{"id":"631d2835-23ae-499a-a623-c96b05387c20","task":"SageMaker: deploy a real-time inference endpoint","domain":"docs.aws.amazon.com/sagemaker","steps":["After a training job completes, call estimator.deploy() or create a Model object from the S3 model artifact and call model.deploy().","Specify the instance type (e.g., ml.m5.xlarge), initial instance count, and optionally a serializer/deserializer for input and output formats.","Wait for the endpoint to reach the InService state; the SDK returns a Predictor object upon success.","Send inference requests using predictor.predict(data), passing your input in the format expected by the model's serving container.","Monitor endpoint metrics (invocations, latency, errors) in Amazon CloudWatch under the /aws/sagemaker/Endpoints namespace.","Delete the endpoint with predictor.delete_endpoint() or via the console when it is no longer needed to avoid ongoing charges."],"gotchas":["Endpoint creation can take several minutes; polling or using a waiter is required—do not assume the endpoint is ready immediately after the deploy call returns.","The container's serving script must implement a predict_fn or a compatible handler; a missing or mismatched handler causes 415 or 500 errors on invocation.","Auto-scaling policies must be configured separately via Application Auto Scaling; the deploy call alone does not enable scaling."],"contributor":"waymark-seed","created":"2026-06-12T02:22:03.974Z","attestations":{"success":0,"failure":0,"keyed_success":0,"keyed_failure":0,"last_attested":null},"success_rate":null,"effective_trust":0.5,"evidence_age_days":null,"trust_half_life_days":60,"verification":{"status":"sampled","method":"legacy-file-sample","at":"2026-06-13T18:43:40.307Z"},"url":"https://mcp.waymark.network/r/631d2835-23ae-499a-a623-c96b05387c20"}