diff --git a/.github/config/image/autogluon/1.6-sagemaker-cpu.yml b/.github/config/image/autogluon/1.6-sagemaker-cpu.yml
new file mode 100644
index 000000000000..3d04ee467ca4
--- /dev/null
+++ b/.github/config/image/autogluon/1.6-sagemaker-cpu.yml
@@ -0,0 +1,33 @@
+image:
+  name: "autogluon-1.6-sagemaker-cpu"
+  description: "AutoGluon 1.6 CPU training and inference for SageMaker"
+
+metadata:
+  framework: "autogluon"
+  framework_version: "1.6.3"
+  os_version: "amzn2023"
+  customer_type: "sagemaker"
+  platform: "sagemaker"
+  arch_type: "x86"
+  device_type: "cpu"
+  job_type: "general"
+  prod_image: "autogluon:1.6-cpu-amzn2023"
+
+build:
+  dockerfile: "docker/autogluon/Dockerfile"
+  target: "sagemaker"
+  base_image: "public.ecr.aws/deep-learning-containers/pytorch:2.13-cpu-amzn2023-sagemaker"
+  requirements_file: "docker/autogluon/1.6/requirements.cpu.in"
+  python_version: "3.12"
+  dlc_major_version: "1"
+  dlc_minor_version: "0"
+
+release:
+  # Gamma-testing the unified image before production.
+  # Follow-up: publish the AutoGluon docs only after the production release succeeds.
+  release: true
+  force_release: false
+  public_registry: false
+  private_registry: true
+  enable_soci: false
+  environment: "gamma"
diff --git a/.github/config/image/autogluon/1.6-sagemaker-cuda.yml b/.github/config/image/autogluon/1.6-sagemaker-cuda.yml
new file mode 100644
index 000000000000..ddee498ba01d
--- /dev/null
+++ b/.github/config/image/autogluon/1.6-sagemaker-cuda.yml
@@ -0,0 +1,34 @@
+image:
+  name: "autogluon-1.6-sagemaker-cuda"
+  description: "AutoGluon 1.6 GPU training and inference for SageMaker"
+
+metadata:
+  framework: "autogluon"
+  framework_version: "1.6.3"
+  os_version: "amzn2023"
+  customer_type: "sagemaker"
+  platform: "sagemaker"
+  arch_type: "x86"
+  device_type: "gpu"
+  job_type: "general"
+  prod_image: "autogluon:1.6-cu133-amzn2023"
+
+build:
+  dockerfile: "docker/autogluon/Dockerfile"
+  target: "sagemaker"
+  base_image: "public.ecr.aws/deep-learning-containers/pytorch:2.13-cu133-amzn2023-sagemaker"
+  requirements_file: "docker/autogluon/1.6/requirements.cuda.in"
+  python_version: "3.12"
+  cuda_version: "13.3.0"
+  dlc_major_version: "1"
+  dlc_minor_version: "0"
+
+release:
+  # Gamma-testing the unified image before production.
+  # Follow-up: publish the AutoGluon docs only after the production release succeeds.
+  release: true
+  force_release: false
+  public_registry: false
+  private_registry: true
+  enable_soci: false
+  environment: "gamma"
diff --git a/.github/config/test-suites.yml b/.github/config/test-suites.yml
index b27fe0c9c229..ff761a9db800 100644
--- a/.github/config/test-suites.yml
+++ b/.github/config/test-suites.yml
@@ -56,6 +56,11 @@ suites:
     code_paths:
       - test/pytorch/integration/sagemaker/**
 
+  autogluon/sagemaker:
+    skip_eligible: true
+    code_paths:
+      - test/autogluon/sagemaker/**
+
   tensorflow-inference/sagemaker:
     skip_eligible: true
     code_paths:
diff --git a/.github/workflows/autogluon.dispatch-release.yml b/.github/workflows/autogluon.dispatch-release.yml
new file mode 100644
index 000000000000..4869039112d4
--- /dev/null
+++ b/.github/workflows/autogluon.dispatch-release.yml
@@ -0,0 +1,29 @@
+name: "Dispatch - AutoGluon Release"
+
+# AutoGluon ships a few times a year, so releases are triggered by hand rather
+# than on a cron. Run once per config file from `main`; the pipeline's
+# release-gate reads release.environment (gamma / production) from the config.
+
+on:
+  workflow_dispatch:
+    inputs:
+      config-file:
+        description: "Path to image config YAML (e.g., .github/config/image/autogluon/1.6-sagemaker-cuda.yml)"
+        required: true
+        type: string
+
+concurrency:
+  group: ${{ github.workflow }}
+  cancel-in-progress: false
+
+permissions:
+  contents: read
+
+jobs:
+  pipeline:
+    uses: ./.github/workflows/autogluon.pipeline.yml
+    with:
+      config-file: ${{ inputs.config-file }}
+      tag-suffix: ${{ github.run_id }}
+      release: true
+    secrets: inherit
diff --git a/.github/workflows/autogluon.pipeline.yml b/.github/workflows/autogluon.pipeline.yml
new file mode 100644
index 000000000000..a755bf7f4e3d
--- /dev/null
+++ b/.github/workflows/autogluon.pipeline.yml
@@ -0,0 +1,201 @@
+name: "Pipeline - AutoGluon"
+
+on:
+  workflow_call:
+    inputs:
+      config-file:
+        description: "Path to image config YAML"
+        required: true
+        type: string
+      tag-suffix:
+        description: "CI tag suffix (run_id or pr-NUMBER)"
+        required: true
+        type: string
+      build:
+        description: "Whether to build the image (false = skip build, test against prod)"
+        required: false
+        type: boolean
+        default: true
+      run-sanity-test:
+        description: "Run sanity tests"
+        required: false
+        type: boolean
+        default: true
+      run-unit-test:
+        description: "Run serving adapter unit tests"
+        required: false
+        type: boolean
+        default: true
+      run-security-test:
+        description: "Run security tests"
+        required: false
+        type: boolean
+        default: true
+      run-telemetry-test:
+        description: "Run telemetry tests"
+        required: false
+        type: boolean
+        default: true
+      run-sagemaker-test:
+        description: "Run SageMaker training and endpoint tests"
+        required: false
+        type: boolean
+        default: true
+      release:
+        description: "Run release job after tests pass"
+        required: false
+        type: boolean
+        default: false
+    outputs:
+      image-uri:
+        description: "Built image URI (empty if build was skipped)"
+        value: ${{ jobs.build.outputs.image-uri }}
+
+jobs:
+  build:
+    if: ${{ inputs.build }}
+    concurrency:
+      group: ${{ github.workflow }}-build-${{ inputs.config-file }}-${{ github.ref }}
+      cancel-in-progress: true
+    runs-on:
+      - codebuild-runner-${{ github.run_id }}-${{ github.run_attempt }}
+        fleet:x86-build-runner
+        buildspec-override:true
+    timeout-minutes: 120
+    outputs:
+      image-uri: ${{ steps.build.outputs.image-uri }}
+    steps:
+      - uses: actions/checkout@v6
+      - id: build
+        uses: ./.github/actions/build-image
+        with:
+          config-file: ${{ inputs.config-file }}
+          aws-account-id: ${{ vars.CI_AWS_ACCOUNT_ID }}
+          aws-region: ${{ vars.AWS_REGION }}
+          tag-suffix: ${{ inputs.tag-suffix }}
+
+  check:
+    if: ${{ always() && !failure() && !cancelled() }}
+    needs: [build]
+    concurrency:
+      group: ${{ github.workflow }}-check-${{ inputs.config-file }}-${{ github.ref }}
+      cancel-in-progress: true
+    uses: ./.github/workflows/_reusable.check-test-pass.yml
+    with:
+      config-file: ${{ inputs.config-file }}
+      image-uri: ${{ needs.build.outputs.image-uri || '' }}
+      suites: '["sanity", "telemetry", "autogluon/sagemaker"]'
+
+  unit-tests:
+    if: ${{ inputs.run-unit-test }}
+    uses: ./.github/workflows/autogluon.tests-unit.yml
+
+  sanity-test:
+    if: ${{ always() && !cancelled() && inputs.run-sanity-test && needs.build.result != 'failure' && fromJSON(needs.check.outputs.skips || '{}')['sanity'] != true }}
+    needs: [build, check]
+    concurrency:
+      group: ${{ github.workflow }}-sanity-test-${{ inputs.config-file }}-${{ github.ref }}
+      cancel-in-progress: true
+    uses: ./.github/workflows/_reusable.sanity-tests.yml
+    with:
+      config-file: ${{ inputs.config-file }}
+      image-uri: ${{ needs.build.outputs.image-uri || '' }}
+      image-content-hash: ${{ needs.check.outputs.image-content-hash }}
+      suite-code-hash: ${{ fromJSON(needs.check.outputs.suite-code-hashes || '{}')['sanity'] || '' }}
+
+  security-test:
+    if: ${{ always() && !failure() && !cancelled() && inputs.run-security-test }}
+    needs: [build]
+    concurrency:
+      group: ${{ github.workflow }}-security-test-${{ inputs.config-file }}-${{ github.ref }}
+      cancel-in-progress: true
+    uses: ./.github/workflows/_reusable.security-tests.yml
+    with:
+      config-file: ${{ inputs.config-file }}
+      image-uri: ${{ needs.build.outputs.image-uri || '' }}
+
+  telemetry-test:
+    if: ${{ always() && !cancelled() && inputs.run-telemetry-test && needs.build.result != 'failure' && fromJSON(needs.check.outputs.skips || '{}')['telemetry'] != true }}
+    needs: [build, check]
+    concurrency:
+      group: ${{ github.workflow }}-telemetry-test-${{ inputs.config-file }}-${{ github.ref }}
+      cancel-in-progress: false
+    uses: ./.github/workflows/_reusable.telemetry-tests.yml
+    with:
+      config-file: ${{ inputs.config-file }}
+      image-uri: ${{ needs.build.outputs.image-uri || '' }}
+      image-content-hash: ${{ needs.check.outputs.image-content-hash }}
+      suite-code-hash: ${{ fromJSON(needs.check.outputs.suite-code-hashes || '{}')['telemetry'] || '' }}
+
+  sagemaker-tests:
+    if: >-
+      ${{ always() && !cancelled() && inputs.run-sagemaker-test &&
+          needs.build.result != 'failure' &&
+          fromJSON(needs.check.outputs.skips || '{}')['autogluon/sagemaker'] != true }}
+    needs: [build, check]
+    concurrency:
+      group: ${{ github.workflow }}-sagemaker-tests-${{ inputs.config-file }}-${{ github.ref }}
+      cancel-in-progress: false
+    uses: ./.github/workflows/autogluon.tests-sagemaker.yml
+    with:
+      config-file: ${{ inputs.config-file }}
+      image-uri: ${{ needs.build.outputs.image-uri || '' }}
+      image-content-hash: ${{ needs.check.outputs.image-content-hash }}
+      suite-code-hash: ${{ fromJSON(needs.check.outputs.suite-code-hashes || '{}')['autogluon/sagemaker'] || '' }}
+
+  release-gate:
+    if: >-
+      github.ref == 'refs/heads/main' &&
+      (contains(github.workflow_ref, '.autorelease') || contains(github.workflow_ref, '.dispatch-release')) &&
+      !contains(github.workflow_ref, '.pr') &&
+      inputs.release &&
+      !failure() && !cancelled() &&
+      needs.build.result == 'success'
+    needs: [build, unit-tests, sanity-test, security-test, telemetry-test, sagemaker-tests]
+    runs-on: ubuntu-latest
+    outputs:
+      should-release: ${{ steps.check.outputs.should-release }}
+      release-spec: ${{ steps.spec.outputs.release-spec }}
+      environment: ${{ steps.check.outputs.environment }}
+    steps:
+      - uses: actions/checkout@v6
+      - id: check
+        run: |
+          SHOULD_RELEASE=$(yq '.release.release' "${{ inputs.config-file }}")
+          ENVIRONMENT=$(yq '.release.environment' "${{ inputs.config-file }}")
+          echo "should-release=${SHOULD_RELEASE}" >> $GITHUB_OUTPUT
+          echo "environment=${ENVIRONMENT}" >> $GITHUB_OUTPUT
+      - id: spec
+        if: steps.check.outputs.should-release == 'true'
+        uses: ./.github/actions/generate-release-spec
+        with:
+          config-file: ${{ inputs.config-file }}
+
+  release:
+    if: ${{ !failure() && !cancelled() && needs.release-gate.outputs.should-release == 'true' }}
+    needs: [build, release-gate]
