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AWS Services Cloud

18 Blueprints

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Detect data anomalies in new S3 files with DuckDB SQL and email a CSV of the bad rows.

Ship Kestra workflow and system logs to AWS CloudWatch on a daily schedule for centralized monitoring, auditing, and observability.

Watch a CloudWatch backlog metric and fire an EMR Serverless Spark job only when work is pending.

Build a Docker image and push it to AWS ECR using short-lived token authentication, all in one Kestra flow.

Trigger a Kestra flow automatically whenever new files land in an Amazon S3 bucket, then process and archive them.

Trigger a Python data pipeline automatically whenever a new file lands in an Amazon S3 bucket.

Download a zip archive, unpack it, and fan out all extracted files to Amazon S3 in parallel.

Scan an AWS DynamoDB table and pass the extracted rows to a downstream processing task.

React to new Amazon S3 objects and fan out by file type, routing JSON to AWS Lambda and everything else to SNS, with a Slack notification.

Run a Glue ETL job, validate the output with Athena, then cache the headline KPI in DynamoDB.

Provision AWS Batch on ECS Fargate with Terraform, then run parallel Python workloads on it from one Kestra flow.

Sync AWS resource metadata into Postgres with CloudQuery, then flag public S3 buckets with SQL.

List objects in an Amazon S3 bucket by prefix and fan out over every file in parallel with Kestra.

Invoke multiple AWS Lambda functions in parallel, target specific versions and aliases, pass custom payloads, and parse the JSON results.

Publish custom application and system events to AWS EventBridge using inline definitions or bulk JSON payloads.

Authenticate with Amazon ECR, pull a private container image, and run a Python script inside it.

Trigger a Kestra flow automatically whenever a new message lands in an Amazon SQS queue.

Publish inline events and API-sourced JSON to AWS Kinesis Data Streams in bulk, with automatic ION conversion.