Label config as local or aws api-configuration.md (#1017)

Author: vishalbollu

docs/deployments/api-configuration.md

@@ -10,22 +10,23 @@ Reference the section below which corresponds to your Predictor type: [Python](#
 
 ```yaml
 - name: <string> # API name (required)
- endpoint: <string> # the endpoint for the API (default: <api_name>)
+ endpoint: <string> # the endpoint for the API (aws only) (default: <api_name>)
+ local_port: <int> # specify the port for API (local only) (default: 8888)
  predictor:
  type: python
  path: <string> # path to a python file with a PythonPredictor class definition, relative to the Cortex root (required)
  config: <string: value> # arbitrary dictionary passed to the constructor of the Predictor (optional)
  python_path: <string> # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
  image: <string> # docker image to use for the Predictor (default: cortexlabs/python-predictor-cpu or cortexlabs/python-predictor-gpu based on compute)
  env: <string: string> # dictionary of environment variables
- tracker:
+ tracker: # (aws only)
  key: <string> # the JSON key in the response to track (required if the response payload is a JSON object)
  model_type: <string> # must be "classification" or "regression", so responses can be interpreted correctly (i.e. categorical vs continuous) (required)
  compute:
  cpu: <string | int | float> # CPU request per replica, e.g. 200m or 1 (200m is equivalent to 0.2) (default: 200m)
  gpu: <int> # GPU request per replica (default: 0)
  mem: <string> # memory request per replica, e.g. 200Mi or 1Gi (default: Null)
- autoscaling:
+ autoscaling: # (aws only)
  min_replicas: <int> # minimum number of replicas (default: 1)
  max_replicas: <int> # maximum number of replicas (default: 100)
  init_replicas: <int> # initial number of replicas (default: <min_replicas>)
@@ -40,7 +41,7 @@ Reference the section below which corresponds to your Predictor type: [Python](#
  max_upscale_factor: <float> # the maximum factor by which to scale up the API on a single scaling event (default: 1.5)
  downscale_tolerance: <float> # any recommendation falling within this factor below the current number of replicas will not trigger a scale down event (default: 0.05)
  upscale_tolerance: <float> # any recommendation falling within this factor above the current number of replicas will not trigger a scale up event (default: 0.05)
- update_strategy:
+ update_strategy: # (aws only)
  max_surge: <string | int> # maximum number of replicas that can be scheduled above the desired number of replicas during an update; can be an absolute number, e.g. 5, or a percentage of desired replicas, e.g. 10% (default: 25%) (set to 0 to disable rolling updates)
  max_unavailable: <string | int> # maximum number of replicas that can be unavailable during an update; can be an absolute number, e.g. 5, or a percentage of desired replicas, e.g. 10% (default: 25%)
 ```
@@ -51,7 +52,8 @@ See additional documentation for [autoscaling](autoscaling.md), [compute](comput
 
 ```yaml
 - name: <string> # API name (required)
- endpoint: <string> # the endpoint for the API (default: <api_name>)
+ endpoint: <string> # the endpoint for the API (aws only) (default: <api_name>)
+ local_port: <int> # specify the port for API (local only) (default: 8888)
  predictor:
  type: tensorflow
  path: <string> # path to a python file with a TensorFlowPredictor class definition, relative to the Cortex root (required)
@@ -62,14 +64,14 @@ See additional documentation for [autoscaling](autoscaling.md), [compute](comput
  image: <string> # docker image to use for the Predictor (default: cortexlabs/tensorflow-predictor)
  tensorflow_serving_image: <string> # docker image to use for the TensorFlow Serving container (default: cortexlabs/tensorflow-serving-gpu or cortexlabs/tensorflow-serving-cpu based on compute)
  env: <string: string> # dictionary of environment variables
- tracker:
+ tracker: # (aws only)
  key: <string> # the JSON key in the response to track (required if the response payload is a JSON object)
  model_type: <string> # must be "classification" or "regression", so responses can be interpreted correctly (i.e. categorical vs continuous) (required)
  compute:
  cpu: <string | int | float> # CPU request per replica, e.g. 200m or 1 (200m is equivalent to 0.2) (default: 200m)
