# aws-samples/aws-glue-samples

AWS Glue code samples

Repository: https://github.com/aws-samples/aws-glue-samples
Canonical: https://ross.abutalabs.com/products/aws-glue-samples
Language: Python
License: MIT-0
License Family: permissive
Last push: 2026-08-18T12:44:04+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 3391, "days_push": 15, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1537, forks 832 (observed 2026-08-28T04:05:00.023541+00:00)

## What it is
A collection of code samples, tutorials, and utilities demonstrating AWS Glue, Amazon's serverless data integration and ETL service. It covers Spark ETL jobs, streaming pipelines, schema registry usage, and data migration patterns.

## Use cases
- learn how to write AWS Glue Spark ETL scripts
- stream CDC data from relational databases to Amazon Redshift
- process Amazon MSK data with Glue streaming jobs
- detect and process sensitive data in pipelines
- migrate data into AWS analytics services
- find examples of AWS Glue utilities and best practices

## When to choose
- you are building or learning AWS Glue ETL and streaming jobs
- you need reference code for Glue integrations with S3, Redshift, MSK, or DynamoDB
- you want guided tutorials and workshops on serverless data integration on AWS

## When to avoid
- you need the Glue libraries themselves rather than samples (use awslabs/aws-glue-libs)
- you are not using AWS or want a cloud-agnostic ETL solution
- you need production-ready tooling rather than example code

## Facets
- artifact type: learning-resource
- maturity: active
- function: etl, streaming, data-science, developer-tools
- domain: big-data, cloud-computing, tutorials, analytics
- platform: python, cloud, serverless
- tags: aws-glue, etl, code-samples, spark, data-integration, aws, data-engineering

## Member repositories
- aws-samples/aws-glue-samples (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:00.023541+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:31:00.392412+00:00, confidence not recorded.
  - readme: https://github.com/aws-samples/aws-glue-samples (fetched 2026-08-28T04:05:00.023541+00:00, sha 009b60733dfe)
- Data as of 2026-08-30T08:39:29.467469+00:00.