Update to default to ml.t2.large for inference

Author: brightsparc

OPERATIONS.md

@@ -60,7 +60,7 @@ To deploy the latest approved approved `champion` model, and the latest `N` appr
     "stage_name": "dev",
     "strategy": "ThompsonSampling",
     "instance_count": 1,
-    "instance_type": "ml.t2.medium",
+    "instance_type": "ml.t2.large",
     "challenger_variant_count": 1
 }
 ```

README.md

@@ -409,14 +409,14 @@ With the Deployment Pipeline complete, you will be able to continue with the nex
 
 ## Running Cost
 
-This section outlines cost considerations for running the A/B Testing Pipeline. Completing the pipeline will deploy an endpoint with 2 production variants which will cost less than $3 per day. Further cost breakdowns are below.
+This section outlines cost considerations for running the A/B Testing Pipeline. Completing the pipeline will deploy an endpoint with 2 production variants which will cost less than $6 per day. Further cost breakdowns are below.
 
 - **CodeBuild** – Charges per minute used. First 100 minutes each month come at no charge. For information on pricing beyond the first 100 minutes, see [AWS CodeBuild Pricing](https://aws.amazon.com/codebuild/pricing/).
 - **CodeCommit** – $1/month if you didn't opt to use your own GitHub repository.
 - **CodePipeline** – CodePipeline costs $1 per active pipeline* per month. Pipelines are free for the first 30 days after creation. More can be found at [AWS CodePipeline Pricing](https://aws.amazon.com/codepipeline/pricing/).
 - **SageMaker** – Prices vary based on EC2 instance usage for the Notebook Instances, Model Hosting, Model Training and Model Monitoring; each charged per hour of use. For more information, see [Amazon SageMaker Pricing](https://aws.amazon.com/sagemaker/pricing/).
   - The ten `ml.c5.4xlarge` *training jobs* run for approx 4 minutes at $0.81 an hour, and cost less than $1.
-  - The two `ml.t2.medium` instances for production *hosting* endpoint costs 2 x $0.056 per hour, or $2.68 per day.
+  - The two `ml.t2.large` instances for production *hosting* endpoint costs 2 x $0.111 per hour, or $5.33 per day.
 - **S3** – Low cost, prices will vary depending on the size of the models/artifacts stored. The first 50 TB each month will cost only $0.023 per GB stored. For more information, see [Amazon S3 Pricing](https://aws.amazon.com/s3/pricing/).
 - **API Gateway** - Low cost, $1.29 for first 300 million requests.  For more info see [Amazon API Gateway pricing](https://aws.amazon.com/api-gateway/pricing/)
 - **Lambda** - Low cost, $0.20 per 1 million request see [AWS Lambda Pricing](https://aws.amazon.com/lambda/pricing/).

deployment_pipeline/dev-config.json

@@ -2,6 +2,6 @@
     "stage_name": "dev",
     "strategy": "ThompsonSampling",
     "instance_count": 1,
-    "instance_type": "ml.t2.medium",
+    "instance_type": "ml.t2.large",
     "challenger_variant_count": 1
 }

notebook/mab-reviews-helpfulness.ipynb

@@ -573,7 +573,7 @@
     "    model_data=step_train.properties.ModelArtifacts.S3ModelArtifacts,\n",
     "    content_types=[\"text/plain\"],\n",
     "    response_types=[\"text/csv\"],\n",
-    "    inference_instances=[\"ml.t2.medium\", \"ml.m5.xlarge\"],\n",
+    "    inference_instances=[\"ml.t2.large\", \"ml.m5.xlarge\"],\n",
     "    transform_instances=[\"ml.m5.xlarge\"],\n",
     "    model_package_group_name=champion_model_group\n",
     ")"
@@ -1060,7 +1060,7 @@
     "model_package = best_estimator.register(\n",
     "    content_types=[\"text/plain\"],\n",
     "    response_types=[\"text/csv\"],\n",
-    "    inference_instances=[\"ml.t2.medium\", \"ml.m5.xlarge\"],\n",
+    "    inference_instances=[\"ml.t2.large\", \"ml.m5.xlarge\"],\n",
     "    transform_instances=[\"ml.m5.xlarge\"],\n",
     "    model_package_group_name=challenger_model_group,\n",
     "    approval_status=\"Approved\"\n",
@@ -1722,7 +1722,7 @@
     "model_package = best_estimator.register(\n",
     "    content_types=[\"text/plain\"],\n",
     "    response_types=[\"text/csv\"],\n",
-    "    inference_instances=[\"ml.t2.medium\", \"ml.m5.xlarge\"],\n",
+    "    inference_instances=[\"ml.t2.large\", \"ml.m5.xlarge\"],\n",
     "    transform_instances=[\"ml.m5.xlarge\"],\n",
     "    model_package_group_name=champion_model_group,\n",
     "    approval_status=\"Approved\"\n",
@@ -1824,4 +1824,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}