All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Karpenter Log Analyzer: New feature to analyze Karpenter error logs with AI-powered explanations
- Paste Karpenter error logs (JSON format) to get detailed analysis
- Automatic error categorization (Label Errors, Taint Tolerance, NodePool Limits, Resource Constraints)
- AI-powered explanations using Ollama/LiteLLM (when available)
- Actionable recommendations for resolving scheduling issues
- Visual display of error causes with severity indicators
- Parsed log details showing pod, NodePool, and taint information
- New API endpoint:
POST /api/v1/karpenter/logs/analyze - New UI tab: "Log Analyzer" in the main navigation
0.0.29 - 2025-01-26
- Workload Overview: New comprehensive view for Deployments, StatefulSets, DaemonSets, and Jobs
- Workload Resource Usage: CPU and memory usage tracking for workloads based on running pods
- Jobs Support: Added Kubernetes Jobs to workload discovery and analysis
- Minimalist Tab Navigation: Clean tab-based UI to reduce scrolling and improve navigation
- Column Visibility Controls: Customizable table columns in Workload Overview with essential/all presets
- Workload Summary Statistics: Aggregated CPU, memory, pods, and replicas totals
- Performance Optimizations: Batch pod fetching for workload usage calculation (significant performance improvement)
- Sticky Table Headers: Table headers remain visible while scrolling
- API Endpoint: New
/api/v1/workloads/allendpoint to list all workloads across namespaces
- UI Performance: Optimized rendering by only showing active tab content
- Workload Calculation: Changed from per-workload pod fetching to batch processing (10x+ faster)
- Table Design: More compact table layout with better information density
- Navigation: Replaced section dropdown with minimalist horizontal tabs
- Pagination: Increased default items per page from 20 to 50
- Fixed workload usage calculation performance for large clusters
- Improved pod-to-workload matching accuracy for all workload types
0.0.1 - 2024-12-02
- Initial open source release 🎉
- NodePool-based recommendation engine analyzing actual cluster usage
- Real-time node usage visualization with interactive charts
- AWS Pricing API integration for accurate cost calculations
- Ollama AI-powered explanations for recommendations
- Helm chart for Kubernetes deployment
- Docker images for easy deployment (backend and frontend)
- Comprehensive REST API with Swagger/OpenAPI documentation
- Modern React web UI with real-time updates
- CLI tool for command-line usage and CI/CD integration
- Node disruption tracking
- Cluster cost summary with before/after comparisons
- Support for spot and on-demand instance optimization
- Sidecar deployment pattern for frontend and backend
- Dynamic Swagger host detection for ingress compatibility
- Improved cost calculation accuracy using AWS Pricing API
- Enhanced recommendation algorithm based on actual node capacity
- Better error handling and logging throughout
- Added RBAC configurations for Kubernetes access
- Implemented security best practices in Helm chart
- Added security policy documentation
- Security context configurations for containers