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Updates SDK to v2.1532.0
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awstools committed Jan 8, 2024
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17 changes: 17 additions & 0 deletions .changes/2.1532.0.json
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[
{
"type": "feature",
"category": "CodeBuild",
"description": "Aws CodeBuild now supports new compute type BUILD_GENERAL1_XLARGE"
},
{
"type": "feature",
"category": "EC2",
"description": "Amazon EC2 R7iz bare metal instances are powered by custom 4th generation Intel Xeon Scalable processors."
},
{
"type": "feature",
"category": "Route53Resolver",
"description": "This release adds support for query type configuration on firewall rules that enables customers for granular action (ALLOW, ALERT, BLOCK) by DNS query type."
}
]
7 changes: 6 additions & 1 deletion CHANGELOG.md
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# Changelog for AWS SDK for JavaScript
<!--LATEST=2.1531.0-->
<!--LATEST=2.1532.0-->
<!--ENTRYINSERT-->

## 2.1532.0
* feature: CodeBuild: Aws CodeBuild now supports new compute type BUILD_GENERAL1_XLARGE
* feature: EC2: Amazon EC2 R7iz bare metal instances are powered by custom 4th generation Intel Xeon Scalable processors.
* feature: Route53Resolver: This release adds support for query type configuration on firewall rules that enables customers for granular action (ALLOW, ALERT, BLOCK) by DNS query type.

## 2.1531.0
* feature: Connect: Minor trait updates for User APIs
* feature: QConnect: Marked SearchQuickResponses API as readonly.
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -69,7 +69,7 @@ require('aws-sdk/lib/maintenance_mode_message').suppress = true;
To use the SDK in the browser, simply add the following script tag to your
HTML pages:

<script src="https://sdk.amazonaws.com/js/aws-sdk-2.1531.0.min.js"></script>
<script src="https://sdk.amazonaws.com/js/aws-sdk-2.1532.0.min.js"></script>

