feathr-ai · xiaoyongzhu · Aug 10, 2022 · Aug 1, 2022 · Aug 1, 2022 · Aug 1, 2022
diff --git a/docs/README.md b/docs/README.md
@@ -33,7 +33,7 @@ Feathr automatically computes your feature values and joins them to your trainin
 
 Feathr has native integrations with Databricks and Azure Synapse:
 
-Follow the [Feathr ARM deployment guide ](https://linkedin.github.io/feathr/how-to-guides/azure-deployment-arm.html) to run Feathr on Azure. This allows you to quickly get started with automated deployment using Azure Resource Manager template.
+Follow the [Feathr ARM deployment guide](https://linkedin.github.io/feathr/how-to-guides/azure-deployment-arm.html) to run Feathr on Azure. This allows you to quickly get started with automated deployment using Azure Resource Manager template.
 
 If you want to set up everything manually, you can checkout the [Feathr CLI deployment guide](https://linkedin.github.io/feathr/how-to-guides/azure-deployment-cli.html) to run Feathr on Azure. This allows you to understand what is going on and set up one resource at a time.
 
@@ -60,9 +60,22 @@ Or use the latest code from GitHub:
 pip install git+https://github.com/linkedin/feathr.git#subdirectory=feathr_project
 ```
 
-## 🔡 Feathr Examples
+## 🔡 Feathr Highlighted Capabilities
 
-Please read [Feathr Capabilities](https://linkedin.github.io/feathr/concepts/feathr-capabilities.html) for more examples. Below are a few selected ones:
+Please read [Feathr Full Capabilities](./concepts/feathr-capabilities.md) for more examples. Below are a few selected ones:
+
+### Feathr UI
+
+Feathr provides an intuitive UI so you can search and explore all the available features and their corresponding lineages.
+
+You can use Feathr UI to search features, identify data sources, track feature lineages and manage access controls. Check out the latest live demo [here](https://aka.ms/feathrdemo) to see what Feathr UI can do for you. Use one of following accounts when you are prompted to login:
+
+- A work or school organization account, includes Office 365 subscribers.
+- Microsoft personal account, this means an account can access to Skype, Outlook.com, OneDrive, and Xbox LIVE.
+
+![Feathr UI](./images/feathr-ui.png)
+
+For more information on the Feathr UI and the registry behind it, please refer to [Feathr Feature Registry](./concepts/feature-registry.md)
 
 ### Rich UDF Support
 
@@ -81,7 +94,7 @@ batch_source = HdfsSource(name="nycTaxiBatchSource",
                         timestamp_format="yyyy-MM-dd HH:mm:ss")
 ```
 