+    uses: ./.github/workflows/_reusable.release-image.yml
+    with:
+      source-image-uri: ${{ needs.build.outputs.image-uri }}
+      release-spec: ${{ needs.release-gate.outputs.release-spec }}
+      environment: ${{ needs.release-gate.outputs.environment }}
+      aws-region: ${{ vars.AWS_REGION }}
+    secrets: inherit
+
+  notify-failure:
+    if: >-
+      failure() &&
+      github.ref == 'refs/heads/main' &&
+      (contains(github.workflow_ref, '.autorelease') || contains(github.workflow_ref, '.dispatch-release')) &&
+      !contains(github.workflow_ref, '.pr') &&
+      inputs.release
+    needs: [build, unit-tests, sanity-test, security-test, telemetry-test, sagemaker-tests, release-gate, release]
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v6
+      - uses: ./.github/actions/notify-slack-failure
+        with:
+          webhook-url: ${{ secrets.SLACK_RELEASE_FAILURE_WEBHOOK_URL }}
+          workflow-name: ${{ github.workflow }}
+          config-file: ${{ inputs.config-file }}
+          run-url: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
diff --git a/.github/workflows/autogluon.pr-1.6.yml b/.github/workflows/autogluon.pr-1.6.yml
new file mode 100644
index 000000000000..f86a09da14c8
--- /dev/null
+++ b/.github/workflows/autogluon.pr-1.6.yml
@@ -0,0 +1,100 @@
+name: "PR - AutoGluon 1.6"
+
+on:
+  pull_request:
+    branches: [main]
+    types: [opened, reopened, synchronize]
+    paths:
+      - ".github/config/image/autogluon/1.6-sagemaker-*.yml"
+      - ".github/workflows/autogluon.pipeline.yml"
+      - ".github/workflows/autogluon.pr-1.6.yml"
+      - ".github/workflows/autogluon.tests-sagemaker.yml"
+      - ".github/workflows/autogluon.tests-unit.yml"
+      - "docker/autogluon/**"
+      - "scripts/docker/autogluon/**"
+      - "scripts/docker/common/setup_oss_compliance.sh"
+      - "scripts/docker/telemetry/**"
+      - "test/sanity/**"
+      - "test/security/data/ecr_scan_allowlist/autogluon/**"
+      - "test/telemetry/**"
+      - "test/autogluon/**"
+      - "!docs/**"
+
+permissions:
+  contents: read
+  pull-requests: read
+
+jobs:
+  gatekeeper:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          ref: ${{ github.event.pull_request.base.sha }}
+          fetch-depth: 1
+      - uses: ./.github/actions/pr-permission-gate
+
+  check-changes:
+    needs: [gatekeeper]
+    runs-on: ubuntu-latest
+    outputs:
+      build-change: ${{ steps.changes.outputs.build-change }}
+      sanity-test-change: ${{ steps.changes.outputs.sanity-test-change }}
+      unit-test-change: ${{ steps.changes.outputs.unit-test-change }}
+      sagemaker-test-change: ${{ steps.changes.outputs.sagemaker-test-change }}
+      telemetry-test-change: ${{ steps.changes.outputs.telemetry-test-change }}
+    steps:
+      - uses: actions/checkout@v6
+      - uses: dorny/paths-filter@v4
+        id: changes
+        with:
+          filters: |
+            build-change:
+              - ".github/config/image/autogluon/1.6-sagemaker-*.yml"
+              - "docker/autogluon/**"
+              - "scripts/docker/autogluon/**"
+              - "scripts/docker/common/setup_oss_compliance.sh"
+              - "test/security/data/ecr_scan_allowlist/autogluon/**"
+            sanity-test-change:
+              - "test/sanity/**"
+            unit-test-change:
+              - "scripts/docker/autogluon/**"
+              - "test/autogluon/inference/test_*.py"
+              - ".github/workflows/autogluon.tests-unit.yml"
+            sagemaker-test-change:
+              - "test/autogluon/sagemaker/**"
+              - ".github/workflows/autogluon.tests-sagemaker.yml"
+            telemetry-test-change:
+              - "scripts/docker/telemetry/**"
+              - "test/telemetry/**"
+
+  discover:
+    needs: [gatekeeper]
+    runs-on: ubuntu-latest
+    outputs:
+      configs: ${{ steps.discover.outputs.configs }}
+    steps:
+      - uses: actions/checkout@v6
+      - id: discover
+        uses: ./.github/actions/discover-configs
+        with:
+          pattern: ".github/config/image/autogluon/1.6-sagemaker-*.yml"
+
+  pipeline:
+    needs: [check-changes, discover]
+    strategy:
+      fail-fast: false
+      matrix:
+        include: ${{ fromJson(needs.discover.outputs.configs) }}
+    uses: ./.github/workflows/autogluon.pipeline.yml
+    with:
+      config-file: ${{ matrix.config_file }}
+      tag-suffix: pr-${{ github.event.pull_request.number }}
+      build: ${{ needs.check-changes.outputs.build-change == 'true' }}
+      run-sanity-test: ${{ needs.check-changes.outputs.build-change == 'true' || needs.check-changes.outputs.sanity-test-change == 'true' }}
+      run-unit-test: ${{ (needs.check-changes.outputs.build-change == 'true' || needs.check-changes.outputs.unit-test-change == 'true') && endsWith(matrix.config_file, '-cpu.yml') }}
+      run-security-test: ${{ needs.check-changes.outputs.build-change == 'true' }}
+      run-telemetry-test: ${{ needs.check-changes.outputs.build-change == 'true' || needs.check-changes.outputs.telemetry-test-change == 'true' }}
+      run-sagemaker-test: ${{ needs.check-changes.outputs.build-change == 'true' || needs.check-changes.outputs.sagemaker-test-change == 'true' }}
+      release: false
+    secrets: inherit
diff --git a/.github/workflows/autogluon.tests-sagemaker.yml b/.github/workflows/autogluon.tests-sagemaker.yml
new file mode 100644
index 000000000000..3ce819046165
--- /dev/null
+++ b/.github/workflows/autogluon.tests-sagemaker.yml
@@ -0,0 +1,116 @@
+name: Reusable AutoGluon SageMaker Tests
+
+on:
+  workflow_call:
+    inputs:
+      config-file:
+        description: "Path to image config YAML"
+        required: true
+        type: string
+      image-uri:
+        description: "Image URI to test. If empty, derives prod URI from config."
+        required: false
+        type: string
+        default: ""
+      image-content-hash:
+        description: "Image hash computed from hash_image_content.py for caching a test pass."
+        required: false
+        type: string
+        default: ""
+      suite-code-hash:
+        description: "Test code hash computed from hash_suite_code.py for caching a test pass."
+        required: false
+        type: string
+        default: ""
+
+permissions:
+  contents: read
+
+jobs:
+  preflight:
+    runs-on:
+      - codebuild-runner-${{ github.run_id }}-${{ github.run_attempt }}
+        fleet:default-runner
+        buildspec-override:true
+    outputs:
+      image-uri: ${{ steps.image.outputs.image-uri }}
+      aws-account-id: ${{ steps.image.outputs.aws-account-id }}
+      image-exists: ${{ steps.check.outputs.exists }}
+      device-type: ${{ steps.config.outputs.device-type }}
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Resolve image URI
+        id: image
+        uses: ./.github/actions/resolve-image-uri
+        with:
+          image-uri: ${{ inputs.image-uri }}
+          ci-aws-account-id: ${{ vars.CI_AWS_ACCOUNT_ID }}
+          prod-aws-account-id: ${{ vars.PROD_AWS_ACCOUNT_ID }}
+          aws-region: ${{ vars.AWS_REGION }}
+          config-file: ${{ inputs.config-file }}
+
+      - name: Check image exists
+        id: check
+        uses: ./.github/actions/check-image-exists
+        with:
+          image-uri: ${{ steps.image.outputs.image-uri }}
+
+      - name: Parse image device type
+        id: config
+        run: |
+          echo "device-type=$(yq '.metadata.device_type' '${{ inputs.config-file }}')" >> $GITHUB_OUTPUT
+
+  e2e-test:
+    # Trains a model with the image, then deploys that exact artifact for inference.
+    if: ${{ needs.preflight.outputs.image-exists == 'true' }}
+    needs: [preflight]
+    runs-on:
+      - codebuild-runner-${{ github.run_id }}-${{ github.run_attempt }}
+        fleet:default-runner
+        buildspec-override:true
+    timeout-minutes: 120
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: ECR login
+        uses: ./.github/actions/ecr-authenticate
+        with:
+          aws-account-id: ${{ needs.preflight.outputs.aws-account-id }}
+          aws-region: ${{ vars.AWS_REGION }}
+          image-uri: ${{ needs.preflight.outputs.image-uri }}
+
+      - name: Run SageMaker train-to-serve test
+        env:
+          SM_ROLE_ARN: arn:aws:iam::${{ vars.CI_AWS_ACCOUNT_ID }}:role/SageMakerRole
+          SM_DEVICE_TYPE: ${{ needs.preflight.outputs.device-type }}
+        run: |
+          uv venv --python 3.12
+          source .venv/bin/activate
+          uv pip install -r test/requirements.txt
+          uv pip install -r test/autogluon/sagemaker/requirements.txt
+          cd test/
+          PYTHONPATH=$(pwd):$PYTHONPATH \
+            uv run --active --no-project pytest -v --tb=short -rA --log-cli-level=INFO \
+            --image-uri ${{ needs.preflight.outputs.image-uri }} \
+            autogluon/sagemaker/test_train_and_serve.py
+
+  record-test-pass:
+    if: >-
+      ${{ always() && !cancelled() && !failure() &&
+          inputs.image-content-hash != '' && inputs.suite-code-hash != '' &&
+          needs.e2e-test.result == 'success' }}
+    needs: [e2e-test]
+    runs-on:
+      - codebuild-runner-${{ github.run_id }}-${{ github.run_attempt }}
+        fleet:default-runner
+        buildspec-override:true
+    steps:
+      - uses: actions/checkout@v6
+      - uses: ./.github/actions/record-test-pass
+        with:
+          suite: autogluon/sagemaker
+          image-content-hash: ${{ inputs.image-content-hash }}
+          suite-code-hash: ${{ inputs.suite-code-hash }}
+          ci-image-uri: ${{ inputs.image-uri }}
+          ci-images-table-account-id: ${{ vars.CI_IMAGES_TABLE_ACCOUNT_ID }}
diff --git a/.github/workflows/autogluon.tests-unit.yml b/.github/workflows/autogluon.tests-unit.yml
new file mode 100644
index 000000000000..0d054d6b2bfb
--- /dev/null
+++ b/.github/workflows/autogluon.tests-unit.yml
@@ -0,0 +1,33 @@
+name: Reusable AutoGluon Unit Tests
+
+on:
+  workflow_call: {}
+
+permissions:
+  contents: read
+
+jobs:
+  unit-test:
+    runs-on:
+      - codebuild-runner-${{ github.run_id }}-${{ github.run_attempt }}
+        fleet:default-runner
+        buildspec-override:true
+    timeout-minutes: 15
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Install test dependencies
+        run: |
+          uv venv --python 3.12
+          source .venv/bin/activate
+          uv pip install "flask==3.1.3" pytest
+
+      - name: Validate unified entrypoint
+        run: bash -n scripts/docker/autogluon/sagemaker_entrypoint.sh
+
+      - name: Run serving adapter unit tests
+        run: |
+          source .venv/bin/activate
+          PYTHONPATH="${{ github.workspace }}/test" \
+            uv run --active --no-project pytest -v --tb=short -rA --noconftest \
+            test/autogluon/inference/test_server.py
diff --git a/docker/autogluon/1.6/requirements.cpu.in b/docker/autogluon/1.6/requirements.cpu.in
new file mode 100644
index 000000000000..dd807e408b0a
--- /dev/null
+++ b/docker/autogluon/1.6/requirements.cpu.in
@@ -0,0 +1,112 @@
+# Exact packages added to or changed from the PyTorch 2.13 CPU SageMaker DLC.
