Remove hard coded resources in docs (feathr-ai#696)

Remove hard coded resources, such as synapse, app endpoint, redis and so on in docs to avoid causing confusion.

docs/concepts/feathr-capabilities.md

@@ -143,8 +143,8 @@ schema = AvroJsonSchema(schemaStr="""
 }
 """)
 stream_source = KafKaSource(name="kafkaStreamingSource",
-                            kafkaConfig=KafkaConfig(brokers=["feathrazureci.servicebus.windows.net:9093"],
-                                                    topics=["feathrcieventhub"],
+                            kafkaConfig=KafkaConfig(brokers=["<replace_with_your_broker>.servicebus.windows.net:9093"],
+                                                    topics=["<replace_with_your_eventhub>"],
                                                     schema=schema)
                             )
 

docs/concepts/feature-definition.md

@@ -23,7 +23,7 @@ See an examples below:
 
 ```python
 batch_source = HdfsSource(name="nycTaxiBatchSource",
-                          path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/demo_data/green_tripdata_2020-04.csv",
+                          path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/demo_data/green_tripdata_2020-04.csv",
                           event_timestamp_column="lpep_dropoff_datetime",
                           timestamp_format="yyyy-MM-dd HH:mm:ss")
 ```

docs/concepts/feature-registry.md

@@ -61,7 +61,7 @@ Alternatively, you can set the feature registry and the API endpoint in the conf
 ```yaml
 feature_registry:
   # The API endpoint of the registry service
-  api_endpoint: "https://feathr-sql-registry.azurewebsites.net/api/v1"
+  api_endpoint: "https://<replace_with_your_feathr_api_endpoint>.azurewebsites.net/api/v1"
 ```
 
 ### Register and List Features

docs/concepts/materializing-features.md

@@ -96,7 +96,7 @@ The API call is very similar to materializing features to online store, and here
 
 ```python
 client = FeathrClient()
-offlineSink = HdfsSink(output_path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/materialize_offline_test_data/")
+offlineSink = HdfsSink(output_path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/materialize_offline_test_data/")
 # Materialize two features into a Offline store.
 settings = MaterializationSettings("nycTaxiMaterializationJob",
                                    sinks=[offlineSink],
@@ -121,14 +121,14 @@ settings = MaterializationSettings("nycTaxiTable",
 ```
 
 This will materialize features with cutoff time from `2020/05/10` to `2020/05/20` correspondingly, and the output will have 11 folders, from
-`abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/materialize_offline_test_data/df0/daily/2020/05/10` to `abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/materialize_offline_test_data/df0/daily/2020/05/20`. Note that currently Feathr only supports materializing data in daily step (i.e. even if you specify an hourly step, the generated features in offline store will still be presented in a daily hierarchy). For more details on how `BackfillTime` works, refer to the [BackfillTime section](#feature-backfill) above.
+`abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/materialize_offline_test_data/df0/daily/2020/05/10` to `abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/materialize_offline_test_data/df0/daily/2020/05/20`. Note that currently Feathr only supports materializing data in daily step (i.e. even if you specify an hourly step, the generated features in offline store will still be presented in a daily hierarchy). For more details on how `BackfillTime` works, refer to the [BackfillTime section](#feature-backfill) above.
 
 You can also specify the format of the materialized features in the offline store by using `execution_configurations` like below. Please refer to the [documentation](../how-to-guides/feathr-job-configuration.md) here for those configuration details.
 
 ```python
 
 from feathr import HdfsSink
-offlineSink = HdfsSink(output_path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/materialize_offline_data/")
+offlineSink = HdfsSink(output_path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/materialize_offline_data/")
 # Materialize two features into a Offline store.
 settings = MaterializationSettings("nycTaxiMaterializationJob",
                                    sinks=[offlineSink],
@@ -141,7 +141,7 @@ For reading those materialized features, Feathr has a convenient helper function
 
 ```python
 from feathr import get_result_df
-path = "abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/materialize_offline_test_data/df0/daily/2020/05/20/"
+path = "abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/materialize_offline_test_data/df0/daily/2020/05/20/"
 res = get_result_df(client=client, format="parquet", res_url=path)
 ```
 

docs/concepts/point-in-time-join.md

@@ -105,12 +105,12 @@ And below shows the join definitions:
 feature_query = FeatureQuery(
     feature_list=["feature_X"], key=UserId)
 settings = ObservationSettings(
-    observation_path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/demo_data/green_tripdata_2020-04.csv",
+    observation_path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/demo_data/green_tripdata_2020-04.csv",
     event_timestamp_column="Date",
     timestamp_format="MM/DD")
 client.get_offline_features(observation_settings=settings,
                             feature_query=feature_query,
-                            output_path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/demo_data/output.avro")
+                            output_path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/demo_data/output.avro")
 ```
 
 ## Advanced Point-in-time Lookup

docs/quickstart_synapse.md

@@ -164,8 +164,8 @@ The following feature join config is used:
 ```python
 feature_query = [FeatureQuery(feature_list=["f_location_avg_fare"], key=["DOLocationID"])]
         settings = ObservationSettings(
-            observation_path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/demo_data/green_tripdata_2020-04.csv",
-            output_path="abfss://feathrazuretest3fs@feathrazuretest3storage.dfs.core.windows.net/demo_data/output.avro",
+            observation_path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/demo_data/green_tripdata_2020-04.csv",
+            output_path="abfss://{adls_fs_name}@{adls_account}.dfs.core.windows.net/demo_data/output.avro",
             event_timestamp_column="lpep_dropoff_datetime", timestamp_format="yyyy-MM-dd HH:mm:ss")
 client.get_offline_features(feature_query=feature_query, observation_settings=settings)
 ```