BACKGROUND
Diagnosing live microservice logs often means waiting for sluggish web consoles or dealing with frozen terminals when attempting ad-hoc local aggregations.
APPROACH
Delegated asynchronous I/O and UI rendering to Rust while offloading intensive dataframe computations to Polars in Python, connected asynchronously through Redis.
HOW IT WORKS
- 01
Ingest
Collect distributed logs via lightweight agents
- 02
Buffer
Order and buffer events in Redis streams
- 03
Analyze
Compute windowed aggregations with Polars
- 04
Visualize
Display live interactive charts in Ratatui
ARCHITECTURE
DESIGN DECISIONS
Decoupled Visualization and Compute
Utilizes Rust for smooth 60fps terminal updates and Python Polars for efficient analytical queries.
Redis Event Bus Decoupling
Ensures producers, aggregators, and viewers remain loosely coupled without direct process dependencies.
Keyboard-First Investigation
Built with vim-style navigation, regex filtering, and OSC 52 clipboard copying for lightning-fast investigations.
VERIFICATION
- Docker Compose environment with live sample traffic producers
- Demonstrated stable multi-channel throughput without frame drops
- Clean separation of concerns verified across service boundaries
STATUS & NEXT
Functional prototype verifying the speed and ergonomics of asynchronous stream processing in the terminal.
NEXT STEPS
- Configurable dynamic Redis connection discovery
- Expanded automated test coverage for complex filter logic
- One-click multi-container deployment scripts