+absl-py==2.5.0
+accelerate==1.15.0
+adagio==0.2.6
+aiohttp-cors==0.8.1
+autogluon==1.6.3
+autogluon-common==1.6.3
+autogluon-core==1.6.3
+autogluon-features==1.6.3
+autogluon-multimodal==1.6.3
+autogluon-tabular==1.6.3
+autogluon-timeseries==1.6.3
+catboost==1.2.10
+chronos-forecasting==2.3.2
+colorama==0.4.6
+colorful==0.5.8
+colorlog==6.12.0
+coreforecast==0.0.16
+datasets==5.0.1
+defusedxml==0.7.1
+distlib==0.4.3
+einx==0.4.3
+evaluate==0.4.6
+formulaic==1.2.2
+frozendict==2.4.7
+fugue==0.9.7
+future==1.0.0
+gdown==6.4.0
+gluonts==0.17.0
+google-api-core==2.37.0
+googleapis-common-protos==1.75.3
+graphviz==0.21
+grpcio==1.84.0
+hf-xet==1.6.0
+huggingface-hub==1.32.0
+hyperopt==0.2.7
+interface-meta==2.0.1
+jsonschema==4.23.0
+lazy-loader==0.5
+lightgbm==4.7.0
+lightning==2.6.6
+lightning-utilities==0.15.3
+loguru==0.7.3
+markdown==3.10.3
+mlforecast==0.14.0
+model-index==0.1.11
+multiprocess==0.70.19
+nlpaug==1.1.11
+nltk==3.10.3
+nvidia-ml-py3==7.352.0
+opencensus==0.11.4
+opencensus-context==0.1.3
+opendatalab==0.0.10
+openmim==0.3.9
+opentelemetry-api==1.44.0
+opentelemetry-exporter-prometheus==0.65b0
+opentelemetry-sdk==1.44.0
+opentelemetry-semantic-conventions==0.65b0
+openxlab==0.0.11
+optuna==5.0.0
+ordered-set==4.1.0
+orjson==3.12.0
+patsy==1.0.3
+pbr==7.0.3
+pdf2image==1.17.0
+peft==0.19.1
+prometheus-client==0.26.0
+proto-plus==1.28.4
+py-spy==0.4.2
+py4j==0.10.9.9
+pycryptodome==3.23.0
+pysocks==1.7.1
+pytesseract==0.3.13
+python-discovery==1.6.0
+pytorch-lightning==2.6.6
+pytorch-metric-learning==2.8.1
+ray==2.58.0
+regex==2026.9.10
+safetensors==0.8.0
+scikit-image==0.25.2
+sentencepiece==0.2.2
+seqeval==1.2.2
+statsforecast==2.0.1
+statsmodels==0.15.0
+stevedore==5.4.1
+tensorboard==2.21.0
+tensorboard-data-server==0.7.2
+tensorboardx==2.6.5
+text-unidecode==1.3
+tifffile==2026.9.15
+timm==1.0.3
+tokenizers==0.22.2
+toolz==0.12.1
+torchmetrics==1.7.4
+transformers==5.14.1
+triad==1.0.2
+utilsforecast==0.2.11
+virtualenv==21.7.11
+window-ops==0.0.15
+xgboost-cpu==3.3.0
+xxhash==4.0.1
+
+# Temporary security overrides inherited from the published PyTorch 2.13
+# SageMaker DLC. The source base is already fixed by DLC PR #6749; remove these
+# after the published base tag includes that change. MLflow 3.16 relaxes its
+# cryptography cap and its three packages must remain version-aligned.
+cryptography==50.0.1
+mlflow==3.16.0
+mlflow-skinny==3.16.0
+mlflow-tracing==3.16.0
+sqlparse==0.6.0
+tornado==6.5.10
diff --git a/docker/autogluon/1.6/requirements.cuda.in b/docker/autogluon/1.6/requirements.cuda.in
new file mode 100644
index 000000000000..cb0648af8d83
--- /dev/null
+++ b/docker/autogluon/1.6/requirements.cuda.in
@@ -0,0 +1,112 @@
+# Exact packages added to or changed from the PyTorch 2.13 CUDA SageMaker DLC.
+absl-py==2.5.0
+accelerate==1.15.0
+adagio==0.2.6
+aiohttp-cors==0.8.1
+autogluon==1.6.3
+autogluon-common==1.6.3
+autogluon-core==1.6.3
+autogluon-features==1.6.3
+autogluon-multimodal==1.6.3
+autogluon-tabular==1.6.3
+autogluon-timeseries==1.6.3
+catboost==1.2.10
+chronos-forecasting==2.3.2
+colorama==0.4.6
+colorful==0.5.8
+colorlog==6.12.0
+coreforecast==0.0.16
+datasets==5.0.1
+defusedxml==0.7.1
+distlib==0.4.3
+einx==0.4.3
+evaluate==0.4.6
+formulaic==1.2.2
+frozendict==2.4.7
+fugue==0.9.7
+future==1.0.0
+gdown==6.4.0
+gluonts==0.17.0
+google-api-core==2.30.3
+googleapis-common-protos==1.75.3
+graphviz==0.21
+grpcio==1.84.0
+hf-xet==1.6.0
+huggingface-hub==1.32.0
+hyperopt==0.2.7
+interface-meta==2.0.1
+jsonschema==4.23.0
+lazy-loader==0.5
+lightgbm==4.7.0
+lightning==2.6.6
+lightning-utilities==0.15.3
+loguru==0.7.3
+markdown==3.10.3
+mlforecast==0.14.0
+model-index==0.1.11
+multiprocess==0.70.19
+nlpaug==1.1.11
+nltk==3.10.3
+nvidia-ml-py3==7.352.0
+opencensus==0.11.4
+opencensus-context==0.1.3
+opendatalab==0.0.10
+openmim==0.3.9
+opentelemetry-api==1.44.0
+opentelemetry-exporter-prometheus==0.65b0
+opentelemetry-sdk==1.44.0
+opentelemetry-semantic-conventions==0.65b0
+openxlab==0.0.11
+optuna==5.0.0
+ordered-set==4.1.0
+orjson==3.12.0
+patsy==1.0.3
+pbr==7.0.3
+pdf2image==1.17.0
+peft==0.19.1
+prometheus-client==0.26.0
+proto-plus==1.28.4
+py-spy==0.4.2
+py4j==0.10.9.9
+pycryptodome==3.23.0
+pysocks==1.7.1
+pytesseract==0.3.13
+python-discovery==1.6.0
+pytorch-lightning==2.6.6
+pytorch-metric-learning==2.8.1
+ray==2.58.0
+regex==2026.9.10
+safetensors==0.8.0
+scikit-image==0.25.2
+scipy==1.15.3
+sentencepiece==0.2.2
+seqeval==1.2.2
+statsforecast==2.0.3
+statsmodels==0.15.0
+stevedore==5.4.1
+tensorboard==2.21.0
+tensorboard-data-server==0.7.2
+tensorboardx==2.6.5
+text-unidecode==1.3
+tifffile==2026.9.15
+timm==1.0.3
+tokenizers==0.22.2
+toolz==0.12.1
+torchmetrics==1.7.4
+transformers==5.14.1
+triad==1.0.2
+utilsforecast==0.2.11
+virtualenv==21.7.11
+window-ops==0.0.15
+xgboost-cpu==3.3.0
+xxhash==4.0.1
+
+# Temporary security overrides inherited from the published PyTorch 2.13
+# SageMaker DLC. The source base is already fixed by DLC PR #6749; remove these
+# after the published base tag includes that change. MLflow 3.16 relaxes its
+# cryptography cap and its three packages must remain version-aligned.
+cryptography==50.0.1
+mlflow==3.16.0
+mlflow-skinny==3.16.0
+mlflow-tracing==3.16.0
+tornado==6.5.10
diff --git a/docker/autogluon/Dockerfile b/docker/autogluon/Dockerfile
new file mode 100644
index 000000000000..e81dc01c13fc
--- /dev/null
+++ b/docker/autogluon/Dockerfile
@@ -0,0 +1,93 @@
+# AutoGluon SageMaker DLC, layered on an AWS PyTorch training DLC
+# (Amazon Linux 2023). The image supports both SageMaker commands:
+# `train` uses the inherited training toolkit and `serve` uses the lightweight
+# AutoGluon HTTP adapter below.
+#
+# BASE_IMAGE is supplied by:
+# - .github/config/image/autogluon/1.6-sagemaker-cpu.yml
+# - .github/config/image/autogluon/1.6-sagemaker-cuda.yml
+ARG BASE_IMAGE
+
+FROM ${BASE_IMAGE} AS sagemaker
+
+ARG REQUIREMENTS_FILE
+ARG FRAMEWORK=autogluon
+ARG FRAMEWORK_VERSION=1.6.3
+ARG CONTAINER_TYPE=general
+ARG DLC_MAJOR_VERSION=1
+ARG DLC_MINOR_VERSION=0
+ARG VENV_PYTHON=/opt/venv/bin/python
+
+LABEL maintainer="Amazon AI"
+LABEL dlc_major_version="${DLC_MAJOR_VERSION}"
+LABEL dlc_minor_version="${DLC_MINOR_VERSION}"
+LABEL framework="autogluon"
+LABEL framework_version="${FRAMEWORK_VERSION}"
+# Allow SageMaker to select the listening port through SAGEMAKER_BIND_TO_PORT.
+LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
+# AutoGluon serves one model artifact per container; SageMaker MME is unsupported.
+LABEL com.amazonaws.sagemaker.capabilities.multi-models=false
+
+# jq for the inherited SageMaker hostname setup, rsync for Ray file sync,
+# poppler-utils for pdf2image (AutoMM documents).
+# AL2023 has no tesseract package, so pytesseract-based AutoMM OCR is unavailable.
+RUN dnf install -y jq rsync poppler-utils && dnf clean all
+
+# REQUIREMENTS_FILE is supplied by the matching CPU/CUDA image config. It
+# contains exact pins only for packages added to or changed from that PyTorch
+# DLC base.
+COPY ${REQUIREMENTS_FILE} /tmp/autogluon-requirements.in
+RUN uv pip install --python ${VENV_PYTHON} \
+  --no-deps \
+  -r /tmp/autogluon-requirements.in \
+  && rm /tmp/autogluon-requirements.in \
+  && uv cache clean
+
+# Some GPU base images include Transformer Engine. It is unused by AutoGluon,
+# and peft imports it at load time, which fails without an NVIDIA driver
+# (libcuda.so.1). This is a no-op when the packages are absent, including on CPU.
