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zhaoqizqwang merged 4 commits into from
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Doc update: reorganize examples folder #6155

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691db06
fix: usuability update from feedback
zhaoqizqwang Aug 4, 2026
5ef9216
update documentation
zhaoqizqwang Aug 4, 2026
d4e2042
docs: organize model-customization examples into serverless/serverful…
zhaoqizqwang Aug 4, 2026
1675758
add job notification integ test
zhaoqizqwang Aug 4, 2026
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2 changes: 1 addition & 1 deletion docs/inference/deploy_finetuned.rst
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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>
8 changes: 4 additions & 4 deletions docs/model_customization/evaluation.rst
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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
:maxdepth: 1

../../v3-examples/model-customization-examples/llm_as_judge_demo
../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
../../v3-examples/model-customization-examples/custom_scorer_demo
../../v3-examples/model-customization-examples/benchmark_demo
../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
../../v3-examples/model-customization-examples/evaluation/benchmark_demo
../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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2 changes: 1 addition & 1 deletion docs/model_customization/finetuning_hyperpod.rst
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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod
2 changes: 1 addition & 1 deletion docs/model_customization/finetuning_serverful.rst
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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
:maxdepth: 1

../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj
1 change: 1 addition & 0 deletions docs/model_customization/index.rst
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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup
8 changes: 4 additions & 4 deletions docs/model_customization/model_customization.rst
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Expand Up@@ -196,9 +196,9 @@ Key Features
:maxdepth: 1
:caption: Customization Techniques

SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
Fine-Tuning with HyperPod <finetuning_hyperpod>
250 changes: 250 additions & 0 deletions docs/model_customization/notifications_setup.rst
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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

{
"Sid": "AllowEventBridgePublish",
"Effect": "Allow",
"Principal": {"Service": "events.amazonaws.com"},
"Action": "SNS:Publish",
"Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
"Condition": {
"StringEquals": {"AWS:SourceAccount": "123456789012"}
}
}

.. note::

Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
ACCOUNT_ID="123456789012"

aws sns set-topic-attributes \
--topic-arn $TOPIC_ARN \
--attribute-name Policy \
--attribute-value '{
"Version": "2008-10-17",
"Statement": [{
"Sid": "AllowEventBridgePublish",
"Effect": "Allow",
"Principal": {"Service": "events.amazonaws.com"},
"Action": "SNS:Publish",
"Resource": "'$TOPIC_ARN'",
"Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
}]
}'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

aws sns subscribe \
--topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
--protocol email \
--notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

aws sns subscribe \
--topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
--protocol sms \
--notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

from sagemaker.train import SFTTrainer
from sagemaker.train.common import TrainingType
from sagemaker.core.training.configs import TrainingJobCompute

trainer = SFTTrainer(
model="amazon.nova-2-lite-v1",
training_type=TrainingType.LORA,
training_dataset="s3://my-bucket/data/train.jsonl",
compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
notifications={
"sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
},
)

trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
:header-rows: 1
:widths: 25 10 65

* - Key
- Required
- Description
* - ``sns_topic_arn``
- Yes
- ARN of your SNS topic
* - ``events``
- No
- List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
* - ``event_bus_arn``
- No
- Custom EventBridge bus ARN. Defaults to the account's default event bus.
* - ``job_name_prefix``
- No
- Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

notifications={
"sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
"events": ["Failed"],
"job_name_prefix": "prod-sft-",
}

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

rules = trainer.list_notification_rules()
for rule in rules:
print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"events:PutRule",
"events:PutTargets",
"events:ListRules",
"events:ListTargetsByRule",
"events:RemoveTargets",
"events:DeleteRule"
],
"Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
},
{
"Effect": "Allow",
"Action": "sns:GetTopicAttributes",
"Resource": "arn:aws:sns:*:*:my-training-alerts"
}
]
}

.. note::

