DevOps Best Practices Impact Report

Measuring the impact of DevOps best practices implementation for a client. Feature environments setup followed by continuous deployment to production (Auto-Deploy) on 12 December 2023 were a game changer in the Software Development Lifecycle.

This also showcases the importance of a strong automated testing culture and constant costs management optimization.

This transformation was conducted following 12-Factor App methodology and Expand/Contract patterns to minimize incidents (uptime > 99% for the period 2022-2025).

The Dashboard

➡️ VIEW LIVE DASHBOARD ⚡

📅 Schedule a consultation - Let's discuss your DevOps and DataOps transformation

• Deployment Success Rates: Before vs After Auto-Deploy comparison
• Deployment Speed Metrics: Time reduction analysis
• Test Coverage Trends: Unit test coverage and E2E test growth
• Infrastructure Costs: AWS EC2 costs for feature environments
• Feature Environment Usage: Creation patterns over time
• Data Pipeline Reliability: Failure rate improvements

How to Re-generate the Dashboard

Note: This repository doesn't include the raw .csv data files for security reasons. You'll need to provide your own data files in the expected format.

Prerequisites

• Python 3.8 or higher
• Git

Setup Instructions

1. Clone the repository

   git clone <repository-url>
   cd devops-impact-report

2. Create and activate virtual environment

   # Create virtual environment
   python3 -m venv .venv
   
   # Activate virtual environment
   source .venv/bin/activate

3. Install required packages

   # Install dependencies
   pip install -r requirements.txt
   
   # Or install manually:
   pip install pandas

4. Prepare your data files (Required CSV files)

   The script expects the following data files in the project root:

   • deploy_prod_pipelines_2022_2025_argocd_refined.csv - Deployment pipeline data
   • coverage_data_unit_tests.csv - Unit test coverage data
   • coverage_e2e_tests_count.csv - E2E test count data
   • ec2_costs_us_east_1.csv - AWS EC2 cost data
   • feature_environments_created_count.csv - Feature environment creation data
   • pipeline_success_failure_correlation.csv - Pipeline correlation data
   • data_pipeline_correlation_metrics_filtered.json - Pipeline metrics JSON

5. Generate the dashboard

   python3 create_devops_impact_report.py

6. View the dashboard

   Open autodeploy_impact_dashboard.html in your browser to view the interactive dashboard.

Author

Antoine ROUGEOT (Tony Engineering OÜ)
LinkedIn: antoinerougeot