+RUN TE_PKGS=$(uv pip list --python ${VENV_PYTHON} 2>/dev/null | awk '{print $1}' | grep -i '^transformer-engine' || true) \
+  && if [ -n "${TE_PKGS}" ]; then uv pip uninstall --python ${VENV_PYTHON} ${TE_PKGS}; fi
+
+RUN uv pip check --python ${VENV_PYTHON}
+
+# A deliberately small SageMaker adapter. User handler code remains in the
+# model artifact (/opt/ml/model/code) and keeps the established SageMaker
+# inference-function contract used by AutoGluon Cloud.
+COPY scripts/docker/autogluon/server.py /opt/autogluon-server/server.py
+COPY scripts/docker/autogluon/gunicorn.conf.py /opt/autogluon-server/gunicorn.conf.py
+COPY --chmod=755 scripts/docker/autogluon/install_requirements.py /opt/autogluon-server/install_requirements.py
+COPY --chmod=755 scripts/docker/autogluon/sagemaker_entrypoint.sh /usr/local/bin/autogluon-sagemaker-entrypoint.sh
+
+# Telemetry: report this image's framework instead of the base's.
+COPY ./scripts/docker/telemetry/deep_learning_container.py /usr/local/bin/deep_learning_container.py
+COPY ./scripts/docker/telemetry/bash_telemetry.sh.template /tmp/bash_telemetry.sh.template
+RUN chmod +x /usr/local/bin/deep_learning_container.py \
+  && sed -e "s/{{FRAMEWORK}}/${FRAMEWORK}/g" \
+    -e "s/{{FRAMEWORK_VERSION}}/${FRAMEWORK_VERSION}/g" \
+    -e "s/{{CONTAINER_TYPE}}/${CONTAINER_TYPE}/g" \
+    /tmp/bash_telemetry.sh.template >/usr/local/bin/bash_telemetry.sh \
+  && chmod +x /usr/local/bin/bash_telemetry.sh \
+  && rm /tmp/bash_telemetry.sh.template
+
+ENV DLC_CONTAINER_TYPE=${CONTAINER_TYPE}
+
+# OSS compliance for the added packages, plus AutoGluon's third-party license bundle.
+COPY ./scripts/docker/common/setup_oss_compliance.sh /tmp/setup_oss_compliance.sh
+RUN bash /tmp/setup_oss_compliance.sh python3 && rm /tmp/setup_oss_compliance.sh \
+  && curl -fsSL -o /licenses-autogluon.txt https://autogluon.s3.us-west-2.amazonaws.com/licenses/THIRD-PARTY-LICENSES.txt
+
+# OS security refresh; CACHE_REFRESH busts the cache daily.
+ARG CACHE_REFRESH=0
+RUN echo "cache refresh: ${CACHE_REFRESH}" \
+  && dnf upgrade -y --security --releasever latest \
+  && dnf clean all \
+  && rm -rf /tmp/tmp* /tmp/pip-* /tmp/uv-*
+
+# The security refresh may replace /etc/bashrc, so restore the telemetry hook.
+RUN echo 'source /usr/local/bin/bash_telemetry.sh' >>/etc/bashrc \
+  && echo 'source /usr/local/bin/bash_telemetry.sh' >>/root/.bashrc
+
+EXPOSE 8080
+ENTRYPOINT ["/usr/local/bin/autogluon-sagemaker-entrypoint.sh"]
+CMD ["bash"]
\ No newline at end of file
diff --git a/scripts/docker/autogluon/gunicorn.conf.py b/scripts/docker/autogluon/gunicorn.conf.py
new file mode 100644
index 000000000000..47958fd83f43
--- /dev/null
+++ b/scripts/docker/autogluon/gunicorn.conf.py
@@ -0,0 +1,22 @@
+"""Gunicorn configuration for the AutoGluon SageMaker server."""
+
+import os
+
+bind = f"0.0.0.0:{os.getenv('SAGEMAKER_BIND_TO_PORT', '8080')}"
+workers = int(os.getenv("SAGEMAKER_MODEL_SERVER_WORKERS", "1"))
+timeout = int(os.getenv("SAGEMAKER_MODEL_SERVER_TIMEOUT", "60"))
+graceful_timeout = timeout
+
+worker_class = "sync"
+
+accesslog = "-"
+errorlog = "-"
+capture_output = True
+raw_log_level = os.getenv("SAGEMAKER_CONTAINER_LOG_LEVEL", "info").strip().lower() or "info"
+loglevel = {
+    "10": "debug",
+    "20": "info",
+    "30": "warning",
+    "40": "error",
+    "50": "critical",
+}.get(raw_log_level, raw_log_level)
diff --git a/scripts/docker/autogluon/install_requirements.py b/scripts/docker/autogluon/install_requirements.py
new file mode 100755
index 000000000000..263cb5cab294
--- /dev/null
+++ b/scripts/docker/autogluon/install_requirements.py
@@ -0,0 +1,78 @@
+#!/opt/venv/bin/python
+"""Install model-artifact requirements once before Gunicorn starts."""
+
+from __future__ import annotations
+
+import logging
+import os
+import re
+import subprocess
+import sys
+from pathlib import Path
+from urllib.parse import quote, urlparse, urlunparse
+
+LOGGER = logging.getLogger("autogluon-serving")
+
+
+def _codeartifact_index(repository_arn: str) -> str:
+    # Adapted from scripts/docker/ray/sagemaker_serve.py.
+    match = re.fullmatch(
+        r"arn:([^:]+):codeartifact:([^:]+):([^:]+):repository/([^/]+)/(.+)",
+        repository_arn,
+    )
+    if not match:
+        raise ValueError(f"Invalid CA_REPOSITORY_ARN: {repository_arn!r}")
+
+    import boto3
+
+    _, region, account, domain, repository = match.groups()
+    client = boto3.client("codeartifact", region_name=region)
+    arguments = {
+        "domain": domain,
+        "domainOwner": account,
+    }
+    token = client.get_authorization_token(**arguments)["authorizationToken"]
+    endpoint = client.get_repository_endpoint(
+        **arguments,
+        repository=repository,
+        format="pypi",
+    )["repositoryEndpoint"]
+
+    parsed = urlparse(endpoint)
+    authenticated = parsed._replace(netloc=f"aws:{quote(token, safe='')}@{parsed.netloc}")
+    return urlunparse(authenticated._replace(path=f"{parsed.path.rstrip('/')}/simple/"))
+
+
+def install_requirements() -> None:
+    requirements_path = (
+        Path(os.getenv("SAGEMAKER_BASE_DIR", "/opt/ml")) / "model" / "code" / "requirements.txt"
+    )
+    if not requirements_path.is_file():
+        return
+
+    command = [
+        "uv",
+        "pip",
+        "install",
+        "--python",
+        sys.executable,
+        "--no-cache",
+        "-r",
+        str(requirements_path),
+    ]
+    environment = os.environ.copy()
+    repository_arn = os.getenv("CA_REPOSITORY_ARN")
+    if repository_arn:
+        environment["UV_INDEX_URL"] = _codeartifact_index(repository_arn)
+
+    LOGGER.info("Installing packages from %s", requirements_path)
+    subprocess.check_call(command, env=environment)
+
+
+def main() -> None:
+    logging.basicConfig(level=logging.INFO)
+    install_requirements()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/docker/autogluon/sagemaker_entrypoint.sh b/scripts/docker/autogluon/sagemaker_entrypoint.sh
new file mode 100755
index 000000000000..7bfb08aa5eb0
--- /dev/null
+++ b/scripts/docker/autogluon/sagemaker_entrypoint.sh
@@ -0,0 +1,29 @@
+#!/usr/bin/env bash
+# Unified AutoGluon SageMaker entrypoint. SageMaker invokes training containers
+# with `train` and inference containers with `serve`.
+set -euo pipefail
+
+case "${1:-}" in
+  train)
+    # Preserve the PyTorch training DLC's hostname workaround, CUDA setup, and
+    # SageMaker training-toolkit launcher.
+    cd /
+    exec bash -m start_with_right_hostname.sh "$@"
+    ;;
+  serve)
+    shift
+    # Serving does not start a login shell, so fire telemetry explicitly.
+    bash /usr/local/bin/bash_telemetry.sh >/dev/null 2>&1 || true
+    # Install model-artifact dependencies once, before Gunicorn forks workers.
+    /opt/autogluon-server/install_requirements.py
+    # Delegate CUDA forward compatibility to the inherited generic entrypoint.
+    exec /usr/local/bin/entrypoint.sh gunicorn \
+      --config /opt/autogluon-server/gunicorn.conf.py \
+      --chdir /opt/autogluon-server \
+      "$@" \
+      server:app
+    ;;
+  *)
+    exec /usr/local/bin/entrypoint.sh "$@"
+    ;;
+esac
diff --git a/scripts/docker/autogluon/server.py b/scripts/docker/autogluon/server.py
new file mode 100644
index 000000000000..4152fb397582
--- /dev/null
+++ b/scripts/docker/autogluon/server.py
@@ -0,0 +1,99 @@
+"""SageMaker HTTP adapter for AutoGluon inference handlers."""
+
+from __future__ import annotations
+
+import importlib.util
+import logging
+import os
+import sys
+from pathlib import Path
+from types import ModuleType
+
+from flask import Flask, Response, jsonify, request
+
+MODEL_DIR = Path(os.getenv("SAGEMAKER_BASE_DIR", "/opt/ml")) / "model"
+CODE_DIR = MODEL_DIR / "code"
+PROGRAM = os.getenv("SAGEMAKER_PROGRAM", "inference.py").strip() or "inference.py"
+DEFAULT_ACCEPT = (
+    os.getenv("SAGEMAKER_DEFAULT_INVOCATIONS_ACCEPT", "application/json").strip()
+    or "application/json"
+)
+LOG_LEVEL = os.getenv("SAGEMAKER_CONTAINER_LOG_LEVEL", "INFO").strip() or "INFO"
+logging.basicConfig(level=int(LOG_LEVEL) if LOG_LEVEL.isdigit() else LOG_LEVEL.upper())
+LOGGER = logging.getLogger("autogluon-serving")
+
+
+def _load_handler() -> ModuleType:
+    """Load the user-provided inference module from the model artifact."""