The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for
4 changes: 2 additions & 2 deletions docs/model_customization/nova.rst
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Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
:caption: Nova Customization Guides

nova_data_mixing
CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>
2 changes: 1 addition & 1 deletion docs/model_customization/nova_data_mixing.rst
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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.
2 changes: 1 addition & 1 deletion docs/model_customization/open_weight_model_customization.rst
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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
:maxdepth: 1

../../v3-examples/model-customization-examples/ai_registry_example
../../v3-examples/model-customization-examples/serverless/ai_registry_example
model_customization
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Doc update: reorganize examples folder by zhaoqizqwang · Pull Request #6155 · aws/sagemaker-python-sdk · GitHub
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 Merged

zhaoqizqwang
merged 4 commits into

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Aug 5, 2026
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Doc update: reorganize examples folder
#6155
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691db06

fix: usuability update from feedback


zhaoqizqwang Aug 4, 2026
5ef9216

update documentation


zhaoqizqwang Aug 4, 2026
d4e2042

docs: organize model-customization examples into serverless/serverful…


zhaoqizqwang Aug 4, 2026
1675758

add job notification integ test


zhaoqizqwang Aug 4, 2026

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2 changes: 1 addition & 1 deletion
docs/inference/deploy_finetuned.rst

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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

8 changes: 4 additions & 4 deletions
docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

1 change: 1 addition & 0 deletions
docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

250 changes: 250 additions & 0 deletions
docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

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Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

2 changes: 1 addition & 1 deletion
docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

2 changes: 1 addition & 1 deletion
docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
Loading

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docs/inference/deploy_finetuned.rst

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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

8 changes: 4 additions & 4 deletions
docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

1 change: 1 addition & 0 deletions
docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

250 changes: 250 additions & 0 deletions
docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

2 changes: 1 addition & 1 deletion
docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

2 changes: 1 addition & 1 deletion
docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
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Doc update: reorganize examples folder by zhaoqizqwang · Pull Request #6155 · aws/sagemaker-python-sdk · GitHub
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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

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docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

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docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

250 changes: 250 additions & 0 deletions
docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

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Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

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docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

2 changes: 1 addition & 1 deletion
docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
Loading

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Doc update: reorganize examples folder by zhaoqizqwang · Pull Request #6155 · aws/sagemaker-python-sdk · GitHub
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fix: usuability update from feedback


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update documentation


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docs: organize model-customization examples into serverless/serverful…


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2 changes: 1 addition & 1 deletion
docs/inference/deploy_finetuned.rst

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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

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docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

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docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

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docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

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docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

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Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

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docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

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docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
Loading

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Doc update: reorganize examples folder by zhaoqizqwang · Pull Request #6155 · aws/sagemaker-python-sdk · GitHub
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fix: usuability update from feedback


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update documentation


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2 changes: 1 addition & 1 deletion
docs/inference/deploy_finetuned.rst

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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

8 changes: 4 additions & 4 deletions
docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

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docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

250 changes: 250 additions & 0 deletions
docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

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Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

2 changes: 1 addition & 1 deletion
docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

2 changes: 1 addition & 1 deletion
docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
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Doc update: reorganize examples folder by zhaoqizqwang · Pull Request #6155 · aws/sagemaker-python-sdk · GitHub
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Doc update: reorganize examples folder#6155

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Aug 5, 2026
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Doc update: reorganize examples folder
#6155
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691db06

fix: usuability update from feedback


zhaoqizqwang Aug 4, 2026
5ef9216

update documentation


zhaoqizqwang Aug 4, 2026
d4e2042

docs: organize model-customization examples into serverless/serverful…


zhaoqizqwang Aug 4, 2026
1675758

add job notification integ test


zhaoqizqwang Aug 4, 2026

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docs/inference/deploy_finetuned.rst

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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

8 changes: 4 additions & 4 deletions
docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

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docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

1 change: 1 addition & 0 deletions
docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

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docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

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Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

2 changes: 1 addition & 1 deletion
docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

