Madara Sequencer Performance Optimization

The Challenge

The Starkware Exploration Team's Madara StarkNet sequencer was hitting critical performance bottlenecks as the network grew. The existing Substrate-based architecture struggled with high transaction volumes, and teams faced difficulty creating reliable local testnets for development and testing. Performance regressions were hard to diagnose across geographically distributed nodes, leading to frequent firefighting during peak usage periods.

The Solution

We joined the core development team to implement targeted performance optimizations and architectural improvements across the Madara sequencer stack:

• RPC Architecture Optimization: Refactored the RPC server infrastructure to eliminate resource waste and improve memory efficiency across concurrent request handling.
• Enhanced Error Diagnostics: Transformed generic error responses into detailed, actionable diagnostics that dramatically reduced debugging time for developers and operators.
• Network Reliability Engineering: Solved critical issues with genesis configuration consistency, enabling reliable multi-node deployments and automated testnet creation.
• Performance Infrastructure: Developed and integrated advanced consensus mechanisms and benchmarking frameworks to support future scalability improvements.
• Developer Experience Enhancement: Implemented comprehensive tooling improvements including automated workflows, better testing infrastructure, and standardized development processes.

The Impact

The optimizations delivered measurable improvements in scalability, reliability, and developer productivity:

• Resource Efficiency: Significant reduction in memory footprint and improved request handling capacity without hardware upgrades.
• Developer Velocity: Enhanced debugging capabilities and automated workflows cut investigation time and accelerated feature development.
• System Reliability: Eliminated critical distributed systems bugs that caused production incidents, enabling more stable operations under load.
• Future-Proof Architecture: Modular design improvements positioned Madara for continued scaling and protocol evolution.

Technologies Used: Rust, Substrate, distributed systems, consensus algorithms, performance profiling, production observability

Key Skills Demonstrated: Performance optimization, distributed systems architecture, blockchain protocol development, production debugging, systems engineering