[dagster-airlift][moves] airlift moves (#25832)

## Summary & Motivation
This PR was original just moving the tutorial. Now using it as an accumulator for all the "moving shit out of airlift directory" PRs before landing them as a unit.

.buildkite/dagster-buildkite/dagster_buildkite/pipelines/dagster_oss_nightly_pipeline.py

@@ -54,7 +54,7 @@ def build_dagster_oss_nightly_steps() -> List[BuildkiteStep]:
                 ],
             ),
             PackageSpec(
-                "examples/experimental/dagster-airlift/examples/dbt-example",
+                "examples/starlift-demo",
                 name="airlift-demo-live-tests",
                 env_vars=[
                     "KS_DBT_CLOUD_ACCOUNT_ID",

.buildkite/dagster-buildkite/dagster_buildkite/steps/packages.py

@@ -373,7 +373,7 @@ def k8s_extra_cmds(version: AvailablePythonVersion, _) -> List[str]:
     # Runs against live dbt cloud instance, we only want to run on commits and on the
     # nightly build
     PackageSpec(
-        "examples/experimental/dagster-airlift/examples/dbt-example",
+        "examples/starlift-demo",
         skip_if=skip_if_not_airlift_or_dlift_commit,
         env_vars=[
             "KS_DBT_CLOUD_ACCOUNT_ID",
@@ -386,15 +386,15 @@ def k8s_extra_cmds(version: AvailablePythonVersion, _) -> List[str]:
         queue=BuildkiteQueue.DOCKER,
     ),
     PackageSpec(
-        "examples/experimental/dagster-airlift/examples/perf-harness",
+        "examples/experimental/dagster-airlift/perf-harness",
         always_run_if=has_dagster_airlift_changes,
     ),
     PackageSpec(
-        "examples/experimental/dagster-airlift/examples/tutorial-example",
+        "examples/airlift-migration-tutorial",
         always_run_if=has_dagster_airlift_changes,
     ),
     PackageSpec(
-        "examples/experimental/dagster-airlift/examples/kitchen-sink",
+        "examples/experimental/dagster-airlift/kitchen-sink",
         always_run_if=has_dagster_airlift_changes,
     ),
     PackageSpec(

docs/content/integrations/airlift/full_dag.mdx

@@ -17,7 +17,7 @@ When migrating an entire DAG at once, we'll want to create assets which map to t
 
 For our `rebuild_customers_list` DAG, let's take a look at what the new observation code looks like:
 
-```python file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/dagster_defs/stages/observe_dag_level.py
+```python file=../../airlift-migration-tutorial/tutorial_example/dagster_defs/stages/observe_dag_level.py
 import os
 from pathlib import Path
 
@@ -79,7 +79,7 @@ Now, instead of getting a materialization when a particular task completes, each
 
 Recall that in the [task-by-task migration step](/integrations/airlift/tutorial/migrate), we "proxy" execution on a task by task basis, which is controlled by a yaml document. For DAG-mapped assets, execution is proxied on a per-DAG basis. Proxying execution to Dagster will require all assets mapped to that DAG be _executable_ within Dagster. Let's take a look at some fully migrated code mapped to DAGs instead of tasks:
 
-```python file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/dagster_defs/stages/migrate_dag_level.py
+```python file=../../airlift-migration-tutorial/tutorial_example/dagster_defs/stages/migrate_dag_level.py
 import os
 from pathlib import Path
 
@@ -192,13 +192,13 @@ if __name__ == "__main__":
 
 Now that all of our assets are fully executable, we can create a simple yaml file to proxy execution for the whole dag:
 
-```yaml file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/snippets/rebuild_customers_list.yaml
+```yaml file=../../airlift-migration-tutorial/tutorial_example/snippets/rebuild_customers_list.yaml
 proxied: True
 ```
 
 We will similarly use `proxying_to_dagster` at the end of our DAG file (the code is exactly the same here as it was for the per-task migration step)
 
-```python file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/snippets/dags_truncated.py
+```python file=../../airlift-migration-tutorial/tutorial_example/snippets/dags_truncated.py
 # Dags file can be found at tutorial_example/airflow_dags/dags.py
 from pathlib import Path
 

docs/content/integrations/airlift/reference.mdx

@@ -16,7 +16,7 @@ description: "dagster-airlift is a toolkit for observing and migrating Airflow D
 
 If your Dagster deployment lives behind a custom auth backend, you can customize the Airflow-to-Dagster proxying behavior to authenticate to your backend. `proxying_to_dagster` can take a parameter `dagster_operator_klass`, which allows you to define a custom `BaseProxyTasktoDagsterOperator` class. This allows you to override how a session is created. Let's say for example, your Dagster installation requires an access key to be set whenever a request is made, and that access key is set in an Airflow `Variable` called `my_api_key`. We can create a custom `BaseProxyTasktoDagsterOperator` subclass which will retrieve that variable value and set it on the session, so that any requests to Dagster's graphql API will be made using that api key.
 
-```python file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/snippets/custom_operator_examples/custom_proxy.py
+```python file=../../airlift-migration-tutorial/tutorial_example/snippets/custom_operator_examples/custom_proxy.py
 from pathlib import Path
 
 import requests
@@ -55,7 +55,7 @@ proxying_to_dagster(
 
 You can use a custom proxy operator to establish a connection to a Dagster plus deployment. The below example proxies to Dagster Plus using organization name, deployment name, and user token set as Airflow Variables. To set a Dagster+ user token, follow [this](https://docs.dagster.io/dagster-plus/account/managing-user-agent-tokens#managing-user-tokens) guide.
 
-```python file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/snippets/custom_operator_examples/plus_proxy_operator.py
+```python file=../../airlift-migration-tutorial/tutorial_example/snippets/custom_operator_examples/plus_proxy_operator.py
 import requests
 from airflow.utils.context import Context
 from dagster_airlift.in_airflow import BaseProxyTaskToDagsterOperator
@@ -130,7 +130,7 @@ Similar to how we can customize the operator we construct on a per-dag basis, we
 
 For example, in the following example we can see that the operator is customized to provide an authorization header which authenticates Dagster.
 
-```python file=../../experimental/dagster-airlift/examples/tutorial-example/tutorial_example/snippets/custom_operator_examples/custom_dag_level_proxy.py
+```python file=../../airlift-migration-tutorial/tutorial_example/snippets/custom_operator_examples/custom_dag_level_proxy.py
 from pathlib import Path
 
 import requests