
Matan L. contributed to the starkware-libs/sequencer repository, focusing on backend systems for blockchain transaction processing and observability. Over 13 months, he engineered features such as centralized dashboard metrics, robust alerting, and improved synchronization for staking and consensus. Using Rust and Python, Matan implemented memory optimizations, error handling, and dashboard enhancements that improved throughput, reliability, and operational visibility. His work included tuning epoch timing, refining Prometheus metrics, and hardening input validation for Ethereum smart contracts. By addressing both performance and maintainability, Matan delivered solutions that reduced debugging overhead, increased deployment stability, and supported scalable monitoring across distributed systems.
Month: 2026-03. This month focused on strengthening staking synchronization and data integrity in the sequencer by tuning epoch timing and hardening input validation. Key changes include increasing minimum epoch length to ~5 minutes to improve alignment with the consensus and rejecting out-of-range U256 events on the Ethereum base layer, reducing risk of desynchronization and invalid state transitions. These changes enhance network reliability, validator performance, and data safety, with measurable commit-level traceability.
Month: 2026-03. This month focused on strengthening staking synchronization and data integrity in the sequencer by tuning epoch timing and hardening input validation. Key changes include increasing minimum epoch length to ~5 minutes to improve alignment with the consensus and rejecting out-of-range U256 events on the Ethereum base layer, reducing risk of desynchronization and invalid state transitions. These changes enhance network reliability, validator performance, and data safety, with measurable commit-level traceability.
February 2026 — Starkware Sequencer: Reliability and hygiene improvements. Implemented division-by-zero safeguards for Apollo dashboard metrics by clamping denominators to non-zero values, improving stability of dashboard metrics. Removed an incorrectly committed native classes whitelist config to prevent potential build misconfigurations, improving deployment hygiene. These changes enhance dashboard reliability, prevent data anomalies, and reduce build-time risk. Demonstrates disciplined debugging, targeted bug fixes, and strong version-control practices.
February 2026 — Starkware Sequencer: Reliability and hygiene improvements. Implemented division-by-zero safeguards for Apollo dashboard metrics by clamping denominators to non-zero values, improving stability of dashboard metrics. Removed an incorrectly committed native classes whitelist config to prevent potential build misconfigurations, improving deployment hygiene. These changes enhance dashboard reliability, prevent data anomalies, and reduce build-time risk. Demonstrates disciplined debugging, targeted bug fixes, and strong version-control practices.
Month: 2026-01 — Focused on reliability and edge-case resilience in the Apollo Starknet Client within the Sequencer repository. Delivered targeted fixes to ABORTED block handling, improving stability, error reporting, and data integrity for transaction processing pipelines. Result: reduced crash risk and smoother downstream processing for ABORTED blocks.
Month: 2026-01 — Focused on reliability and edge-case resilience in the Apollo Starknet Client within the Sequencer repository. Delivered targeted fixes to ABORTED block handling, improving stability, error reporting, and data integrity for transaction processing pipelines. Result: reduced crash risk and smoother downstream processing for ABORTED blocks.
December 2025 monthly summary for starkware-libs/sequencer focused on expanding observability, enriching metrics visualization, improving gas monitoring, and stabilizing test reliability. The work delivered clearer network visibility, more accurate data representations, and more robust CI, enabling faster incident response, better capacity planning, and higher confidence in deployment pipelines.
December 2025 monthly summary for starkware-libs/sequencer focused on expanding observability, enriching metrics visualization, improving gas monitoring, and stabilizing test reliability. The work delivered clearer network visibility, more accurate data representations, and more robust CI, enabling faster incident response, better capacity planning, and higher confidence in deployment pipelines.
Month 2025-11: Delivered a suite of dashboard, metric, and observability enhancements for the Sequencer repo that improve reliability, visibility, and developer productivity. Key architectural and feature improvements include a centralized metric query builder with a standardized 10-minute window, flexible panel inputs via IntoExprs and Panel::new, a new MetricCommon trait for unified metric handling, enhanced metric queries with sum_by_label and expanded histogram buckets, and improved operational visibility with state-sync panels, time-to-finish indicators, and layout improvements. In addition, the release reduced log noise and debugging overhead (lowered debug noise, reduced connection attempt logging) and streamlined config-diffs output. These changes collectively reduce time to insight, lower maintenance burden, and support scalable monitoring as the system grows.