+    program = Path(PROGRAM)
+    path = program if program.is_absolute() else CODE_DIR / program
+    if not path.is_file():
+        raise RuntimeError(f"AutoGluon inference handler not found: {path}")
+
+    sys.path.insert(0, str(path.parent))
+    spec = importlib.util.spec_from_file_location("autogluon_user_handler", path)
+    if spec is None or spec.loader is None:
+        raise RuntimeError(f"Unable to import AutoGluon inference handler: {path}")
+
+    handler = importlib.util.module_from_spec(spec)
+    sys.modules[spec.name] = handler
+    try:
+        spec.loader.exec_module(handler)
+    except Exception:
+        sys.modules.pop(spec.name, None)
+        raise
+    return handler
+
+
+def _media_type(value: str | None, default: str) -> str:
+    value = (value or default).split(",", 1)[0].split(";", 1)[0].strip().lower()
+    return default if not value or value == "*/*" else value
+
+
+def _request_body(body: bytes, content_type: str) -> bytes | str:
+    if content_type.startswith("text/") or content_type in (
+        "application/json",
+        "application/jsonl",
+    ):
+        return body.decode("utf-8")
+    return body
+
+
+HANDLER = _load_handler()
+if not callable(getattr(HANDLER, "model_fn", None)):
+    raise TypeError("AutoGluon inference handler must define model_fn")
+if not callable(getattr(HANDLER, "transform_fn", None)):
+    raise TypeError("AutoGluon inference handler must define transform_fn")
+MODEL = HANDLER.model_fn(str(MODEL_DIR))
+app = Flask(__name__)
+
+
+@app.get("/ping")
+def ping() -> Response:
+    return Response(status=200)
+
+
+@app.post("/invocations")
+def invocations() -> Response:
+    content_type = _media_type(request.headers.get("content-type"), "application/json")
+    accept = _media_type(request.headers.get("accept"), DEFAULT_ACCEPT)
+
+    try:
+        body = _request_body(request.get_data(cache=False), content_type)
+        result = HANDLER.transform_fn(MODEL, body, content_type, accept)
+        if not isinstance(result, tuple) or len(result) != 2:
+            raise TypeError("transform_fn must return (body, content_type)")
+        output, output_content_type = result
+    except ValueError as error:
+        return jsonify(detail=str(error)), 400
+    except Exception:
+        LOGGER.exception("AutoGluon inference failed")
+        return jsonify(detail="inference failed"), 500
+
+    output_content_type = _media_type(output_content_type, accept)
+    if isinstance(output, (bytes, str)):
+        return Response(response=output, content_type=output_content_type)
+    return (
+        jsonify(detail=f"handler returned {type(output).__name__} for {output_content_type}"),
+        500,
+    )
diff --git a/scripts/docker/telemetry/deep_learning_container.py b/scripts/docker/telemetry/deep_learning_container.py
index 6601d5cc86d1..9c586ddf098d 100755
--- a/scripts/docker/telemetry/deep_learning_container.py
+++ b/scripts/docker/telemetry/deep_learning_container.py
@@ -230,6 +230,7 @@ def parse_args():
     parser.add_argument(
         "--framework",
         choices=[
+            "autogluon",
             "tensorflow",
             "mxnet",
             "pytorch",
diff --git a/test/autogluon/inference/test_server.py b/test/autogluon/inference/test_server.py
new file mode 100644
index 000000000000..063e6743412b
--- /dev/null
+++ b/test/autogluon/inference/test_server.py
@@ -0,0 +1,371 @@
+"""CPU-only tests for the AutoGluon SageMaker server."""
+
+from __future__ import annotations
+
+import importlib.util
+import sys
+import time
+import types
+from pathlib import Path
+
+import pytest
+
+SERVER_DIR = Path(__file__).resolve().parents[3] / "scripts" / "docker" / "autogluon"
+SERVER_PATH = SERVER_DIR / "server.py"
+INSTALL_REQUIREMENTS_PATH = SERVER_DIR / "install_requirements.py"
+GUNICORN_CONFIG_PATH = SERVER_DIR / "gunicorn.conf.py"
+
+SERVING_ENVIRONMENT_VARIABLES = {
+    "SAGEMAKER_PROGRAM",
+    "SAGEMAKER_BIND_TO_PORT",
+    "SAGEMAKER_MODEL_SERVER_WORKERS",
+    "SAGEMAKER_MODEL_SERVER_TIMEOUT",
+    "SAGEMAKER_DEFAULT_INVOCATIONS_ACCEPT",
+    "SAGEMAKER_CONTAINER_LOG_LEVEL",
+    "SAGEMAKER_BASE_DIR",
+    "CA_REPOSITORY_ARN",
+}
+
+
+def _load(path: Path, prefix: str):
+    module_name = f"{prefix}_{time.time_ns()}"
+    spec = importlib.util.spec_from_file_location(module_name, path)
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[module_name] = module
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+def _clear_serving_environment(monkeypatch):
+    for name in SERVING_ENVIRONMENT_VARIABLES:
+        monkeypatch.delenv(name, raising=False)
+
+
+def _write_handler(base_dir: Path, source: str, program: str = "inference.py") -> Path:
+    model_dir = base_dir / "model"
+    code_dir = model_dir / "code"
+    code_dir.mkdir(parents=True)
+    (code_dir / program).write_text(source)
+    return model_dir
+
+
+def _load_server(monkeypatch, base_dir: Path, program: str | None = None):
+    _clear_serving_environment(monkeypatch)
+    monkeypatch.setenv("SAGEMAKER_BASE_DIR", str(base_dir))
+    if program is not None:
+        monkeypatch.setenv("SAGEMAKER_PROGRAM", program)
+    monkeypatch.syspath_prepend(str(SERVER_DIR))
+    return _load(SERVER_PATH, "autogluon_server")
+
+
+def _request(app, method: str, path: str, **kwargs):
+    with app.test_client() as client:
+        return client.open(path, method=method, **kwargs)
+
+
+def test_model_artifact_handler_receives_normalized_json_headers(monkeypatch, tmp_path):
+    model_dir = _write_handler(
+        tmp_path,
+        """
+import json
+
+def model_fn(model_dir):
+    return {"model_dir": model_dir}
+
+def transform_fn(model, body, content_type, accept):
+    return json.dumps({
+        "body": body,
+        "content_type": content_type,
+        "accept": accept,
+        "model_dir": model["model_dir"],
+    }), "application/json"
+""",
+    )
+    server = _load_server(monkeypatch, tmp_path)
+
+    assert _request(server.app, "GET", "/ping").data == b""
+    response = _request(
+        server.app,
+        "POST",
+        "/invocations",
+        data='[{"feature": 1}]',
+        headers={
+            "content-type": "application/json; charset=utf-8",
+            "accept": "application/json, */*",
+        },
+    )
+
+    assert response.status_code == 200
+    assert response.get_json() == {
+        "body": '[{"feature": 1}]',
+        "content_type": "application/json",
+        "accept": "application/json",
+        "model_dir": str(model_dir),
+    }
+
+
+def test_binary_request_and_response_are_not_decoded(monkeypatch, tmp_path):
+    _write_handler(
+        tmp_path,
+        """
+def model_fn(model_dir):
+    return None
+
+def transform_fn(model, body, content_type, accept):
+    assert isinstance(body, bytes)
+    assert content_type == "application/x-parquet"
+    return body[::-1], "application/x-parquet"
+""",
+    )
+    server = _load_server(monkeypatch, tmp_path)
+
+    response = _request(
+        server.app,
+        "POST",
+        "/invocations",
+        data=b"parquet-bytes",
+        headers={"content-type": "application/x-parquet", "accept": "application/x-parquet"},
+    )
+
+    assert response.status_code == 200
+    assert response.headers["content-type"] == "application/x-parquet"
+    assert response.data == b"setyb-teuqrap"
+
+
+@pytest.mark.parametrize(
+    "content_type,body",
+    [
+        ("application/json", '{"feature": 1}'),
+        ("application/jsonl", '{"feature": 1}\n{"feature": 2}'),
+        ("text/csv", "feature\n1"),
+    ],
+)
+def test_text_request_body_is_decoded(monkeypatch, tmp_path, content_type, body):
+    _write_handler(
+        tmp_path,
+        """
+def model_fn(model_dir):
+    return None
+
+def transform_fn(model, body, content_type, accept):
+    assert isinstance(body, str)
+    return body, content_type
+""",
+    )
+    server = _load_server(monkeypatch, tmp_path)
+
+    response = _request(
+        server.app,
+        "POST",
+        "/invocations",
+        data=body,
+        headers={"content-type": content_type},
+    )
+
+    assert response.status_code == 200
+    assert response.text == body
+    assert response.headers["content-type"] == content_type
+
+
+def test_default_accept_environment_variable(monkeypatch, tmp_path):
+    _write_handler(
+        tmp_path,
+        """
+def model_fn(model_dir):
+    return None
+
+def transform_fn(model, body, content_type, accept):
+    return accept, "text/plain"
+""",
+    )
+    _clear_serving_environment(monkeypatch)
+    monkeypatch.setenv("SAGEMAKER_BASE_DIR", str(tmp_path))
+    monkeypatch.setenv("SAGEMAKER_DEFAULT_INVOCATIONS_ACCEPT", "text/csv")
+    monkeypatch.syspath_prepend(str(SERVER_DIR))
+    server = _load(SERVER_PATH, "autogluon_server")
+
+    response = _request(server.app, "POST", "/invocations", data=b"input")
+
+    assert response.status_code == 200
+    assert response.text == "text/csv"
+
+
+def test_sagemaker_program_selects_custom_handler(monkeypatch, tmp_path):
+    _write_handler(
+        tmp_path,
+        """
+def model_fn(model_dir):
+    return model_dir
+
+def transform_fn(model, body, content_type, accept):
+    return model, "text/plain"
+""",
+        program="tabular_serve.py",
+    )
+    server = _load_server(monkeypatch, tmp_path, program="tabular_serve.py")
+
+    response = _request(server.app, "POST", "/invocations", data=b"input")
+
+    assert response.status_code == 200
+    assert response.text == str(tmp_path / "model")
+
+
+def test_handler_module_is_registered_during_execution(monkeypatch, tmp_path):
+    _write_handler(
+        tmp_path,
+        """
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+@dataclass
+class Model:
+    model_dir: str
+
+def model_fn(model_dir):
+    return Model(model_dir)
+
+def transform_fn(model, body, content_type, accept):
+    return model.model_dir, "text/plain"
+""",
+    )
+    server = _load_server(monkeypatch, tmp_path)
+
+    response = _request(server.app, "POST", "/invocations", data=b"input")
+
+    assert response.status_code == 200
+    assert response.text == str(tmp_path / "model")
+
+
+def test_handler_value_error_is_a_client_error(monkeypatch, tmp_path):
+    _write_handler(
+        tmp_path,
+        """
+def model_fn(model_dir):
+    return None
+
+def transform_fn(model, body, content_type, accept):
+    raise ValueError("unsupported payload")
+""",
+    )
+    server = _load_server(monkeypatch, tmp_path)
+
+    response = _request(server.app, "POST", "/invocations", data=b"bad")
+
+    assert response.status_code == 400
+    assert response.get_json()["detail"] == "unsupported payload"
+
+
+def test_gunicorn_environment_configuration(monkeypatch):
+    _clear_serving_environment(monkeypatch)
+    monkeypatch.setenv("SAGEMAKER_BIND_TO_PORT", "9000")
+    monkeypatch.setenv("SAGEMAKER_MODEL_SERVER_WORKERS", "3")
+    monkeypatch.setenv("SAGEMAKER_MODEL_SERVER_TIMEOUT", "120")
+    monkeypatch.setenv("SAGEMAKER_CONTAINER_LOG_LEVEL", "10")
+
+    gunicorn_config = _load(GUNICORN_CONFIG_PATH, "autogluon_gunicorn_config")
+
+    assert gunicorn_config.bind == "0.0.0.0:9000"
+    assert gunicorn_config.workers == 3
+    assert gunicorn_config.timeout == 120
+    assert gunicorn_config.graceful_timeout == 120
+    assert gunicorn_config.loglevel == "debug"
+    assert gunicorn_config.worker_class == "sync"
+
+
+def test_requirements_installed_once_with_codeartifact_index(monkeypatch, tmp_path):
+    model_dir = _write_handler(
+        tmp_path,
+        """
+def model_fn(model_dir):
+    return None
+
+def transform_fn(model, body, content_type, accept):
+    return body
+""",
+    )
+    requirements = model_dir / "code" / "requirements.txt"
+    requirements.write_text("customer-package==1.2.3\n")
+    _clear_serving_environment(monkeypatch)
+    monkeypatch.setenv("SAGEMAKER_BASE_DIR", str(tmp_path))
+    monkeypatch.setenv(
+        "CA_REPOSITORY_ARN",
+        "arn:aws:codeartifact:us-west-2:123456789012:repository/domain/repository",
+    )
+    monkeypatch.syspath_prepend(str(SERVER_DIR))
+    installer = _load(INSTALL_REQUIREMENTS_PATH, "autogluon_install_requirements")
+    monkeypatch.setattr(
+        installer,
+        "_codeartifact_index",
+        lambda arn: "https://aws:secret@example.com/pypi/repository/simple/",
+    )
+    calls = []
+    monkeypatch.setattr(
+        installer.subprocess,
+        "check_call",
+        lambda command, **kwargs: calls.append((command, kwargs)),
+    )
+
+    installer.install_requirements()
+
+    assert len(calls) == 1
+    command, kwargs = calls[0]
+    assert command == [
+        "uv",
+        "pip",
+        "install",
+        "--python",
+        sys.executable,
+        "--no-cache",
+        "-r",
+        str(requirements),
+    ]
+    assert "secret" not in " ".join(command)
+    assert kwargs["env"]["UV_INDEX_URL"] == (
+        "https://aws:secret@example.com/pypi/repository/simple/"
+    )
+
+
+def test_codeartifact_arn_is_resolved_without_logging_credentials(monkeypatch):
+    monkeypatch.syspath_prepend(str(SERVER_DIR))
+    installer = _load(INSTALL_REQUIREMENTS_PATH, "autogluon_install_requirements")
+    calls = []
+
+    class CodeArtifactClient:
+        def get_authorization_token(self, **kwargs):
+            calls.append(("token", kwargs))
+            return {"authorizationToken": "token+/="}
+
+        def get_repository_endpoint(self, **kwargs):
+            calls.append(("endpoint", kwargs))
+            return {"repositoryEndpoint": "https://example.com/pypi/repository/"}
+
+    boto3 = types.SimpleNamespace(
+        client=lambda service, region_name: (
+            calls.append(("client", service, region_name)) or CodeArtifactClient()
+        )
+    )
+    monkeypatch.setitem(sys.modules, "boto3", boto3)
+
+    index = installer._codeartifact_index(
+        "arn:aws:codeartifact:us-west-2:123456789012:repository/domain/repository"
+    )
+
+    assert index == "https://aws:token%2B%2F%3D@example.com/pypi/repository/simple/"
+    assert calls == [
+        ("client", "codeartifact", "us-west-2"),
+        (
+            "token",
+            {"domain": "domain", "domainOwner": "123456789012"},
+        ),
+        (
+            "endpoint",
+            {
+                "domain": "domain",
+                "domainOwner": "123456789012",
+                "repository": "repository",
+                "format": "pypi",
+            },
+        ),
+    ]
diff --git a/test/autogluon/sagemaker/requirements.txt b/test/autogluon/sagemaker/requirements.txt
new file mode 100644
index 000000000000..521e63c93a43
--- /dev/null
+++ b/test/autogluon/sagemaker/requirements.txt
@@ -0,0 +1 @@
+sagemaker>=3.0.0
diff --git a/test/autogluon/sagemaker/resources/code/tabular/serve.py b/test/autogluon/sagemaker/resources/code/tabular/serve.py
new file mode 100644
index 000000000000..c2ad36d4fd3e
--- /dev/null
+++ b/test/autogluon/sagemaker/resources/code/tabular/serve.py
@@ -0,0 +1,23 @@
+"""Inference handler packaged with the trained AutoGluon tabular model."""
