chore(release): Release 3.22.0 (#6274)

* chore(release): Release 3.22.0

Bump package versions and inter-package dependency floors for the
3.22.0 release. Raise the sagemaker-core boto3 floor for
InstancePreferences compatibility and update the package changelogs.

---
X-AI-Prompt: Complete all SageMaker Python SDK 3.22.0 changelog entries
X-AI-Tool: Kiro

Author: papriwal

CHANGELOG.md

@@ -1,5 +1,42 @@
 # Changelog
 
+## v3.22.0 (2026-09-14)
+
+### New Features
+
+- feat(train): add list_hyperparameters() for pre-trainer hyperparameter discovery (#6149)
+- feat(train): validate raw base model names in SageMaker Hub (#6227)
+- feat(core,train): add InstancePreferences for multi-instance-type training and processing (#6249)
+- feat(feature-store): add UpdateRecord API and Standard_V2 storage type (#6247)
+
+### Bug Fixes
+
+- fix(train): add PipelineSession support to SFT, DPO, RLAIF, and RLVR trainers (#6213)
+- fix(feature-store): register HubContent Dataset from DatasetBuilder CSV paths (#6212)
+- fix(local): detect docker compose v2+ when version has no 'v' prefix (#6231)
+- fix(train): resolve private Hub models and aliased references for ModelTrainer (#6201)
+- fix(core): resolve default training role from sagemaker config (#6228)
+- fix(train): validate evaluator models against the live supported-model list (#6217)
+- fix(train): complete PipelineSession support for SFT, DPO, RLAIF, and RLVR trainers (#6235)
+- fix(train): preserve training_plan_arn during serverful compute reconstruction (#6258)
+
+### Other
+
+- change(core): add image URI configs for DLC serving frameworks and Amazon Linux 2023 PyTorch (#6220)
+- change(core): add image URI configs for vLLM and SGLang (#6218)
+- ci(core): add botocore-sync workflows (#6226)
+- change(core): add TensorFlow inference 2.20 and training 2.21 image URI configs (#6230)
+- change(core): add Ray/llama-cpp CPU images and device-selectable DLC serving configs (#6229)
+- change(core): refresh generated image URI configs (55c2a9bd)
+- change(serve): emit the JumpStart model ID in ModelBuilder telemetry (#6234)
+
+### Tests
+
+- fix(ci,train): stop integ tests from rerunning the shallow suite (#6216)
+- docs(train): add guidance for maintaining shallow integration tests (#6219)
+- fix(train): refresh MTRL attached-job integration fixtures (#6259)
+- fix(train): add training_plan_arn to serverful test fixtures (#6270)
+
 ## v3.21.0 (2026-08-25)
 
 ### New Features

VERSION

@@ -1 +1 @@
-3.21.0
+3.22.0

pyproject.toml

@@ -32,10 +32,10 @@ classifiers = [
   "Programming Language :: Python :: 3.12",
 ]
 dependencies = [
-  "sagemaker-core>=2.21.0,<3.0.0",
-  "sagemaker-train>=1.21.0,<2.0.0",
-  "sagemaker-serve>=1.21.0,<2.0.0",
-  "sagemaker-mlops>=1.21.0,<2.0.0",
+  "sagemaker-core>=2.22.0,<3.0.0",
+  "sagemaker-train>=1.22.0,<2.0.0",
+  "sagemaker-serve>=1.22.0,<2.0.0",
+  "sagemaker-mlops>=1.22.0,<2.0.0",
 ]
 
 [project.optional-dependencies]

sagemaker-core/CHANGELOG.md

@@ -1,5 +1,26 @@
 # Changelog
 
+## v2.22.0 (2026-09-14)
+
+### New Features
+
+- feat(core): add InstancePreferences for multi-instance-type training and processing (#6249)
+- feat(feature-store): add UpdateRecord API and Standard_V2 storage type (#6247)
+
+### Bug Fixes
+
+- fix(local): detect docker compose v2+ when version has no 'v' prefix (#6231)
+- fix(core): resolve default training role from sagemaker config (#6228)
+
+### Other
+
+- change(core): add image URI configs for DLC serving frameworks and Amazon Linux 2023 PyTorch (#6220)
+- change(core): add image URI configs for vLLM and SGLang (#6218)
+- ci(core): add botocore-sync workflows (#6226)
+- change(core): add TensorFlow inference 2.20 and training 2.21 image URI configs (#6230)
+- change(core): add Ray/llama-cpp CPU images and device-selectable DLC serving configs (#6229)
+- change(core): refresh generated image URI configs (55c2a9bd)
+
 ## v2.21.0 (2026-08-25)
 
 ### Bug Fixes

sagemaker-core/VERSION

@@ -1 +1 @@
-2.21.0
+2.22.0

sagemaker-core/pyproject.toml

@@ -12,7 +12,7 @@ authors = [
 readme = "README.rst" 
 dependencies = [
   # Add your dependencies here (Include lower and upper bounds as applicable)
-    "boto3>=1.43.20,<2.0.0",
+    "boto3>=1.43.90,<2.0.0",
     "pydantic>=2.0.0,<3.0.0",
     "PyYAML>=6.0, <7.0",
     "jsonschema<5.0.0",

sagemaker-mlops/CHANGELOG.md

@@ -1,5 +1,19 @@
 # Changelog
 
+## v1.22.0 (2026-09-14)
+
+### New Features
+
+- feat(feature-store): add UpdateRecord API and Standard_V2 storage type (#6247)
+
+### Bug Fixes
+
+- fix(feature-store): register HubContent Dataset from DatasetBuilder CSV paths (#6212)
+
+### Tests
+
+- test(mlops): add PipelineSession integration coverage for V3 trainers (#6235)
+
 ## v1.21.0 (2026-08-25)
 
 ### Bug Fixes

sagemaker-mlops/VERSION

@@ -1 +1 @@
-1.21.0
+1.22.0

sagemaker-mlops/pyproject.toml

@@ -22,9 +22,9 @@ classifiers = [
     "Programming Language :: Python :: 3.12",
 ]
 dependencies = [
-    "sagemaker-core>=2.21.0",
-    "sagemaker-train>=1.21.0",
-    "sagemaker-serve>=1.21.0",
+    "sagemaker-core>=2.22.0",
+    "sagemaker-train>=1.22.0",
+    "sagemaker-serve>=1.22.0",
     "cryptography>=46.0.0",
     "boto3>=1.42.2,<2.0",
     "botocore>=1.42.2,<2.0",

sagemaker-serve/CHANGELOG.md

@@ -1,5 +1,11 @@
 # Changelog
 
+## v1.22.0 (2026-09-14)
+
+### Other
+
+- change(serve): emit the JumpStart model ID in ModelBuilder telemetry (#6234)
+
 ## v1.21.0 (2026-08-25)
 
 ### Bug Fixes