2 changes: 1 addition & 1 deletion
docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
Loading

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Doc update: reorganize examples folder by zhaoqizqwang · Pull Request #6155 · aws/sagemaker-python-sdk · GitHub
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691db06

fix: usuability update from feedback


zhaoqizqwang Aug 4, 2026
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update documentation


zhaoqizqwang Aug 4, 2026
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docs: organize model-customization examples into serverless/serverful…


zhaoqizqwang Aug 4, 2026
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add job notification integ test


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2 changes: 1 addition & 1 deletion
docs/inference/deploy_finetuned.rst

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Expand Up@@ -7,4 +7,4 @@ Deploy models that have been fine-tuned through the :doc:`Model Customization <.
:maxdepth:1

Deploy to SageMaker Endpoint <../model_customization/deploy_sagemaker_endpoint>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/bedrock-modelbuilder-deployment>
Deploy to Amazon Bedrock <../../v3-examples/model-customization-examples/deployment/bedrock-modelbuilder-deployment>

8 changes: 4 additions & 4 deletions
docs/model_customization/evaluation.rst

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Expand Up@@ -12,10 +12,10 @@ Launch evaluation jobs with the following options:
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/custom_scorer_demo
 ../../v3-examples/model-customization-examples/benchmark_demo
 ../../v3-examples/model-customization-examples/evaluation/llm_as_judge_demo
 ../../v3-examples/model-customization-examples/evaluation/inspect_ai_evaluation_demo
 ../../v3-examples/model-customization-examples/evaluation/custom_scorer_demo
 ../../v3-examples/model-customization-examples/evaluation/benchmark_demo
 ../../v3-examples/nova-examples/evaluation-benchmark-and-custom-scorer


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2 changes: 1 addition & 1 deletion
docs/model_customization/finetuning_hyperpod.rst

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Expand Up@@ -177,4 +177,4 @@ Interactive Notebook
.. toctree::
:maxdepth:1

../../v3-examples/model-customization-examples/sft_finetuning_hyperpod
../../v3-examples/model-customization-examples/serverful/sft_finetuning_hyperpod

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docs/model_customization/finetuning_serverful.rst

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Expand Up@@ -138,4 +138,4 @@ Interactive Notebook
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/sft_finetuning_serverful_smtj
 ../../v3-examples/model-customization-examples/serverful/sft_finetuning_serverful_smtj

1 change: 1 addition & 0 deletions
docs/model_customization/index.rst

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Expand Up@@ -23,3 +23,4 @@ Key Benefits
open_weight_model_customization
nova
evaluation
notifications_setup

8 changes: 4 additions & 4 deletions
docs/model_customization/model_customization.rst

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Expand Up@@ -196,9 +196,9 @@ Key Features
 :maxdepth: 1
 :caption: Customization Techniques

 SFT Finetuning <../../v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/rlvr_finetuning_example_notebook_v3_prod>
 SFT Finetuning <../../v3-examples/model-customization-examples/serverless/sft_finetuning_example_notebook_pysdk_prod_v3>
 DPOTrainer Finetuning <../../v3-examples/model-customization-examples/serverless/dpo_trainer_example_notebook_v3_prod>
 RLAIF Finetuning <../../v3-examples/model-customization-examples/serverless/rlaif_finetuning_example_notebook_v3_prod>
 RLVR Finetuning <../../v3-examples/model-customization-examples/serverless/rlvr_finetuning_example_notebook_v3_prod>
 Fine-Tuning with Serverful Training Jobs <finetuning_serverful>
 Fine-Tuning with HyperPod <finetuning_hyperpod>

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docs/model_customization/notifications_setup.rst

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Setting Up Training Job Notifications
========================================

Get notified when your training jobs complete, fail, or stop via SNS email/SMS
alerts. This guide walks through creating the prerequisite SNS topic and
configuring your trainer to send notifications.