+
+from io import StringIO
+
+import pandas as pd
+from autogluon.tabular import TabularPredictor
+
+
+def model_fn(model_dir):
+    predictor = TabularPredictor.load(model_dir)
+    predictor.persist()
+    return predictor
+
+
+def transform_fn(model, request_body, input_content_type, output_content_type="application/json"):
+    if input_content_type != "application/json":
+        raise ValueError(f"unsupported input content type: {input_content_type}")
+    if output_content_type != "application/json":
+        raise ValueError(f"unsupported output content type: {output_content_type}")
+
+    data = pd.read_json(StringIO(request_body))
+    predictions = model.predict(data, as_pandas=True)
+    return predictions.to_frame(name=model.label).to_json(orient="records"), "application/json"
diff --git a/test/autogluon/sagemaker/resources/code/tabular/train.py b/test/autogluon/sagemaker/resources/code/tabular/train.py
new file mode 100644
index 000000000000..f4fd2cc945db
--- /dev/null
+++ b/test/autogluon/sagemaker/resources/code/tabular/train.py
@@ -0,0 +1,49 @@
+"""Train an AutoGluon tabular predictor and package its inference handler."""
+
+import os
+import shutil
+from pathlib import Path
+
+from autogluon.tabular import TabularDataset, TabularPredictor
+
+
+def first_file(directory):
+    return Path(directory) / min(os.listdir(directory))
+
+
+if __name__ == "__main__":
+    model_dir = Path(os.environ["SM_MODEL_DIR"])
+    num_gpus = int(os.environ.get("SM_NUM_GPUS", "0"))
+
+    if num_gpus:
+        import torch
+
+        assert torch.cuda.is_available(), "SM_NUM_GPUS > 0 but CUDA is unavailable"
+
+    fit_args = {
+        "hyperparameters": {
+            "GBM": {"num_boost_round": 20},
+            "NN_TORCH": {"num_epochs": 2},
+        },
+        "num_bag_folds": 3,
+        "num_bag_sets": 1,
+        "num_stack_levels": 0,
+    }
+    if num_gpus:
+        fit_args["num_gpus"] = num_gpus
+
+    predictor = TabularPredictor(
+        label="class",
+        eval_metric="roc_auc",
+        path=str(model_dir),
+    ).fit(
+        TabularDataset(first_file(os.environ["SM_CHANNEL_TRAIN"])),
+        **fit_args,
+    )
+
+    assert TabularPredictor.load(str(model_dir)).model_names(), "reloaded predictor has no models"
+
+    resource_dir = Path(__file__).parent
+    code_dir = model_dir / "code"
+    code_dir.mkdir(exist_ok=True)
+    shutil.copy2(resource_dir / "serve.py", code_dir / "serve.py")
diff --git a/test/autogluon/sagemaker/resources/code/timeseries/serve.py b/test/autogluon/sagemaker/resources/code/timeseries/serve.py
new file mode 100644
index 000000000000..abd7951492b9
--- /dev/null
+++ b/test/autogluon/sagemaker/resources/code/timeseries/serve.py
@@ -0,0 +1,27 @@
+"""Inference handler packaged with the trained AutoGluon time series model."""
+
+from io import StringIO
+
+import pandas as pd
+from autogluon.timeseries import TimeSeriesDataFrame, TimeSeriesPredictor
+
+
+def model_fn(model_dir):
+    predictor = TimeSeriesPredictor.load(model_dir)
+    predictor.persist()
+    return predictor
+
+
+def transform_fn(model, request_body, input_content_type, output_content_type="application/json"):
+    if input_content_type != "application/json":
+        raise ValueError(f"unsupported input content type: {input_content_type}")
+    if output_content_type != "application/json":
+        raise ValueError(f"unsupported output content type: {output_content_type}")
+
+    data = TimeSeriesDataFrame.from_data_frame(
+        pd.read_json(StringIO(request_body)),
+        id_column="item_id",
+        timestamp_column="timestamp",
+    )
+    predictions = model.predict(data).reset_index()
+    return predictions.to_json(orient="records", date_format="iso"), "application/json"
diff --git a/test/autogluon/sagemaker/resources/code/timeseries/train.py b/test/autogluon/sagemaker/resources/code/timeseries/train.py
new file mode 100644
index 000000000000..cf34bd831bb6
--- /dev/null
+++ b/test/autogluon/sagemaker/resources/code/timeseries/train.py
@@ -0,0 +1,60 @@
+"""Train an AutoGluon time series predictor and package its inference handler."""
+
+import os
+import shutil
+from pathlib import Path
+
+import pandas as pd
+from autogluon.timeseries import TimeSeriesDataFrame, TimeSeriesPredictor
+
+PREDICTION_LENGTH = 5
+
+
+def first_file(directory):
+    return Path(directory) / min(os.listdir(directory))
+
+
+if __name__ == "__main__":
+    model_dir = Path(os.environ["SM_MODEL_DIR"])
+    num_gpus = int(os.environ.get("SM_NUM_GPUS", "0"))
+
+    if num_gpus:
+        import torch
+
+        assert torch.cuda.is_available(), "SM_NUM_GPUS > 0 but CUDA is unavailable"
+
+    train_data = TimeSeriesDataFrame.from_data_frame(
+        pd.read_csv(first_file(os.environ["SM_CHANNEL_TRAIN"])),
+        id_column="item_id",
+        timestamp_column="timestamp",
+    )
+    predictor = TimeSeriesPredictor(
+        prediction_length=PREDICTION_LENGTH,
+        target="target",
+        path=str(model_dir),
+    ).fit(
+        train_data,
+        hyperparameters={
+            "DeepAR": {
+                "batch_size": 4,
+                "hidden_size": 8,
+                "max_epochs": 2,
+                "num_batches_per_epoch": 2,
+                "num_layers": 1,
+                "trainer_kwargs": {
+                    "accelerator": "gpu" if num_gpus else "cpu",
+                    "devices": 1,
+                },
+            },
+            "SeasonalNaive": {"seasonal_period": 6, "n_jobs": 1},
+        },
+        enable_ensemble=False,
+    )
+
+    reloaded = TimeSeriesPredictor.load(str(model_dir))
+    assert {"DeepAR", "SeasonalNaive"} <= set(reloaded.model_names())
+
+    resource_dir = Path(__file__).parent
+    code_dir = model_dir / "code"
+    code_dir.mkdir(exist_ok=True)
+    shutil.copy2(resource_dir / "serve.py", code_dir / "serve.py")
diff --git a/test/autogluon/sagemaker/resources/data/tabular/train.csv b/test/autogluon/sagemaker/resources/data/tabular/train.csv
new file mode 100644
index 000000000000..23f83dd758e0
--- /dev/null
+++ b/test/autogluon/sagemaker/resources/data/tabular/train.csv
@@ -0,0 +1,101 @@
+age,workclass,fnlwgt,education,education-num,marital-status,occupation,relationship,race,sex,capital-gain,capital-loss,hours-per-week,native-country,class
+25, Private,178478, Bachelors,13, Never-married, Tech-support, Own-child, White, Female,0,0,40, United-States, <=50K
+23, State-gov,61743, 5th-6th,3, Never-married, Transport-moving, Not-in-family, White, Male,0,0,35, United-States, <=50K
+46, Private,376789, HS-grad,9, Never-married, Other-service, Not-in-family, White, Male,0,0,15, United-States, <=50K
+55, ?,200235, HS-grad,9, Married-civ-spouse, ?, Husband, White, Male,0,0,50, United-States, >50K
+36, Private,224541, 7th-8th,4, Married-civ-spouse, Handlers-cleaners, Husband, White, Male,0,0,40, El-Salvador, <=50K
+51, Private,178054, Some-college,10, Married-civ-spouse, Sales, Husband, White, Male,0,0,40, ?, >50K
+33, Private,263561, Some-college,10, Married-civ-spouse, Craft-repair, Husband, White, Male,0,0,60, United-States, >50K
+46, Private,173613, HS-grad,9, Divorced, Adm-clerical, Not-in-family, White, Female,0,0,40, United-States, <=50K
+18, Private,214617, Some-college,10, Never-married, Handlers-cleaners, Own-child, White, Male,0,0,30, United-States, <=50K
+43, Private,84661, Assoc-voc,11, Married-civ-spouse, Sales, Husband, White, Male,0,0,45, United-States, <=50K
+41, Private,225892, Some-college,10, Married-civ-spouse, Craft-repair, Husband, White, Male,0,0,48, United-States, >50K
+41, Private,191547, Masters,14, Married-civ-spouse, Exec-managerial, Husband, White, Male,99999,0,55, United-States, >50K
+22, Private,150175, Some-college,10, Never-married, Adm-clerical, Own-child, White, Female,0,0,20, United-States, <=50K
+41, Private,227890, Some-college,10, Divorced, Craft-repair, Not-in-family, White, Male,0,0,46, United-States, >50K
+39, Private,80479, Bachelors,13, Divorced, Transport-moving, Not-in-family, White, Male,0,0,55, United-States, <=50K
+44, Local-gov,100479, Assoc-acdm,12, Married-civ-spouse, Prof-specialty, Husband, White, Male,0,0,48, United-States, <=50K
+37, Private,191524, Assoc-voc,11, Separated, Prof-specialty, Own-child, White, Female,0,0,38, United-States, <=50K
+39, Private,173175, Bachelors,13, Married-civ-spouse, Exec-managerial, Husband, White, Male,15024,0,50, United-States, >50K
+40, Private,72887, Assoc-voc,11, Married-civ-spouse, Machine-op-inspct, Husband, Asian-Pac-Islander, Male,0,0,40, United-States, >50K
+24, Private,295763, Bachelors,13, Never-married, Exec-managerial, Own-child, White, Female,0,0,50, United-States, <=50K
+61, ?,451327, Bachelors,13, Married-civ-spouse, ?, Husband, Other, Male,0,0,24, United-States, >50K
+39, Private,188540, HS-grad,9, Divorced, Exec-managerial, Not-in-family, White, Male,0,0,45, United-States, <=50K
+19, Private,318061, Some-college,10, Never-married, Machine-op-inspct, Not-in-family, White, Female,0,0,80, United-States, <=50K
+27, Private,70034, Some-college,10, Never-married, Other-service, Not-in-family, White, Male,0,0,40, United-States, <=50K
+47, Private,269620, Some-college,10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male,0,0,40, ?, <=50K
+47, Private,181758, HS-grad,9, Never-married, Transport-moving, Not-in-family, Black, Male,0,0,40, United-States, <=50K