Month 2025-11: Delivered a suite of dashboard, metric, and observability enhancements for the Sequencer repo that improve reliability, visibility, and developer productivity. Key architectural and feature improvements include a centralized metric query builder with a standardized 10-minute window, flexible panel inputs via IntoExprs and Panel::new, a new MetricCommon trait for unified metric handling, enhanced metric queries with sum_by_label and expanded histogram buckets, and improved operational visibility with state-sync panels, time-to-finish indicators, and layout improvements. In addition, the release reduced log noise and debugging overhead (lowered debug noise, reduced connection attempt logging) and streamlined config-diffs output. These changes collectively reduce time to insight, lower maintenance burden, and support scalable monitoring as the system grows.
October 2025 — Delivered observability and dashboard enhancements for transaction monitoring in the sequencer, including consolidated logging for transactions and gateway errors and improved consensus visuals. L1 retry and deployment reliability tuning reduced delays by avoiding retries when core communicates with L1. L1 provider robustness enhanced with graceful handling of unknown L1 event types and added support for transaction cancellations. These changes improved production visibility, reduced end-to-end latency with Layer 1 services, and increased resilience in L1 interactions. Notable commits include: 12854cae6a500552ec750396896708bc54ccb721; 9c155f34aa712e538d5be0861efa8ced624814e1; 0c433e7193bcde9c281c8de75e0d82a8a7d594ea; d499f89fa0b406f38eaa382193e53ae5d074e7c2; 4b26a804a3f75f2f3eb71c8ef236f078a2281ca3; d165c66925c95feec2ea0585273e56a3a76199fd; 53d54e698e91bedec6f41ddd98fdbc4f0103837d. Technologies/skills demonstrated: observability engineering (logging, dashboards), reliability tuning (retry behavior), safe L1 event handling, cancellation support, and cross-team collaboration.
October 2025 — Delivered observability and dashboard enhancements for transaction monitoring in the sequencer, including consolidated logging for transactions and gateway errors and improved consensus visuals. L1 retry and deployment reliability tuning reduced delays by avoiding retries when core communicates with L1. L1 provider robustness enhanced with graceful handling of unknown L1 event types and added support for transaction cancellations. These changes improved production visibility, reduced end-to-end latency with Layer 1 services, and increased resilience in L1 interactions. Notable commits include: 12854cae6a500552ec750396896708bc54ccb721; 9c155f34aa712e538d5be0861efa8ced624814e1; 0c433e7193bcde9c281c8de75e0d82a8a7d594ea; d499f89fa0b406f38eaa382193e53ae5d074e7c2; 4b26a804a3f75f2f3eb71c8ef236f078a2281ca3; d165c66925c95feec2ea0585273e56a3a76199fd; 53d54e698e91bedec6f41ddd98fdbc4f0103837d. Technologies/skills demonstrated: observability engineering (logging, dashboards), reliability tuning (retry behavior), safe L1 event handling, cancellation support, and cross-team collaboration.
Concise monthly report for 2025-09 covering features delivered, observability enhancements, and latency instrumentation for the Apollo dashboard and gateway in the sequencer repo.
Concise monthly report for 2025-09 covering features delivered, observability enhancements, and latency instrumentation for the Apollo dashboard and gateway in the sequencer repo.
Performance-focused monthly contribution for 2025-08: Delivered Apollo Dashboard Alerting Improvements in starkware-libs/sequencer, centralizing alert definitions, expanding evaluation windows, tuning thresholds, and consolidating alert config for the Apollo dashboard. Implemented bug fixes to alerting logic (Prometheus query corrections and division-by-zero guard) that stabilized latency alerts and reduced false positives. These changes improved alert reliability, reduced noise, and enhanced maintainability, enabling faster incident response and clearer operational signals.