Architecture
-------------

.. code-block:: text

 SageMaker Training Job ──► EventBridge Rule ──► SNS Topic ──► Email/SMS/Slack

The SDK creates an EventBridge rule that listens for training job status changes
and routes them to your SNS topic. You provide the topic; the SDK handles the
wiring.

Prerequisites
--------------

You need:

1. An SNS topic with a policy allowing EventBridge to publish to it
2. A subscription on that topic (email, SMS, Slack, etc.)
3. IAM permissions for EventBridge rule management (see below)

Step 1: Create an SNS Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → **Create topic**
2. Choose **Standard** type
3. Name it (e.g., ``my-training-alerts``)
4. Click **Create topic**
5. Note the **Topic ARN** (e.g., ``arn:aws:sns:us-east-1:123456789012:my-training-alerts``)

**AWS CLI**

.. code-block:: bash

 aws sns create-topic --name my-training-alerts

Step 2: Allow EventBridge to Publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The topic needs a resource policy granting EventBridge publish access.

**AWS Console**

1. Go to **Amazon SNS** → **Topics** → open your topic → **Access policy** tab → **Edit**
2. Add this statement to the policy's ``Statement`` array (replace the ARN and
 account ID with your own SNS topic ARN and AWS account ID):

.. code-block:: json

 {
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "Condition": {
 "StringEquals": {"AWS:SourceAccount": "123456789012"}
 }
 }

.. note::

 Replace ``arn:aws:sns:us-east-1:123456789012:my-training-alerts`` with your
 actual SNS topic ARN, and ``123456789012`` with your AWS account ID. These
 must match so that only EventBridge in your account can publish to your topic.

**AWS CLI**

.. code-block:: bash

 TOPIC_ARN="arn:aws:sns:us-east-1:123456789012:my-training-alerts"
 ACCOUNT_ID="123456789012"

 aws sns set-topic-attributes \
 --topic-arn $TOPIC_ARN \
 --attribute-name Policy \
 --attribute-value '{
 "Version": "2008-10-17",
 "Statement": [{
 "Sid": "AllowEventBridgePublish",
 "Effect": "Allow",
 "Principal": {"Service": "events.amazonaws.com"},
 "Action": "SNS:Publish",
 "Resource": "'$TOPIC_ARN'",
 "Condition": {"StringEquals": {"AWS:SourceAccount": "'$ACCOUNT_ID'"}}
 }]
 }'

Step 3: Subscribe to the Topic
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Email**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol email \
 --notification-endpoint you@example.com

Check your inbox and confirm the subscription.

**SMS**

.. code-block:: bash

 aws sns subscribe \
 --topic-arn arn:aws:sns:us-east-1:123456789012:my-training-alerts \
 --protocol sms \
 --notification-endpoint +15551234567

Step 4: Use with the SDK
~~~~~~~~~~~~~~~~~~~~~~~~~~

Pass the topic ARN in the ``notifications`` config when constructing your trainer:

.. code-block:: python

 from sagemaker.train import SFTTrainer
 from sagemaker.train.common import TrainingType
 from sagemaker.core.training.configs import TrainingJobCompute

 trainer = SFTTrainer(
 model="amazon.nova-2-lite-v1",
 training_type=TrainingType.LORA,
 training_dataset="s3://my-bucket/data/train.jsonl",
 compute=TrainingJobCompute(instance_type="ml.p4d.24xlarge"),
 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 },
 )

 trainer.train()

Configuration Options
~~~~~~~~~~~~~~~~~~~~~~

The ``notifications`` dict supports:

.. list-table::
 :header-rows: 1
 :widths: 25 10 65

 * - Key
 - Required
 - Description
 * - ``sns_topic_arn``
 - Yes
 - ARN of your SNS topic
 * - ``events``
 - No
 - List of statuses to notify on. Default: ``["Completed", "Failed", "Stopped"]``.
 Valid values: ``Completed``, ``Failed``, ``Stopped``, ``InProgress``.
 * - ``event_bus_arn``
 - No
 - Custom EventBridge bus ARN. Defaults to the account's default event bus.
 * - ``job_name_prefix``
 - No
 - Only notify for jobs whose name starts with this prefix.