+51, State-gov,103063, Bachelors,13, Married-civ-spouse, Protective-serv, Husband, White, Male,7298,0,40, United-States, >50K
+34, Private,154667, HS-grad,9, Married-civ-spouse, Machine-op-inspct, Wife, White, Female,0,0,40, United-States, <=50K
+29, Private,198704, Assoc-voc,11, Never-married, Machine-op-inspct, Not-in-family, White, Male,0,0,40, United-States, <=50K
+23, Private,134045, Assoc-voc,11, Never-married, Adm-clerical, Unmarried, White, Female,0,0,40, United-States, <=50K
+45, Private,353083, Some-college,10, Separated, Other-service, Unmarried, White, Female,0,0,40, United-States, <=50K
+55, Private,160631, HS-grad,9, Married-civ-spouse, Sales, Husband, White, Male,0,0,56, United-States, >50K
+31, Private,80511, Assoc-acdm,12, Divorced, Tech-support, Not-in-family, White, Female,0,0,44, United-States, <=50K
+59, Private,96459, 11th,7, Never-married, Machine-op-inspct, Not-in-family, White, Male,0,0,40, United-States, <=50K
+24, Private,233280, Assoc-acdm,12, Never-married, Sales, Own-child, White, Female,0,0,37, United-States, <=50K
+35, Self-emp-not-inc,278557, HS-grad,9, Married-civ-spouse, Farming-fishing, Husband, White, Male,0,0,30, United-States, <=50K
+63, Local-gov,80655, Some-college,10, Divorced, Adm-clerical, Not-in-family, White, Female,0,0,40, United-States, <=50K
+43, Private,334991, Bachelors,13, Married-civ-spouse, Sales, Husband, White, Male,0,0,50, United-States, >50K
+49, Private,122206, Assoc-voc,11, Married-civ-spouse, Sales, Husband, White, Male,0,0,25, United-States, <=50K
+23, Private,436798, Some-college,10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male,0,0,40, United-States, <=50K
+44, Private,374423, Masters,14, Married-civ-spouse, Exec-managerial, Husband, Black, Male,0,1902,40, United-States, >50K
+49, Private,50567, Some-college,10, Divorced, Adm-clerical, Not-in-family, White, Female,0,0,32, United-States, <=50K
+18, Private,90934, Some-college,10, Never-married, Sales, Own-child, White, Male,0,0,28, United-States, <=50K
+21, Private,117210, HS-grad,9, Never-married, Machine-op-inspct, Own-child, White, Male,0,0,40, United-States, <=50K
+34, Private,179877, Some-college,10, Married-civ-spouse, Machine-op-inspct, Husband, White, Male,0,0,40, United-States, >50K
+69, Private,361561, Prof-school,15, Married-civ-spouse, Prof-specialty, Husband, White, Male,0,0,3, United-States, <=50K
+38, Private,247111, HS-grad,9, Married-civ-spouse, Tech-support, Husband, White, Male,0,0,40, United-States, >50K
+37, Private,156266, HS-grad,9, Married-civ-spouse, Craft-repair, Husband, Amer-Indian-Eskimo, Male,0,0,40, United-States, <=50K
+42, Private,173938, HS-grad,9, Separated, Sales, Own-child, White, Female,0,0,40, United-States, <=50K
+43, Self-emp-inc,260960, Bachelors,13, Divorced, Farming-fishing, Not-in-family, White, Male,0,0,35, United-States, <=50K
+58, Private,49893, Masters,14, Married-civ-spouse, Exec-managerial, Husband, White, Male,0,0,50, United-States, >50K
+29, Self-emp-not-inc,58744, Assoc-acdm,12, Never-married, Other-service, Own-child, White, Male,0,0,60, United-States, <=50K
+51, Local-gov,74784, Some-college,10, Widowed, Adm-clerical, Not-in-family, White, Female,0,0,40, United-States, <=50K
+51, Private,54465, Assoc-voc,11, Divorced, Prof-specialty, Not-in-family, White, Female,0,0,48, United-States, <=50K
+31, Private,169122, HS-grad,9, Divorced, Other-service, Not-in-family, White, Male,0,0,28, United-States, <=50K
+40, Private,131899, Some-college,10, Divorced, Exec-managerial, Not-in-family, White, Male,0,0,40, United-States, <=50K
+46, Private,423222, Some-college,10, Married-civ-spouse, Craft-repair, Husband, White, Male,3103,0,60, United-States, >50K
+48, State-gov,327886, Doctorate,16, Divorced, Prof-specialty, Own-child, White, Male,0,0,50, United-States, >50K
+29, Private,342989, HS-grad,9, Never-married, Adm-clerical, Own-child, White, Female,0,0,40, United-States, <=50K
+69, State-gov,170458, HS-grad,9, Married-civ-spouse, Other-service, Husband, White, Male,0,0,20, United-States, <=50K
+19, Private,239057, HS-grad,9, Never-married, Craft-repair, Own-child, White, Male,0,0,40, United-States, <=50K
+20, Private,221661, HS-grad,9, Married-civ-spouse, Adm-clerical, Wife, White, Female,0,0,40, Mexico, <=50K
+26, Private,292692, 12th,8, Never-married, Craft-repair, Not-in-family, White, Male,0,0,40, Mexico, <=50K
+45, Private,461725, HS-grad,9, Married-civ-spouse, Handlers-cleaners, Husband, White, Male,0,0,40, United-States, <=50K
+48, Local-gov,148121, Bachelors,13, Married-spouse-absent, Adm-clerical, Unmarried, Asian-Pac-Islander, Female,0,0,40, Philippines, <=50K
+56, Private,174209, 5th-6th,3, Married-civ-spouse, Machine-op-inspct, Husband, Black, Male,0,0,40, United-States, <=50K
+72, Self-emp-inc,149689, Prof-school,15, Married-civ-spouse, Prof-specialty, Husband, White, Male,20051,0,48, United-States, >50K
+53, Private,164198, HS-grad,9, Married-civ-spouse, Transport-moving, Husband, Black, Male,0,0,40, United-States, >50K
+50, Private,33931, HS-grad,9, Divorced, Craft-repair, Not-in-family, White, Male,0,0,40, United-States, <=50K
+42, Self-emp-not-inc,27821, Assoc-voc,11, Married-civ-spouse, Exec-managerial, Husband, White, Male,0,0,60, United-States, <=50K
+19, Private,369463, HS-grad,9, Never-married, Adm-clerical, Own-child, White, Female,0,0,40, United-States, <=50K
+43, Private,152958, Bachelors,13, Married-civ-spouse, Exec-managerial, Husband, White, Male,7298,0,40, United-States, >50K
+19, Self-emp-not-inc,194205, Some-college,10, Never-married, Other-service, Own-child, White, Female,0,0,40, Mexico, <=50K
+18, Private,201871, 12th,8, Never-married, Other-service, Own-child, White, Male,0,0,20, United-States, <=50K
+49, Self-emp-inc,34998, Some-college,10, Married-civ-spouse, Farming-fishing, Husband, White, Male,0,0,60, United-States, <=50K
+41, Private,110562, Bachelors,13, Married-civ-spouse, Exec-managerial, Husband, White, Male,0,0,40, United-States, <=50K
+49, Local-gov,159641, Bachelors,13, Divorced, Exec-managerial, Unmarried, White, Female,0,625,40, United-States, <=50K
+23, Private,278391, HS-grad,9, Never-married, Transport-moving, Own-child, White, Male,0,0,40, United-States, <=50K
+41, Private,175642, Some-college,10, Never-married, Craft-repair, Not-in-family, White, Female,0,0,40, United-States, <=50K
+35, Private,317153, HS-grad,9, Never-married, Sales, Not-in-family, White, Female,0,0,40, United-States, <=50K
+65, Private,90907, 5th-6th,3, Married-civ-spouse, Other-service, Husband, Asian-Pac-Islander, Male,0,0,40, United-States, <=50K
+61, Private,159822, 7th-8th,4, Married-civ-spouse, Craft-repair, Husband, White, Male,7688,0,40, Poland, >50K
+51, Private,205100, Some-college,10, Divorced, Sales, Not-in-family, White, Female,0,0,45, United-States, >50K
+64, Private,207188, Bachelors,13, Divorced, Exec-managerial, Not-in-family, White, Female,0,0,40, United-States, <=50K
+26, ?,102541, 10th,6, Never-married, ?, Unmarried, Amer-Indian-Eskimo, Female,0,0,40, United-States, <=50K
+33, Private,182401, 10th,6, Never-married, Adm-clerical, Not-in-family, Black, Male,0,0,40, United-States, <=50K
+23, Private,348092, HS-grad,9, Never-married, Transport-moving, Own-child, Black, Male,0,0,40, Haiti, <=50K
+39, Private,144169, HS-grad,9, Married-civ-spouse, Exec-managerial, Husband, White, Male,0,0,40, United-States, <=50K
+27, Private,167031, Bachelors,13, Never-married, Prof-specialty, Unmarried, Other, Female,0,0,33, United-States, <=50K
+66, Private,216856, Masters,14, Married-civ-spouse, Sales, Husband, White, Male,0,0,50, United-States, <=50K
+23, Private,214236, HS-grad,9, Never-married, Adm-clerical, Not-in-family, White, Female,0,0,40, United-States, <=50K
+22, Private,52596, Some-college,10, Never-married, Sales, Own-child, White, Male,0,0,8, United-States, <=50K
+22, Private,176131, Some-college,10, Married-civ-spouse, Exec-managerial, Husband, Black, Male,0,0,40, United-States, <=50K
+61, Private,137733, Some-college,10, Divorced, Other-service, Not-in-family, White, Male,0,0,25, United-States, <=50K
+18, Private,400616, Some-college,10, Never-married, Adm-clerical, Own-child, White, Male,0,0,40, United-States, <=50K
+43, Private,26252, Some-college,10, Separated, Other-service, Unmarried, Amer-Indian-Eskimo, Female,0,0,36, United-States, <=50K
+29, Federal-gov,182344, HS-grad,9, Married-spouse-absent, Other-service, Unmarried, Black, Male,0,0,40, United-States, <=50K
+31, Private,91964, Some-college,10, Never-married, Adm-clerical, Other-relative, White, Male,0,0,40, United-States, <=50K
+31, Private,359249, Assoc-voc,11, Never-married, Protective-serv, Own-child, Black, Male,0,0,40, United-States, <=50K
+34, Private,24529, HS-grad,9, Widowed, Adm-clerical, Unmarried, White, Male,0,0,15, United-States, <=50K
diff --git a/test/autogluon/sagemaker/resources/data/timeseries/train.csv b/test/autogluon/sagemaker/resources/data/timeseries/train.csv
new file mode 100644
index 000000000000..add96af365ac
--- /dev/null
+++ b/test/autogluon/sagemaker/resources/data/timeseries/train.csv
@@ -0,0 +1,61 @@
+item_id,timestamp,target
+series_1,2024-01-01 00:00:00,10
+series_1,2024-01-01 01:00:00,12
+series_1,2024-01-01 02:00:00,15
+series_1,2024-01-01 03:00:00,14
+series_1,2024-01-01 04:00:00,11
+series_1,2024-01-01 05:00:00,9
+series_1,2024-01-01 06:00:00,11
+series_1,2024-01-01 07:00:00,13
+series_1,2024-01-01 08:00:00,16
+series_1,2024-01-01 09:00:00,15
+series_1,2024-01-01 10:00:00,12
+series_1,2024-01-01 11:00:00,10
