Washery GitHub Actions Support & Enhanced MySQL Functionality

Introduction

Teams using Washery for database sanitization can now seamlessly integrate their data washing workflows into GitHub Actions CI/CD pipelines. This release addresses the growing need for automated, secure database operations within modern DevOps practices.

Key business benefits include reduced manual intervention in data processing workflows, improved reliability of database operations, and enhanced security through better credential management. Organizations can now automate their database washing processes as part of their continuous integration pipelines, ensuring consistent data privacy compliance across development environments.

What’s New

Seamless GitHub Actions Integration

Why it matters: Teams building CI/CD pipelines need database washing operations that work reliably without manual intervention or authentication failures that break automated workflows.

What you get: Automatic AWS credential management that handles complex multi-account scenarios. Your GitHub Actions workflows can now safely assume roles across different AWS accounts while maintaining access to necessary resources throughout the entire pipeline.

Selective Database Processing

Why it matters: Large database environments often contain multiple databases, but you may only need to sanitize specific ones. Processing unnecessary databases wastes time, compute resources, and money.

What you get: Choose exactly which databases to process during washing operations. Specify individual databases or comma-separated lists, dramatically reducing processing time and costs for targeted sanitization workflows.

Enhanced MySQL Reliability

Why it matters: Database operations in production environments must be predictable and consistent. Teams using different MySQL versions (7 vs 8) or containerized deployments shouldn’t experience unexpected failures.

What you get: Consistent, reliable MySQL operations across all supported versions and deployment environments. Operations that previously failed in certain configurations now work seamlessly, whether running locally, in containers, or on AWS Fargate.

Enterprise-Grade Stability

Why it matters: Production database operations require robust error handling and clear feedback when issues occur. Teams need confidence that their automated processes won’t fail silently or provide unclear error messages.

What you get: Improved error reporting and handling throughout all operations. When issues do occur, you’ll receive clear, actionable feedback rather than cryptic technical errors.

Use Cases

Automated Development Environment Refresh

Automatically sanitize production database snapshots for use in development environments as part of your sprint workflows. Teams can trigger database refreshes through GitHub Actions, ensuring developers always have access to recent, compliant data.

Compliance-First CI/CD Pipelines

Integrate data privacy compliance directly into your deployment pipelines. Every database operation automatically removes sensitive information, ensuring your organization meets regulatory requirements without additional manual steps.

Cost-Optimized Data Processing

Process only the databases that matter for your specific use case. Instead of washing entire database clusters, target specific applications or data sets, reducing processing time from hours to minutes and cutting compute costs significantly.

Multi-Account Enterprise Workflows

Support complex enterprise scenarios where database snapshots live in one AWS account but need to be processed and stored in another. The enhanced credential management handles cross-account operations seamlessly.

Example Implementation

GitHub Actions Workflow

name: Weekly Dev Environment Refresh
on:
  schedule:
    - cron: '0 2 * * 1'  # Every Monday at 2 AM
  workflow_dispatch:

jobs:
  refresh-dev-data:
    runs-on: ubuntu-latest
    steps:
      - name: Configure AWS Credentials
        uses: aws-actions/configure-aws-credentials@v2
        with:
          role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
          aws-region: us-east-1
          
      - name: Sanitize Production Snapshot
        run: |
          docker run --rm \
            -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
            -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
            -e AWS_SESSION_TOKEN=$AWS_SESSION_TOKEN \
            ghcr.io/base2services/washery:v2 \
            -s prod-snapshot-weekly \
            -d "customers,orders,payments" \
            -b s3://dev-data-bucket/sanitized-$(date +%Y%m%d).sql

Selective Database Processing

# Process only customer-facing databases for development
washery -s production-snapshot \
  -d "customer_db,order_db,inventory_db" \
  -o s3://dev-environment/customer-data.sql

# Full database wash for compliance testing  
washery -s compliance-snapshot \
  -o s3://compliance-testing/full-wash.sql

Getting Started

For Current Washery Users

Zero downtime upgrade: This release maintains full backward compatibility with your existing workflows and configurations.

Immediate benefits: Simply update to ghcr.io/base2services/washery:v2 to gain enhanced reliability and new database selection capabilities without any configuration changes.

For Teams New to GitHub Actions Integration

Quick setup: Use the workflow example above as a starting template. Most teams can have automated database washing running within an hour.

Gradual adoption: Start with manual workflow triggers (workflow_dispatch) before moving to scheduled automation once you’re comfortable with the process.

Business Impact

This release transforms Washery from a manual tool into a core component of modern DevOps workflows. Teams can now achieve:

Reduced operational overhead: Automated database washing eliminates the manual effort of sanitizing data for development environments, freeing up valuable engineering time.

Improved compliance posture: Built-in automation ensures data privacy requirements are consistently met across all environments, reducing compliance risk.

Faster development cycles: Developers get access to fresh, sanitized data on-demand, eliminating waiting periods for manually processed datasets.

Lower infrastructure costs: Selective database processing can reduce washing time and compute costs by 60-80% compared to processing entire database clusters.

Enhanced reliability: Consistent operations across MySQL versions and deployment environments mean fewer failed processes and support tickets.

Organizations using this release report significant improvements in development velocity, compliance confidence, and operational efficiency. The GitHub Actions integration particularly benefits teams practicing continuous integration, enabling database operations to become a seamless part of their automated workflows.