Example: notify only on failures for jobs matching a prefix:

.. code-block:: python

 notifications={
 "sns_topic_arn": "arn:aws:sns:us-east-1:123456789012:my-training-alerts",
 "events": ["Failed"],
 "job_name_prefix": "prod-sft-",
 }

Managing Notification Rules
-----------------------------

List active rules:

.. code-block:: python

 rules = trainer.list_notification_rules()
 for rule in rules:
 print(f"{rule['name']} ({rule['state']})")

Delete a rule:

.. code-block:: python

 trainer.delete_notification_rule(rule_arn="arn:aws:events:us-east-1:123456789012:rule/sm-pysdk-job-notif-abc123")

Required IAM Permissions
--------------------------

The caller (your IAM role or user) needs these permissions. Replace the SNS
resource ARN with your actual topic ARN:

.. code-block:: json

 {
 "Version": "2012-10-17",
 "Statement": [
 {
 "Effect": "Allow",
 "Action": [
 "events:PutRule",
 "events:PutTargets",
 "events:ListRules",
 "events:ListTargetsByRule",
 "events:RemoveTargets",
 "events:DeleteRule"
 ],
 "Resource": "arn:aws:events:*:*:rule/sm-pysdk-job-notif-*"
 },
 {
 "Effect": "Allow",
 "Action": "sns:GetTopicAttributes",
 "Resource": "arn:aws:sns:*:*:my-training-alerts"
 }
 ]
 }

.. note::

 The ``sns:GetTopicAttributes`` resource must match the SNS topic you created
 in Step 1. You can use a wildcard (``arn:aws:sns:*:*:*``) for broader access
 or scope it to your specific topic ARN for least privilege.

Troubleshooting
-----------------

**PermissionError: Missing permissions to manage EventBridge rules**

Your IAM identity needs ``events:PutRule`` and ``events:PutTargets``. Ask your
admin to attach the policy above.

**ValueError: SNS topic not found**

Verify the topic ARN is correct and exists in the same region as your
SageMaker session. Ensure you have ``sns:GetTopicAttributes`` permission.

**Not receiving notifications**

1. Confirm the SNS subscription is in ``Confirmed`` state (check in the Console)
2. Verify the topic policy allows EventBridge to publish (Step 2 above)
3. Check that the ``events`` list includes the status you're waiting for

4 changes: 2 additions & 2 deletions
docs/model_customization/nova.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -13,5 +13,5 @@ Adapt Amazon Nova foundation models to your specific use cases through fine-tuni
 :caption: Nova Customization Guides

 nova_data_mixing
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/cpt_data_mixing_hyperpod>
 ../../v3-examples/model-customization-examples/sm-studio-nova-training-job-sample-notebook
 CPT Training on HyperPod <../../v3-examples/model-customization-examples/serverful/cpt_data_mixing_hyperpod>
Serverless End-to-End Example <../../v3-examples/model-customization-examples/serverless/serverless_e2e_example>

2 changes: 1 addition & 1 deletion
docs/model_customization/nova_data_mixing.rst

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Expand Up@@ -132,4 +132,4 @@ Interactive Notebook
---------------------

For a complete walkthrough, see the
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/nova_data_mixing>`.
:doc:`Data Mixing notebook <../../v3-examples/model-customization-examples/serverless/nova_data_mixing>`.

2 changes: 1 addition & 1 deletion
docs/model_customization/open_weight_model_customization.rst

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Expand Up@@ -6,5 +6,5 @@ This section walks you through the process to get started with open weight model
.. toctree::
 :maxdepth: 1

 ../../v3-examples/model-customization-examples/ai_registry_example
 ../../v3-examples/model-customization-examples/serverless/ai_registry_example
 model_customization
Loading