Version: 0.0.42

[0.0.39] - 2025-11-17

LRU-Cache Implementation: Introduced LRU (Least Recently Used) caching mechanism to optimize data access patterns and reduce redundant computations.
Extended Chart Integration: Comprehensive integration of all chart types with expanded chart intent capabilities for more flexible and powerful data visualization.

Kubernetes Deployment Architecture: Complete migration to Kubernetes Pod Operator, marking the first successful packaging of the entire application using this operator for improved scalability and orchestration.

Backend Performance Optimization: Massive refactoring of backend components with significant performance improvements:
- Conducted detailed performance analysis using PySpy profiler
- Identified and eliminated bottlenecks in critical code paths
- Achieved substantial reduction in response times and resource consumption
User Experience Enhancements: Various improvements throughout the application to deliver a smoother and more intuitive user experience.

Performance profiling with PySpy revealed key optimization opportunities in data processing pipelines
LRU-Cache implementation reduces database queries and accelerates frequently accessed data retrieval
Kubernetes Pod Operator deployment provides better resource management and simplified scaling capabilities

Continuing to leverage Kubernetes infrastructure for enhanced reliability and performance
Further optimization of caching strategies based on usage patterns
Expanding chart integration capabilities in upcoming releases