feat: model deploy with endpoint config name (#19)

* feat: model deploynwith endpoint config name

* chore: update descriptions

* chore: remove wiki url

* chore: update descriptions

Author: stiyyagura0901

src/@orb.yml

@@ -5,5 +5,5 @@ description: >
   (OPEN PREVIEW - send feedback at [email protected])
 
 display:
-  home_url: "https://github.com/CircleCI-Public/aws-sagemaker-orb/wiki"
+  home_url: "https://github.com/CircleCI-Public/aws-sagemaker-orb"
   source_url: "https://github.com/CircleCI-Public/aws-sagemaker-orb"

src/examples/create_endpoint.yml

@@ -0,0 +1,40 @@
+description: >
+  This example defines a CircleCI workflow that uses the aws-sagemaker orb to:
+    - Create a SageMaker model
+    - Create an endpoint configuration for the model
+    - Deploy the model to an endpoint
+  It shows a typical machine learning workflow using SageMaker with model releases being tracked on CircleCI.
+usage:
+  version: 2.1
+  orbs:
+    aws-sagemaker: circleci/[email protected]
+  workflows:
+    ai-workflow:
+      jobs:
+        - aws-sagemaker/create_model:
+            name: create-model
+            model_name: replace_with_model_name
+            deploy_environment: replace_with_environment
+            pipeline_id: << pipeline.id >>
+            bucket: replace_with_s3_bucket_name
+            region_name: replace_with_region_name
+        - aws-sagemaker/create_endpoint_configuration:
+            name: create-endpoint-configuration
+            model_name: replace_with_model_name
+            deploy_environment: replace_with_environment
+            pipeline_id: << pipeline.id >>
+            bucket: replace_with_s3_bucket_name
+            region_name: replace_with_region_name
+            requires:
+              - create-model
+        - aws-sagemaker/deploy_endpoint:
+            name: deploy-endpoint
+            model_name: replace_with_model_name
+            model_desc: replace_with_description
+            deploy_environment: replace_with_environment
+            pipeline_id: <<pipeline.id>>
+            project_id: replace_with_project_id
+            bucket: replace_with_s3_bucket_name
+            region_name: replace_with_region_name
+            requires:
+              - create-endpoint-configuration

src/examples/deploy_model.yml

@@ -0,0 +1,20 @@
+description: >
+  Deploys a model to SageMaker with an existing endpoint configuration.
+usage:
+  version: 2.1
+  orbs:
+    aws-sagemaker: circleci/[email protected]
+  workflows:
+    ai-workflow:
+      jobs:
+        - aws-sagemaker/deploy_endpoint:
+            name: deploy-endpoint
+            model_name: replace_with_model_name
+            model_desc: replace_with_description
+            deploy_environment: replace_with_environment
+            pipeline_id: <<pipeline.id>>
+            project_id: replace_with_project_id
+            bucket: replace_with_s3_bucket_name
+            region_name: replace_with_region_name
+            endpoint_config_name: replace_with_existing_endpoint_config_name
+            endpoint_name: replace_with_endpoint_name

src/examples/deploy_model_with_endpoint_config_name.yml

@@ -114,7 +114,7 @@ repo_name="cci-sagemaker"
 # binary="${orb_bin_dir}/${repo_name}"
 # TODO: Make the version configurable via parameter
 # Don't forget the v!
-binary_version="v0.0.12"
+binary_version="v0.0.13"
 basic_name="cci-sagemaker"
 binary_name="${basic_name}-${binary_version}-${PLATFORM}-${ARCH}"
 binary_zip="${orb_bin_dir}/${binary_name}.zip"