+series_1,2024-01-01 12:00:00,12
+series_1,2024-01-01 13:00:00,14
+series_1,2024-01-01 14:00:00,17
+series_1,2024-01-01 15:00:00,16
+series_1,2024-01-01 16:00:00,13
+series_1,2024-01-01 17:00:00,11
+series_1,2024-01-01 18:00:00,13
+series_1,2024-01-01 19:00:00,15
+series_1,2024-01-01 20:00:00,18
+series_1,2024-01-01 21:00:00,17
+series_1,2024-01-01 22:00:00,14
+series_1,2024-01-01 23:00:00,12
+series_1,2024-01-02 00:00:00,14
+series_1,2024-01-02 01:00:00,16
+series_1,2024-01-02 02:00:00,19
+series_1,2024-01-02 03:00:00,18
+series_1,2024-01-02 04:00:00,15
+series_1,2024-01-02 05:00:00,13
+series_2,2024-01-01 00:00:00,30
+series_2,2024-01-01 01:00:00,28
+series_2,2024-01-01 02:00:00,27
+series_2,2024-01-01 03:00:00,29
+series_2,2024-01-01 04:00:00,32
+series_2,2024-01-01 05:00:00,34
+series_2,2024-01-01 06:00:00,31
+series_2,2024-01-01 07:00:00,29
+series_2,2024-01-01 08:00:00,28
+series_2,2024-01-01 09:00:00,30
+series_2,2024-01-01 10:00:00,33
+series_2,2024-01-01 11:00:00,35
+series_2,2024-01-01 12:00:00,32
+series_2,2024-01-01 13:00:00,30
+series_2,2024-01-01 14:00:00,29
+series_2,2024-01-01 15:00:00,31
+series_2,2024-01-01 16:00:00,34
+series_2,2024-01-01 17:00:00,36
+series_2,2024-01-01 18:00:00,33
+series_2,2024-01-01 19:00:00,31
+series_2,2024-01-01 20:00:00,30
+series_2,2024-01-01 21:00:00,32
+series_2,2024-01-01 22:00:00,35
+series_2,2024-01-01 23:00:00,37
+series_2,2024-01-02 00:00:00,34
+series_2,2024-01-02 01:00:00,32
+series_2,2024-01-02 02:00:00,31
+series_2,2024-01-02 03:00:00,33
+series_2,2024-01-02 04:00:00,36
+series_2,2024-01-02 05:00:00,38
diff --git a/test/autogluon/sagemaker/test_train_and_serve.py b/test/autogluon/sagemaker/test_train_and_serve.py
new file mode 100644
index 000000000000..d7ffc82a0fc6
--- /dev/null
+++ b/test/autogluon/sagemaker/test_train_and_serve.py
@@ -0,0 +1,193 @@
+"""Train with the unified AutoGluon image, then serve the resulting artifact."""
+
+import csv
+import json
+import logging
+import os
+from pathlib import Path
+
+import pytest
+from sagemaker.core.resources import Endpoint, EndpointConfig, Model
+from sagemaker.core.shapes import ContainerDefinition, ProductionVariant
+from sagemaker.core.training.configs import Compute, InputData, SourceCode
+from sagemaker.train import ModelTrainer
+from test_utils import random_suffix_name
+from test_utils.constants import INFERENCE_AMI_VERSION
+
+LOGGER = logging.getLogger(__name__)
+RESOURCE_DIR = Path(__file__).parent / "resources"
+CODE_DIR = RESOURCE_DIR / "code"
+DATA_DIR = RESOURCE_DIR / "data"
+PREDICTION_LENGTH = 5
+
+_WORKLOADS = {
+    "tabular": {
+        "source_dir": CODE_DIR / "tabular",
+        "data": DATA_DIR / "tabular" / "train.csv",
+    },
+    "timeseries": {
+        "source_dir": CODE_DIR / "timeseries",
+        "data": DATA_DIR / "timeseries" / "train.csv",
+    },
+}
+
+_INSTANCE_BY_DEVICE = {
+    "cpu": {
+        "training": "ml.m5.2xlarge",
+        "inference": "ml.c5.xlarge",
+    },
+    "gpu": {
+        "training": "ml.g4dn.2xlarge",
+        "inference": "ml.g6.xlarge",
+    },
+}
+_NUMERIC_COLUMNS = {
+    "age",
+    "fnlwgt",
+    "education-num",
+    "capital-gain",
+    "capital-loss",
+    "hours-per-week",
+}
+
+
+def _cleanup(resources):
+    for resource in reversed(resources):
+        try:
+            resource.delete()
+        except Exception as error:  # noqa: BLE001 - cleanup must not mask test failures
+            LOGGER.warning("Cleanup of %s failed: %s", type(resource).__name__, error)
+
+
+@pytest.fixture(scope="module")
+def device_config():
+    device = os.environ.get("SM_DEVICE_TYPE", "").lower()
+    assert device in _INSTANCE_BY_DEVICE, f"SM_DEVICE_TYPE must be cpu or gpu, got {device!r}"
+    return device, _INSTANCE_BY_DEVICE[device]
+
+
+@pytest.fixture(scope="module", params=_WORKLOADS)
+def workload(request):
+    return request.param, _WORKLOADS[request.param]
+
+
+@pytest.fixture(scope="module")
+def model_data_url(image_uri, sagemaker_session, device_config, workload):
+    """Train once and return the model artifact produced by the tested image."""
+    device, instances = device_config
+    workload_name, config = workload
+    key_prefix = random_suffix_name(f"ag-e2e-{workload_name}", 32)
+    trainer = ModelTrainer(
+        training_image=image_uri,
+        source_code=SourceCode(source_dir=str(config["source_dir"]), entry_script="train.py"),
+        compute=Compute(instance_type=instances["training"], instance_count=1),
+        role=os.environ["SM_ROLE_ARN"],
+        base_job_name=random_suffix_name(f"ag-{workload_name}-{device}", 32),
+    )
+    trainer.train(
+        input_data_config=[
+            InputData(
+                channel_name="train",
+                data_source=sagemaker_session.upload_data(
+                    path=str(config["data"]),
+                    key_prefix=f"{key_prefix}/train",
+                ),
+            )
+        ],
+        wait=True,
+    )
+    return trainer._latest_training_job.model_artifacts.s3_model_artifacts
+
+
+@pytest.fixture(scope="module")
+def endpoint(aws_session, image_uri, model_data_url, device_config, workload):
+    """Deploy the training artifact with the same unified image."""
+    device, instances = device_config
+    workload_name, _ = workload
+    endpoint_name = random_suffix_name(f"ag-{workload_name}", 63)
+    model_name = random_suffix_name(f"ag-{workload_name}-model", 63)
+    resources = []
+    try:
+        model = Model.create(
+            model_name=model_name,
+            primary_container=ContainerDefinition(
+                image=image_uri,
+                model_data_url=model_data_url,
+                environment={"SAGEMAKER_PROGRAM": "serve.py"},
+            ),
+            execution_role_arn=os.environ["SM_ROLE_ARN"],
+            session=aws_session.session,
+        )
+        resources.append(model)
+
+        variant = {
+            "variant_name": "AllTraffic",
+            "model_name": model_name,
+            "initial_instance_count": 1,
+            "instance_type": instances["inference"],
+            "container_startup_health_check_timeout_in_seconds": 600,
+        }
+        if device == "gpu":
+            variant["inference_ami_version"] = INFERENCE_AMI_VERSION
+        endpoint_config = EndpointConfig.create(
+            endpoint_config_name=endpoint_name,
+            production_variants=[ProductionVariant(**variant)],
+            session=aws_session.session,
+        )
+        resources.append(endpoint_config)
+
+        deployed = Endpoint.create(
+            endpoint_name=endpoint_name,
+            endpoint_config_name=endpoint_name,
+            session=aws_session.session,
+        )
+        resources.append(deployed)
+        deployed.wait_for_status("InService", timeout=1800)
+        yield deployed
+    finally:
+        _cleanup(resources)
+
+
+def _assert_tabular_prediction(endpoint, data_path):
+    with data_path.open(newline="") as data_file:
+        row = next(csv.DictReader(data_file))
+    expected_labels = {"<=50K", ">50K"}
+    row.pop("class")
+    for column in _NUMERIC_COLUMNS:
+        row[column] = int(row[column])
+
+    response = endpoint.invoke(
+        body=json.dumps([row]),
+        content_type="application/json",
+        accept="application/json",
+    )
+    prediction = json.loads(response.body.read())
+
+    assert len(prediction) == 1
+    assert prediction[0]["class"].strip() in expected_labels
+
+
+def _assert_timeseries_prediction(endpoint, data_path):
+    with data_path.open(newline="") as data_file:
+        rows = list(csv.DictReader(data_file))
+    for row in rows:
+        row["target"] = float(row["target"])
+
+    response = endpoint.invoke(
+        body=json.dumps(rows),
+        content_type="application/json",
+        accept="application/json",
+    )
+    prediction = json.loads(response.body.read())
+
+    assert len(prediction) == 2 * PREDICTION_LENGTH
+    assert {row["item_id"] for row in prediction} == {"series_1", "series_2"}
+    assert all(isinstance(row["mean"], (int, float)) for row in prediction)
+
+
+def test_train_then_serve(endpoint, workload):
+    workload_name, config = workload
+    if workload_name == "tabular":
+        _assert_tabular_prediction(endpoint, config["data"])
+    else:
+        _assert_timeseries_prediction(endpoint, config["data"])
diff --git a/test/security/data/ecr_scan_allowlist/autogluon/framework_allowlist.json b/test/security/data/ecr_scan_allowlist/autogluon/framework_allowlist.json
new file mode 100644
index 000000000000..048795fd6a0b
--- /dev/null
+++ b/test/security/data/ecr_scan_allowlist/autogluon/framework_allowlist.json
@@ -0,0 +1,12 @@
+[
+    {
+        "vulnerability_id": "CVE-2026-54399",
+        "reason": "Ray 2.58.0 bundles httpcore5 5.0.2 inside ray_dist.jar. The Java dependency cannot be upgraded independently from the Ray wheel; remediation requires an upstream Ray release that updates the bundled Apache HttpComponents Core.",
+        "review_by": "2026-10-20"
+    },
+    {
+        "vulnerability_id": "CVE-2026-58659",
+        "reason": "False positive for lightning 2.6.6: the advisory affects versions through 2.6.5, and 2.6.6 includes the fix from commit d710d68. The scanner incorrectly reports 2022.6.15 as the fixed version because the advisory's patched-version metadata is malformed.",
+        "review_by": "2026-10-20"
+    }
+]