-### Defining Window Aggregation Features
+### Defining Window Aggregation Features with Point-in-time correctness
 
 ```python
 agg_features = [Feature(name="f_location_avg_fare",
@@ -131,13 +144,6 @@ Read [Point-in-time Correctness and Point-in-time Join in Feathr](https://linked
 
 Follow the [quick start Jupyter Notebook](./samples/product_recommendation_demo.ipynb) to try it out. There is also a companion [quick start guide](https://linkedin.github.io/feathr/quickstart_synapse.html) containing a bit more explanation on the notebook.
 
-### Feathr UI
-
-You can use Feathr UI to search features, identify data sources, track feature lineages and manage access controls. Check out the latest live demo [here](https://aka.ms/feathrdemo) to see what Feathr UI can do for you. Use one of following accounts when you are prompted to login:
-
-- A work or school organization account, includes Office 365 subscribers.
-- Microsoft personal account, this means an account can access to Skype, Outlook.com, OneDrive, and Xbox LIVE.
-
 ## 🗣️ Tech Talks on Feathr
 
 - [Introduction to Feathr - Beginner's guide](https://www.youtube.com/watch?v=gZg01UKQMTY)
@@ -155,7 +161,7 @@ You can use Feathr UI to search features, identify data sources, track feature l
 | Offline store – SQL             | Azure SQL DB, Azure Synapse Dedicated SQL Pools, Azure SQL in VM, Snowflake |
 | Streaming Source                | Kafka, EventHub                                                             |
 | Online store                    | Azure Cache for Redis                                                       |
-| Feature Registry and Governance | Azure Purview                                                               |
+| Feature Registry and Governance | Azure Purview, ANSI SQL such as Azure SQL Server                            |
 | Compute Engine                  | Azure Synapse Spark Pools, Databricks                                       |
 | Machine Learning Platform       | Azure Machine Learning, Jupyter Notebook, Databricks Notebook               |
 | File Format                     | Parquet, ORC, Avro, JSON, Delta Lake                                        |
@@ -167,10 +173,10 @@ For a complete roadmap with estimated dates, please [visit this page](https://gi
 
 - [x] Support streaming
 - [x] Support common data sources
+- [x] Support feature store UI, including Lineage and Search functionalities
 - [ ] Support online transformation
 - [ ] Support feature versioning
 - [ ] Support feature monitoring
-- [ ] Support feature store UI, including Lineage and Search functionalities
 - [ ] Support feature data deletion and retention
 
 ## 👨‍👨‍👦‍👦 Community Guidelines

diff --git a/docs/concepts/feature-definition.md b/docs/concepts/feature-definition.md
@@ -60,11 +60,11 @@ request_anchor = FeatureAnchor(name="request_features",
                                features=features)
 ```
 
-For the features field above, there are two different types, simple anchored features and window aggregation features.
+For the features field above, there are two different types, anchor features without aggregations, and anchor features with window aggregation features.
 
-### Simple anchored features
+### Anchor features without aggregations
 
-1. For simple anchored features, see the example below:
+For simple anchored features, see the example below:
 
 ```python
 f_trip_time_duration = Feature(name="f_trip_time_duration",
@@ -74,9 +74,9 @@ f_trip_time_duration = Feature(name="f_trip_time_duration",
 
 Note that for `transform` section, you can put a simple expression to transform your features. For more information, please refer to [Feathr User Defined Functions (UDFs)](../how-to-guides/feathr-udfs.md).
 
-### Window aggregation features
+### Anchor features with aggregations
 
-2. For window aggregation features, see the supported fields below:
+For window aggregation features, see the supported fields below:
 
