit Tests
+
+Historically, dbt's test coverage was confined to [“data” tests](/docs/build/data-tests), assessing the quality of input data or resulting datasets' structure.
+
+In v1.8, we're introducing native support for [unit testing](/docs/build/unit-tests). Unit tests validate your SQL modeling logic on a small set of static inputs __before__ you materialize your full model in production. They support a test-driven development approach, improving both the efficiency of developers and the reliability of code.
+
+Starting from v1.8, when you execute the `dbt test` command, it will run both unit and data tests. Use the [`test_type`](/reference/node-selection/methods#the-test_type-method) method to run only unit or data tests:
+
+```shell
+
+dbt test --select "test_type:unit"           # run all unit tests
+dbt test --select "test_type:data"           # run all data tests
+
+```
+
+Unit tests are defined in YML files in your `models/` directory and are currently only supported on SQL models. To distinguish between the two, the `tests:` config has been renamed to `data_tests:`. Both are currently supported for backward compatibility.
 
 ### The `--empty` flag
 
@@ -37,4 +67,6 @@ The [`run`](/reference/commands/run#the-`--empty`-flag) and [`build`](/reference
 
 ## Quick hits
 
-Coming soon!
+- [Global config flags](/reference/global-configs/about-global-configs) are deprecated from the [`profiles.yml`](/docs/core/connect-data-platform/profiles.yml) file and should be moved to the [`dbt_project.yml`](/reference/dbt_project.yml).
+- A new subcategory of flags has been created for [legacy behaviors](/reference/global-configs/legacy-behaviors).
+- The [`--indirect_selection`](/reference/global-configs/indirect-selection) flag used with `dbt test` or `dbt build` configures which tests to run for the nodes you specify.