Summary Implement a system that categorizes all job failures in CircleCI by type, provides robust filtering capabilities, and automates credit refunds for platform-related failures. Problem Statement When jobs fail in CircleCI, customers: Cannot easily filter and categorize failures by their underlying cause or type Struggle to distinguish between different failure categories (infrastructure, CircleCI errors, configuration, code, dependencies, etc.) Lack the ability to analyze patterns in specific types of failures across their pipelines Waste time manually investigating and categorizing failures that could be automatically classified Have no streamlined way to identify and receive credit refunds for platform-related failures Use Cases: Engineers need to filter out CircleCI related failures to focus on actual code issues Team leads want to analyze trends in specific failure types over time Organizations need to identify recurring failure patterns across multiple projects Finance teams need to track and recover credits spent on platform-related failures Administrators need to validate and request refunds for credits spent on CircleCI errors/issues Proposed Solution: Implement a comprehensive failure type classification and filtering system with integrated credit refund automation: Failure Classification Framework Create a taxonomy of failure types covering all possible job failures Include categories such as: Infrastructure failures Platform issues Resource limitations (memory, CPU, disk) Configuration errors (YAML, environment) Dependency failures (build tools, libraries) Test failures (unit, integration, UI) Deployment failures Timeout issues Automatically classify failures using pattern matching and machine learning Flag platform-responsibility failures that qualify for credit refunds Allow users to manually classify or reclassify failures when needed Enhanced Filtering Interface Add failure type as a primary filter in the jobs dashboard Enable multi-select filtering across multiple failure types Provide nested category filtering (main category → subcategory) Allow combining failure type filters with other existing filters (project, branch, user, etc.) Include specific filters for refund-eligible failures Support saving and sharing of filter configurations Automated Credit Refund System Automatically identify jobs that failed due to platform issues Calculate credit usage for refund-eligible failures Generate monthly credit refund reports with itemized failure details Provide one-click refund request functionality for eligible failures Implement automatic credit refunds for confirmed platform issues Create an audit trail of refund requests and processing Include refund status tracking (pending, approved, processed) Credit Usage Analytics Display historical credit usage broken down by failure types Show potential savings from addressing specific failure types Track refunded credits vs. total credits used Provide forecasting based on failure patterns and credit usage API Integration Extend the CircleCI API to include failure type parameters Enable programmatic filtering of jobs by failure type Support credit refund status and requests via API Allow third-party integrations to leverage failure type and credit data Business Value Improved Troubleshooting Efficiency: Reduces time spent analyzing failures Better Resource Allocation: Helps teams focus on the most impactful failure types Enhanced Visibility: Provides clear insights into failure patterns Financial Fairness: Ensures customers don't pay for platform-related issues Reduced Support Burden: Decreases manual credit refund requests and processing Increased Customer Trust: Demonstrates transparency and accountability Technical Considerations Requires development of a comprehensive failure classification system Must integrate with billing and credit management systems Should handle both real-time classification and historical reclassification Needs automated detection algorithms for platform-related failures Must maintain high performance with complex filtering Should include approval workflows for credit refunds Success Metrics Reduction in time spent troubleshooting failures Decrease in support tickets related to credit refunds Increased automation rate for refund processing User satisfaction with failure classification accuracy Adoption of failure type filtering across the user base Improved transparency in credit usage reporting Prioritization Factors: This feature addresses both technical and financial pain points for CircleCI users. By enabling filtering by failure type and automating credit refunds, we can significantly improve the user experience, make troubleshooting more efficient, ensure fair billing practices, and reduce administrative overhead for both customers and CircleCI support.
