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Copy file name to clipboardExpand all lines: .github/workflows/publish_v3_layer.yml
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# PROCESS
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#
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# 1. Compile Layer using cdk-aws-lambda-powertools-layer CDK construct for Python3.8-3.12 and x86_64/ARM architectures (uses custom runner as it's CPU heavy)
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# 1. Compile Layer using cdk-aws-lambda-powertools-layer CDK construct for Python3.9-3.13 and x86_64/ARM architectures (uses custom runner as it's CPU heavy)
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# 2. Kick off pipeline for beta, prod, and canary releases
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# 3. Create PR to update trunk so staged docs also point to the latest Layer ARN, when merged
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# 4. Builds and publishes docs with latest Layer ARN using given version (generally coming from release)
Copy file name to clipboardExpand all lines: .github/workflows/reusable_deploy_v3_sar.yml
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#
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# 1. This workflow starts after the layer artifact is produced on `publish_v3_layer`
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# 2. We use the same layer artifact to ensure the SAR app is consistent with the published Lambda Layer
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# 3. We publish the SAR for 3.8 to 3.13 Python runtime and both x86_64 and arm64 (see `matrix` section)
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# 3. We publish the SAR for 3.9 to 3.13 Python runtime and both x86_64 and arm64 (see `matrix` section)
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# 4. We use `sam package` and `sam publish` to publish the SAR app
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# 5. We remove the previous Canary stack (if present) and deploy a new one to test the SAR App. We retain the Canary in the account for debugging purposes
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# 6. Finally the published SAR app is made public on the PROD environment
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