AWS SageMaker Endpoint Config Builder

ComputeAWS

Build SageMaker endpoint configurations with production variants, auto-scaling, data capture, and canary deployments.

Amazon SageMaker Configuration

Build SageMaker endpoint configurations with production variants, auto-scaling, data capture, and canary deployments.

Required Fields

EndpointConfigNameProductionVariants

{
  "EndpointConfigName": "prod-inference-endpoint-config",
  "ProductionVariants": [
    {
      "VariantName": "primary",
      "ModelName": "my-model-v3",
      "InstanceType": "ml.g5.xlarge",
      "InitialInstanceCount": 2,
      "InitialVariantWeight": 0.9,
      "AcceleratorType": "ml.eia2.medium",
      "ModelDataDownloadTimeoutInSeconds": 600,
      "ContainerStartupHealthCheckTimeoutInSeconds": 300,
      "VolumeSizeInGB": 50,
      "ManagedInstanceScaling": {
        "Status": "ENABLED",
        "MinInstanceCount": 1,
        "MaxInstanceCount": 5
      },
      "RoutingConfig": {
        "RoutingStrategy": "LEAST_OUTSTANDING_REQUESTS"
      }
    },
    {
      "VariantName": "canary",
      "ModelName": "my-model-v4",
      "InstanceType": "ml.g5.xlarge",
      "InitialInstanceCount": 1,
      "InitialVariantWeight": 0.1,
      "VolumeSizeInGB": 50
    }
  ],
  "DataCaptureConfig": {
    "EnableCapture": true,
    "InitialSamplingPercentage": 10,
    "DestinationS3Uri": "s3://model-monitoring-bucket/data-capture/",
    "CaptureOptions": [
      {"CaptureMode": "Input"},
      {"CaptureMode": "Output"}
    ],
    "CaptureContentTypeHeader": {
      "JsonContentTypes": ["application/json"]
    }
  },
  "KmsKeyId": "arn:aws:kms:us-east-1:123456789012:key/abcd1234-ef56-gh78-ij90-klmnopqrstuv",
  "Tags": [
    {
      "Key": "Model",
      "Value": "recommendation-engine"
    }
  ]
}

Generated Output

Output will appear here...

How It Helps

Build SageMaker endpoint configurations with production variants, auto-scaling, data capture, and canary deployments. This tool helps AWS engineers generate valid configurations quickly without consulting documentation, reducing errors and accelerating infrastructure deployment. All processing runs in your browser with no data sent to external servers.

Things Engineers Ask

How does this SageMaker Endpoint config builder keep up with new AWS features?

The SageMaker Endpoint options surface what is currently documented in the AWS reference for that service. When AWS adds a new property or value, it is added here after we have verified the schema in a real account. If a brand-new feature is not yet selectable, treat that as a 'not yet supported' signal rather than an opinion that it should not be used.

Will the output of this SageMaker Endpoint config builder pass `aws cloudformation validate-template` or `terraform validate`?

It produces structurally valid output for the AWS schemas it supports. We still recommend running provider validation locally before applying — schemas evolve and a recently-released property may not yet be reflected here. If validation fails, the failure message points at the exact attribute the schema rejected.

Practical Applications

1Producing a SageMaker Endpoint starting point for a new microservice that follows the AWS reference architecture rather than copy-paste from another team's repo.
2Pre-flighting a SageMaker Endpoint change against a change-management ticket so the implementation matches what the CAB approved.
3Translating an AWS Solutions Architect's whiteboard sketch into a concrete SageMaker Endpoint spec engineers can apply.
4Generating a SageMaker Endpoint starting point for a Well-Architected Framework review where the reviewer wants to see baseline configs.

Related Learning Guides

EC2 Instance Types Explained24 min read
ECS vs EKS Decision Guide24 min read

Was this tool helpful?

Disclaimer: This tool runs entirely in your browser. No data is sent to our servers. Always verify outputs before using them in production. AWS, Azure, and GCP are trademarks of their respective owners.

AWS SageMaker Endpoint Config Builder

ComputeAWS

Build SageMaker endpoint configurations with production variants, auto-scaling, data capture, and canary deployments.

Amazon SageMaker Configuration

Build SageMaker endpoint configurations with production variants, auto-scaling, data capture, and canary deployments.

Required Fields

EndpointConfigNameProductionVariants

Generated Output

Output will appear here...

How It Helps

Things Engineers Ask

How does this SageMaker Endpoint config builder keep up with new AWS features?

Will the output of this SageMaker Endpoint config builder pass `aws cloudformation validate-template` or `terraform validate`?

Practical Applications

1Producing a SageMaker Endpoint starting point for a new microservice that follows the AWS reference architecture rather than copy-paste from another team's repo.
2Pre-flighting a SageMaker Endpoint change against a change-management ticket so the implementation matches what the CAB approved.
3Translating an AWS Solutions Architect's whiteboard sketch into a concrete SageMaker Endpoint spec engineers can apply.
4Generating a SageMaker Endpoint starting point for a Well-Architected Framework review where the reviewer wants to see baseline configs.

Related Learning Guides

EC2 Instance Types Explained24 min read
ECS vs EKS Decision Guide24 min read

Was this tool helpful?