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:

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

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

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)

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

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.