You can also build a custom browser SDK with your specified set of AWS services.
This can allow you to reduce the SDK's size, specify different API versions of
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3 changes: 2 additions & 1 deletion apis/codebuild-2016-10-06.normal.json
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"BUILD_GENERAL1_SMALL",
"BUILD_GENERAL1_MEDIUM",
"BUILD_GENERAL1_LARGE",
"BUILD_GENERAL1_XLARGE",
"BUILD_GENERAL1_2XLARGE",
"BUILD_LAMBDA_1GB",
"BUILD_LAMBDA_2GB",
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},
"computeType": {
"shape": "ComputeType",
"documentation": "<p>Information about the compute resources the build project uses. Available values include:</p> <ul> <li> <p> <code>BUILD_GENERAL1_SMALL</code>: Use up to 3 GB memory and 2 vCPUs for builds.</p> </li> <li> <p> <code>BUILD_GENERAL1_MEDIUM</code>: Use up to 7 GB memory and 4 vCPUs for builds.</p> </li> <li> <p> <code>BUILD_GENERAL1_LARGE</code>: Use up to 16 GB memory and 8 vCPUs for builds, depending on your environment type.</p> </li> <li> <p> <code>BUILD_GENERAL1_2XLARGE</code>: Use up to 145 GB memory, 72 vCPUs, and 824 GB of SSD storage for builds. This compute type supports Docker images up to 100 GB uncompressed.</p> </li> <li> <p> <code>BUILD_LAMBDA_1GB</code>: Use up to 1 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_2GB</code>: Use up to 2 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_4GB</code>: Use up to 4 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_8GB</code>: Use up to 8 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_10GB</code>: Use up to 10 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> </ul> <p> If you use <code>BUILD_GENERAL1_SMALL</code>: </p> <ul> <li> <p> For environment type <code>LINUX_CONTAINER</code>, you can use up to 3 GB memory and 2 vCPUs for builds. </p> </li> <li> <p> For environment type <code>LINUX_GPU_CONTAINER</code>, you can use up to 16 GB memory, 4 vCPUs, and 1 NVIDIA A10G Tensor Core GPU for builds.</p> </li> <li> <p> For environment type <code>ARM_CONTAINER</code>, you can use up to 4 GB memory and 2 vCPUs on ARM-based processors for builds.</p> </li> </ul> <p> If you use <code>BUILD_GENERAL1_LARGE</code>: </p> <ul> <li> <p> For environment type <code>LINUX_CONTAINER</code>, you can use up to 15 GB memory and 8 vCPUs for builds. </p> </li> <li> <p> For environment type <code>LINUX_GPU_CONTAINER</code>, you can use up to 255 GB memory, 32 vCPUs, and 4 NVIDIA Tesla V100 GPUs for builds.</p> </li> <li> <p> For environment type <code>ARM_CONTAINER</code>, you can use up to 16 GB memory and 8 vCPUs on ARM-based processors for builds.</p> </li> </ul> <p>For more information, see <a href=\"https://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref-compute-types.html\">Build Environment Compute Types</a> in the <i>CodeBuild User Guide.</i> </p>"
"documentation": "<p>Information about the compute resources the build project uses. Available values include:</p> <ul> <li> <p> <code>BUILD_GENERAL1_SMALL</code>: Use up to 3 GB memory and 2 vCPUs for builds.</p> </li> <li> <p> <code>BUILD_GENERAL1_MEDIUM</code>: Use up to 7 GB memory and 4 vCPUs for builds.</p> </li> <li> <p> <code>BUILD_GENERAL1_LARGE</code>: Use up to 16 GB memory and 8 vCPUs for builds, depending on your environment type.</p> </li> <li> <p> <code>BUILD_GENERAL1_XLARGE</code>: Use up to 70 GB memory and 36 vCPUs for builds, depending on your environment type.</p> </li> <li> <p> <code>BUILD_GENERAL1_2XLARGE</code>: Use up to 145 GB memory, 72 vCPUs, and 824 GB of SSD storage for builds. This compute type supports Docker images up to 100 GB uncompressed.</p> </li> <li> <p> <code>BUILD_LAMBDA_1GB</code>: Use up to 1 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_2GB</code>: Use up to 2 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_4GB</code>: Use up to 4 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_8GB</code>: Use up to 8 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> <li> <p> <code>BUILD_LAMBDA_10GB</code>: Use up to 10 GB memory for builds. Only available for environment type <code>LINUX_LAMBDA_CONTAINER</code> and <code>ARM_LAMBDA_CONTAINER</code>.</p> </li> </ul> <p> If you use <code>BUILD_GENERAL1_SMALL</code>: </p> <ul> <li> <p> For environment type <code>LINUX_CONTAINER</code>, you can use up to 3 GB memory and 2 vCPUs for builds. </p> </li> <li> <p> For environment type <code>LINUX_GPU_CONTAINER</code>, you can use up to 16 GB memory, 4 vCPUs, and 1 NVIDIA A10G Tensor Core GPU for builds.</p> </li> <li> <p> For environment type <code>ARM_CONTAINER</code>, you can use up to 4 GB memory and 2 vCPUs on ARM-based processors for builds.</p> </li> </ul> <p> If you use <code>BUILD_GENERAL1_LARGE</code>: </p> <ul> <li> <p> For environment type <code>LINUX_CONTAINER</code>, you can use up to 15 GB memory and 8 vCPUs for builds. </p> </li> <li> <p> For environment type <code>LINUX_GPU_CONTAINER</code>, you can use up to 255 GB memory, 32 vCPUs, and 4 NVIDIA Tesla V100 GPUs for builds.</p> </li> <li> <p> For environment type <code>ARM_CONTAINER</code>, you can use up to 16 GB memory and 8 vCPUs on ARM-based processors for builds.</p> </li> </ul> <p>For more information, see <a href=\"https://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref-compute-types.html\">Build Environment Compute Types</a> in the <i>CodeBuild User Guide.</i> </p>"
},
"environmentVariables": {
"shape": "EnvironmentVariables",
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4 changes: 3 additions & 1 deletion apis/ec2-2016-11-15.normal.json
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"m7i.metal-24xl",
"m7i.metal-48xl",
"r7i.metal-24xl",
"r7i.metal-48xl"
"r7i.metal-48xl",
"r7iz.metal-16xl",
"r7iz.metal-32xl"
]
},
"InstanceTypeHypervisor": {
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