A collection of ready-to-deploy examples, blog companion code, and hands-on workshops demonstrating data processing and analytics patterns on AWS.
This repository is organized into three categories:
| Folder | Description |
|---|---|
blogs/ |
Code accompanying AWS blog posts — deploy the exact architecture discussed in each article |
samples/ |
Standalone, self-contained examples you can launch independently |
workshops/ |
Step-by-step guided labs for deeper learning |
| Name | Services | Description |
|---|---|---|
| Medallion Architecture with DevOps Agent | AWS Glue, Amazon MWAA, Amazon Redshift, Amazon S3, EventBridge, Lambda | Bronze → Silver → Gold data pipeline with autonomous incident troubleshooting |
Coming soon — standalone examples covering common data processing patterns.
Coming soon — guided, hands-on labs for building analytics solutions.
This repo provides examples across the AWS data and analytics stack, including:
- Data Integration & ETL — AWS Glue, AWS Lambda
- Data Lakes & Storage — Amazon S3, AWS Lake Formation
- Data Warehousing — Amazon Redshift
- Streaming & Real-Time — Amazon Kinesis, Amazon MSK
- Query & Analytics — Amazon Athena, Amazon EMR
- Orchestration — Amazon MWAA (Apache Airflow), AWS Step Functions
- Visualization — Amazon QuickSight
- Operational AI — AWS DevOps Agent (autonomous troubleshooting)
Not every service is covered today — content is actively growing. Contributions are welcome!
Each example is self-contained with its own README, prerequisites, and deployment instructions. Pick a folder and follow the guide inside.
General prerequisites:
- An AWS account
- AWS CLI v2 installed and configured
- Permissions to create the resources described in each example (IAM roles, VPCs, etc.)
We welcome contributions! Whether it's a new sample, a bug fix, or improved documentation — see CONTRIBUTING for guidelines.
See CONTRIBUTING for more information.
This library is licensed under the MIT-0 License. See the LICENSE file.