 ```python
 

diff --git a/docs/concepts/feature-registry.md b/docs/concepts/feature-registry.md
@@ -0,0 +1,117 @@
+---
+layout: default
+title: Feature Registry
+parent: Feathr Concepts
+---
+
+# Feature Registry and Feathr UI
+
+Feature registry is an important component of a feature store. This documentation will cover the supported backend of a feature registry and the usages.
+
+## Introduction
+
+Feathr UI and Feathr Registry are two optional components to use Feathr, but
+
+## Deployment
+
+Please follow the `Provision Azure Resources using ARM Template` part in the [Azure Resource Provisioning document](../how-to-guides/azure-deployment-arm.md#provision-azure-resources-using-arm-template) to provision corresponding the Azure resources. After completing those steps, you should have a set of resources that can be used for Feature Registry.
+
+In case you want to do it in a more customized way, you can use [this Dockerfile](https://github.com/linkedin/feathr/blob/main/FeathrRegistry.Dockerfile) to deploy the REST API and UI. This docker image is more for illustration purpose, and you can customize it further (like building the REST API and UI in separate docker images).
+
+If you use [Azure Resource Provisioning document](../how-to-guides/azure-deployment-arm.md#provision-azure-resources-using-arm-template) to provision the resources, you should be able to access the UI in this website:
+
+```bash
+https://{prefix}webapp.azurewebsites.net
+```
+
+And the corresponding REST API will be:
+
+```bash
+https://{prefix}webapp.azurewebsites.net/api/v1
+```
+
+## Deployment Options
+
+Feathr supports two types of backends for Feature Registry - Azure Purview (Apache Atlas compatible service) and ANSI SQL. Depending on your IT setup, you might choose either of those in the above deployment steps.
+
+Note that if you choose to enable Role-based Access Control (RBAC), you still need to use a SQL service (such as Azure SQL) to store all the RBAC related information.
+
+## Architecture
+
+![Architecture Diagram](../images/architecture.png)
+
+The architecture is as above. More specifically, there are three components for Feathr feature registry:
+
+- Feathr UI, a react based application
+- Feathr REST API, which provides abstraction for different registry providers, as well as role-based access control (RBAC)
+- Different feature registry backends. Currently only Azure Purview and SQL based registry are supported, but more registry providers from the community are welcome.
+
+Both the Feathr UI and the Feathr Python Client interact with the Feathr REST API service. The REST API service then detect if the user has the right access, and route the corresponding request to the registry providers.
+
+## Accessing Registry in Feathr Python Client
+
+In the Feathr python client, if you want to access the registry, you should set the `FEATURE_REGISTRY__API_ENDPOINT` environment variable. The full [document is here](../how-to-guides/feathr-configuration-and-env.md#a-list-of-environment-variables-that-feathr-uses).
+
+Alternatively, you can set the feature registry and the API endpoint in the configuration YAML file:
+
+```yaml
+feature_registry:
+  # The API endpoint of the registry service
+  api_endpoint: "https://feathr-sql-registry.azurewebsites.net/api/v1"
+```
+
+### Register and Listing Features
+
+You can register your features in the centralized registry and share it with other team members who want to consume those features and for further use. You can also use `list_registered_features` to verify if they have been registered successfully.
+
+```python
+client.build_features(anchor_list=[agg_anchor, request_anchor], derived_feature_list=derived_feature_list)
+client.register_features()
+all_features = client.list_registered_features(project_name=client.project_name)
+```
+
+### Reuse Features from Existing Registry
+
+For feature consumers, they can reuse existing features from the registry. The whole project can be retrieved to local environment by calling this API `client.get_features_from_registry` with a project name. This encourage feature reuse across organizations. For example, end users of a feature just need to read all feature definitions from the existing projects, then use a few features from the projects and join those features with a new dataset you have.
+
+For example, in the [product recommendation demo notebook](./../samples/product_recommendation_demo.ipynb), some other team members have already defined a few features, such as `feature_user_gift_card_balance` and `feature_user_has_valid_credit_card`. If we want to reuse those features for anti-abuse purpose in a new dataset, what you can do is like this, i.e. just call `get_features_from_registry` to get the features, then put the features you want to query to the anti-abuse dataset you have.
+
+```python
+registered_features_dict = client.get_features_from_registry(client.project_name)
+
+# Features that we want to request
+feature_query = FeatureQuery(feature_list=[ "feature_user_gift_card_balance",
+                                           "feature_user_has_valid_credit_card", ],
+                             key=user_id)
+settings = ObservationSettings(
+    observation_path="some_anti_abuse_dataset_path",
+    event_timestamp_column="event_timestamp",
+    timestamp_format="yyyy-MM-dd")
+feathr_client.get_offline_features(observation_settings=settings,
+                            feature_query=feature_query,
+                            output_path=output_path)
+```
+
+## Accessing Feathr UI
+
+Feathr UI should be straightforward to use. Currently there are a few pages, including:
+
+### Feature Summary page
+
+You can see a list of all the features in a project:
+![Feature Summary](../images/feature-summary.png)
+
+### Feature Detailed Page
+
+You can view the detailed information for a feature:
+![Feature Detailed Page](../images/feature-details.png)
+
+### Feature Lineage Page
+
+You can view all the lineage info for features in a project.
+![Feature Lineage Page](../images/feathr-ui.png)
+
+### Access Control Management Page
+
+If RBAC is enabled, admins can manage access control for users.
+![Access Control Management Page](../images/access-control-management.png)