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README.md

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@@ -101,7 +101,7 @@ Streaming function, on the other hand, sends back data as soon as it's available
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waiting for all the data to be ready. It processes and returns the response in chunks, piece by
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piece, which can be useful when you want to start delivering results right away, especially for
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large or ongoing tasks. This allows for faster responses and can handle data as it comes
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in. [More details here.](https://docs.aws.amazon.com/lambda/latest/dg/configuration-response-streaming.html).
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in. [More details here](https://docs.aws.amazon.com/lambda/latest/dg/configuration-response-streaming.html).
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For example, `SampleStreamingHandler` reads a large json file and streams it by chunks.
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```kotlin
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locate Lambda handler's executable file, e.g. `YOUR_MODULE.kexe`. The name of the file (including
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the extension) will be used as `handler` name. Don't forget to specify it upon
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lambda-function creation.
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3.
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Execute `(echo '#!/bin/sh' > bootstrap && echo './"$_HANDLER"' >> bootstrap && chmod +x bootstrap && zip -r bootstrap.zip ./*)`
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3. Execute `(echo '#!/bin/sh' > bootstrap && echo './"$_HANDLER"' >> bootstrap && chmod +x bootstrap && zip -r bootstrap.zip ./*)`
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4. Deploy bootstrap.zip archive to AWS. If you have never used AWS Lambda
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before, [learn how to deploy Lambda function as zip archive manually](https://docs.aws.amazon.com/lambda/latest/dg/configuration-function-zip.html)
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or
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using [AWS CLI](https://docs.aws.amazon.com/codedeploy/latest/userguide/getting-started-codedeploy.html):
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```bash
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$ aws lambda create-function --function-name sample \
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--handler sample.kexe \ # Important to specify the name of the Lambda\'s executable
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--handler sample.kexe \ # Important to specify the name of the Lambda executable
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--zip-file bootstrap.zip \
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--runtime provided.al2023 \ # Change this to provided.al2 if you would like to use Amazon Linux 2
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--role arn:aws:iam::XXXXXXXXXXXXX:role/your_lambda_execution_role \
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The Runtime uses AWS logging conventions for enhanced log capture, supporting String and JSON log
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output
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format. It also allows you to dynamically control log levels without altering your code, simplifying
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format. It also allows to dynamically control log levels without altering your code, simplifying
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the debugging process. Additionally, you can direct logs to specific Amazon CloudWatch log groups,
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making log management and aggregation more efficient at scale. More details on how to set log format
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and level refer to the article.

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