Add docs

docs/ui-ingestion.md

@@ -1,5 +1,12 @@
+import FeatureAvailability from '@site/src/components/FeatureAvailability';
+
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
 # Ingestion
 
+<FeatureAvailability/>
+
 ## Introduction 
 
 Starting in version `0.8.25`, DataHub supports creating, configuring, scheduling, & executing batch metadata ingestion using the DataHub user interface. This makes
@@ -173,28 +180,29 @@ Finally, give your Ingestion Source a name.
 Once you're happy with your configurations, click 'Done' to save your changes.
 
 
-##### Advanced: Running with a specific CLI version 
+##### Advanced ingestion configs:
 
-DataHub comes pre-configured to use the latest version of the DataHub CLI ([acryl-datahub](https://pypi.org/project/acryl-datahub/)) that is compatible
+DataHub's Managed Ingestion UI comes pre-configured to use the latest version of the DataHub CLI ([acryl-datahub](https://pypi.org/project/acryl-datahub/)) that is compatible
 with the server. However, you can override the default package version using the 'Advanced' source configurations.
 
 To do so, simply click 'Advanced', then change the 'CLI Version' text box to contain the exact version
 of the DataHub CLI you'd like to use.
 
-
 <p align="center">
   <img width="70%"  src="https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/custom-ingestion-cli-version.png"/>
 </p>
 
 _Pinning the CLI version to version `0.8.23.2`_
 
+Other advanced options include specifying environment variables, DataHub plugins or python packages at runtime. 
+
 Once you're happy with your changes, simply click 'Done' to save. 
 
    </TabItem>
    <TabItem value="cli" label="CLI" default>
 
 You can upload and even update recipes using the cli as mentioned in the [cli documentation for uploading ingestion recipes](./cli.md#ingest-deploy).
-An example execution would look something like:
+An example execution for a given `recipe.yaml` file, would look something like:
 
 ```bash
 datahub ingest deploy --name "My Test Ingestion Source" --schedule "5 * * * *" --time-zone "UTC" -c recipe.yaml

metadata-ingestion/docs/dev_guides/profiling_ingestions.md

@@ -13,6 +13,35 @@ This page documents how to perform memory profiles of ingestion runs.
 It is useful when trying to size the amount of resources necessary to ingest some source or when developing new features or sources.
 
 ## How to use
+
+<Tabs>
+<TabItem value="ui" label="UI" default>
+
+Create an ingestion as specified in the [Ingestion guide](../../../docs/ui-ingestion.md).
+
+Add a flag to your ingestion recipe to generate a memray memory dump of your ingestion:
+```yaml
+source:
+  ...
+
+sink:
+  ...
+
+flags:
+  generate_memory_profiles: "<path to folder where dumps will be written to>"
+```
+
+In the final panel, under the advanced section, add the `debug` datahub package under the **Extra DataHub Plugins** section.
+As seen below:
+
+<p align="center">
+  <img width="70%"  src="https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/ingestion-advanced-extra-datahub-plugin.png"/>
+</p>
+
+Finally, save and run the ingestion process.
+
+</TabItem>
+<TabItem value="cli" label="CLI" default>
 Install the `debug` plugin for DataHub's CLI wherever the ingestion runs:
 
 ```bash
@@ -33,6 +62,16 @@ flags:
   generate_memory_profiles: "<path to folder where dumps will be written to>"
 ```
 
+Finally run the ingestion recipe
+
+```bash
+$ datahub ingest -c recipe.yaml
+```
+
+</TabItem>
+</Tabs>
+
+
 Once the ingestion run starts a binary file will be created and appended to during the execution of the ingestion. 
 
 These files follow the pattern `file-<ingestion-run-urn>.bin` for a unique identification.