From 0df387a6b3ff2d3ef8b6b547d224e3ea53a545f9 Mon Sep 17 00:00:00 2001 From: Roja Reddy Sareddy Date: Thu, 20 Mar 2025 00:48:08 -0700 Subject: [PATCH] Added code block to describe update_endpoint option in sagemaker model_builder --- .../model_builder_handshake.ipynb | 55 +++++++++++++++++++ 1 file changed, 55 insertions(+) diff --git a/ deploy_and_monitor/sm-model_builder/model_builder_handshake.ipynb b/ deploy_and_monitor/sm-model_builder/model_builder_handshake.ipynb index 4e014d3e64..a2e0e73a2a 100644 --- a/ deploy_and_monitor/sm-model_builder/model_builder_handshake.ipynb +++ b/ deploy_and_monitor/sm-model_builder/model_builder_handshake.ipynb @@ -259,6 +259,21 @@ "print(result)" ] }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "# Update existing endpoint\n", + "predictor = model_builder.deploy(\n", + " endpoint_name=f\"{alias}-xgboost-deploy-realtime\",\n", + " initial_instance_count=3,\n", + " update_endpoint=True, # Updates existing endpoint\n", + ")" + ], + "id": "74b554744208fa27" + }, { "cell_type": "markdown", "id": "fbd0e6f6e92d0aeb", @@ -285,6 +300,24 @@ "print(result)" ] }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "predictor = model_builder.deploy(\n", + " endpoint_name=f\"{alias}-xgboost-deploy-serverless\",\n", + " inference_config=ServerlessInferenceConfig(memory_size_in_mb=1024),\n", + " update_endpoint=True,\n", + ")\n", + "\n", + "sklearn_input = np.array([1.0, 2.0, 3.0, 4.0])\n", + "result = predictor.predict(sklearn_input)\n", + "print(result)" + ], + "id": "305dca02732c0eac" + }, { "cell_type": "markdown", "id": "93818038782f105d", @@ -317,6 +350,28 @@ "print(result)" ] }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "predictor = model_builder.deploy(\n", + " endpoint_name=f\"{alias}-xgboost-deploy-async\",\n", + " inference_config=AsyncInferenceConfig(\n", + " output_path=s3_path_join(\n", + " \"s3://\", bucket, f\"{default_bucket_prefix_path}async_inference/update_output_prefix\"\n", + " )\n", + " ),\n", + " update_endpoint=True,\n", + ")\n", + "\n", + "sklearn_input = np.array([1.0, 2.0, 3.0, 4.0])\n", + "result = predictor.predict(sklearn_input)\n", + "print(result)" + ], + "id": "bbb56866e2faf7b" + }, { "cell_type": "markdown", "id": "2ff3e043b5f5f8d7",