  gpu: <int> # GPU request per replica (default: 0)
  mem: <string> # memory request per replica, e.g. 200Mi or 1Gi (default: Null)
- autoscaling:
+ autoscaling: # (aws only)
  min_replicas: <int> # minimum number of replicas (default: 1)
  max_replicas: <int> # maximum number of replicas (default: 100)
  init_replicas: <int> # initial number of replicas (default: <min_replicas>)
@@ -84,7 +86,7 @@ See additional documentation for [autoscaling](autoscaling.md), [compute](comput
  max_upscale_factor: <float> # the maximum factor by which to scale up the API on a single scaling event (default: 1.5)
  downscale_tolerance: <float> # any recommendation falling within this factor below the current number of replicas will not trigger a scale down event (default: 0.05)
  upscale_tolerance: <float> # any recommendation falling within this factor above the current number of replicas will not trigger a scale up event (default: 0.05)
- update_strategy:
+ update_strategy: # (aws only)
  max_surge: <string | int> # maximum number of replicas that can be scheduled above the desired number of replicas during an update; can be an absolute number, e.g. 5, or a percentage of desired replicas, e.g. 10% (default: 25%) (set to 0 to disable rolling updates)
  max_unavailable: <string | int> # maximum number of replicas that can be unavailable during an update; can be an absolute number, e.g. 5, or a percentage of desired replicas, e.g. 10% (default: 25%)
 ```
@@ -95,7 +97,8 @@ See additional documentation for [autoscaling](autoscaling.md), [compute](comput
 
 ```yaml
 - name: <string> # API name (required)
- endpoint: <string> # the endpoint for the API (default: <api_name>)
+ endpoint: <string> # the endpoint for the API (aws only) (default: <api_name>)
+ local_port: <int> # specify the port for API (local only) (default: 8888)
  predictor:
  type: onnx
  path: <string> # path to a python file with an ONNXPredictor class definition, relative to the Cortex root (required)
@@ -104,14 +107,14 @@ See additional documentation for [autoscaling](autoscaling.md), [compute](comput
  python_path: <string> # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
  image: <string> # docker image to use for the Predictor (default: cortexlabs/onnx-predictor-gpu or cortexlabs/onnx-predictor-cpu based on compute)
  env: <string: string> # dictionary of environment variables
- tracker:
+ tracker: # (aws only)
  key: <string> # the JSON key in the response to track (required if the response payload is a JSON object)
  model_type: <string> # must be "classification" or "regression", so responses can be interpreted correctly (i.e. categorical vs continuous) (required)
  compute:
  cpu: <string | int | float> # CPU request per replica, e.g. 200m or 1 (200m is equivalent to 0.2) (default: 200m)
  gpu: <int> # GPU request per replica (default: 0)
  mem: <string> # memory request per replica, e.g. 200Mi or 1Gi (default: Null)
- autoscaling:
+ autoscaling: # (aws only)
  min_replicas: <int> # minimum number of replicas (default: 1)
  max_replicas: <int> # maximum number of replicas (default: 100)
  init_replicas: <int> # initial number of replicas (default: <min_replicas>)
@@ -126,7 +129,7 @@ See additional documentation for [autoscaling](autoscaling.md), [compute](comput
  max_upscale_factor: <float> # the maximum factor by which to scale up the API on a single scaling event (default: 1.5)
  downscale_tolerance: <float> # any recommendation falling within this factor below the current number of replicas will not trigger a scale down event (default: 0.05)
  upscale_tolerance: <float> # any recommendation falling within this factor above the current number of replicas will not trigger a scale up event (default: 0.05)
- update_strategy:
+ update_strategy: # (aws only)
  max_surge: <string | int> # maximum number of replicas that can be scheduled above the desired number of replicas during an update; can be an absolute number, e.g. 5, or a percentage of desired replicas, e.g. 10% (default: 25%) (set to 0 to disable rolling updates)
  max_unavailable: <string | int> # maximum number of replicas that can be unavailable during an update; can be an absolute number, e.g. 5, or a percentage of desired replicas, e.g. 10% (default: 25%)
 ```