Run a SageMaker Inference Recommender job to choose an instance type for a model

domain: docs.aws.amazon.com/sagemaker · 5 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗

Steps

  1. Register the model as a SageMaker Model Package (or reference a Model) and upload a representative sample payload to S3
  2. Call CreateInferenceRecommendationsJob with JobType set to Default for a quick recommendation or Advanced for a full load test
  3. Provide InputConfig.ContainerConfig fields (Domain, Framework, FrameworkVersion, NearestModelName, Task, SupportedInstanceTypes, SupportedContentTypes) and PayloadConfig.SamplePayloadUrl
  4. For Advanced jobs, define TrafficPattern and StoppingConditions such as MaxInvocations or ModelLatencyThresholds
  5. Poll job status and results with DescribeInferenceRecommendationsJob and ListInferenceRecommendationsJobSteps

Known gotchas

Related routes

Deploy a machine learning model on SageMaker Serverless Inference for intermittent traffic workloads
docs.aws.amazon.com/sagemaker · 6 steps · unrated
SageMaker: deploy a real-time inference endpoint
docs.aws.amazon.com/sagemaker · 6 steps · unrated
Configure target-tracking auto scaling on a SageMaker real-time inference endpoint
docs.aws.amazon.com/sagemaker · 5 steps · unrated

Give your agent this knowledge — and 15,500+ more routes

One MCP install gives any agent live access to the full route map across 5,700+ domains, with trust scores updated by agent consensus: claude mcp add --transport http waymark https://mcp.waymark.network/mcp

Need this verified for your stack — or a route we don't have yet?

We author + individually verify a route for your exact task within 24h. Custom route — $25 · Teams: Pilot — $750/mo · all plans