Performance-focused monthly contribution for 2025-08: Delivered Apollo Dashboard Alerting Improvements in starkware-libs/sequencer, centralizing alert definitions, expanding evaluation windows, tuning thresholds, and consolidating alert config for the Apollo dashboard. Implemented bug fixes to alerting logic (Prometheus query corrections and division-by-zero guard) that stabilized latency alerts and reduced false positives. These changes improved alert reliability, reduced noise, and enhanced maintainability, enabling faster incident response and clearer operational signals.
July 2025 monthly summary for starkware-libs/sequencer: Delivered reliability and stability improvements across alerting, deployments, tooling, and codebase. Key outcomes include removal of a duplicate http_server_idle alert to reduce noise; stabilization of deployments by extending the L1 handler cooldown to exceed the scraping interval; enhancement of merge tooling with an auto-delete-from-dst mode to correctly resolve destination deletions; and broad codebase cleanup addressing merge conflicts, error handling, and deprecated SecretKey usage. These changes increased alert accuracy, prevented race conditions, streamlined merges, and improved maintainability and security posture.
July 2025 monthly summary for starkware-libs/sequencer: Delivered reliability and stability improvements across alerting, deployments, tooling, and codebase. Key outcomes include removal of a duplicate http_server_idle alert to reduce noise; stabilization of deployments by extending the L1 handler cooldown to exceed the scraping interval; enhancement of merge tooling with an auto-delete-from-dst mode to correctly resolve destination deletions; and broad codebase cleanup addressing merge conflicts, error handling, and deprecated SecretKey usage. These changes increased alert accuracy, prevented race conditions, streamlined merges, and improved maintainability and security posture.
June 2025: Focused on delivering tooling improvements for commit hygiene and strengthening observability in the Sequencer repository. Key features delivered streamlined commit management; major bugs addressed to improve alert reliability and accuracy.
June 2025: Focused on delivering tooling improvements for commit hygiene and strengthening observability in the Sequencer repository. Key features delivered streamlined commit management; major bugs addressed to improve alert reliability and accuracy.
May 2025 monthly summary for starkware-libs/sequencer focused on release readiness, stability, and cross-component upgrades. Key activities centered on release/versioning and branch management for v0.14.x and the upcoming v0.15.0-rc.0, post-merge stability improvements, and an across-the-board Starknet upgrade to ensure compatibility and test integrity.
May 2025 monthly summary for starkware-libs/sequencer focused on release readiness, stability, and cross-component upgrades. Key activities centered on release/versioning and branch management for v0.14.x and the upcoming v0.15.0-rc.0, post-merge stability improvements, and an across-the-board Starknet upgrade to ensure compatibility and test integrity.
April 2025: Focused on test diagnostics and reliability in starkware-libs/sequencer. Delivered a targeted bug fix to contract file read error reporting in blockifier tests, enriching panic messages with file paths and adding context in get_raw_contract_class. This improves debuggability, reduces time to diagnose failures, and supports faster iteration of contract tests. Demonstrated solid debugging, Rust error handling, and test utility maintenance.
April 2025: Focused on test diagnostics and reliability in starkware-libs/sequencer. Delivered a targeted bug fix to contract file read error reporting in blockifier tests, enriching panic messages with file paths and adding context in get_raw_contract_class. This improves debuggability, reduces time to diagnose failures, and supports faster iteration of contract tests. Demonstrated solid debugging, Rust error handling, and test utility maintenance.
March 2025 — starkware-libs/sequencer Overview: Delivered performance and reliability improvements to the Starknet sequencer with targeted optimizations, user-facing label improvements, and critical internal maintenance. The changes collectively enhanced throughput, accuracy, and maintainability while reducing future risk. Key deliverables: - Performance optimizations: Mempool pruning now computes submission cutoff once and the batcher pre-allocates capacity to avoid reallocations, boosting throughput and efficiency. - Observability and correctness: Fixed logging of total transactions in the consensus orchestrator to correctly sum batch lengths, preventing inaccurate tx counts. - UX improvements: Dashboard now displays accurate and readable transaction reception rate labels, improving operator visibility. - Maintainability: Refactors to internal APIs included renaming eth_to_strk_rate to eth_to_fri_rate (u64 to u128) and reordering init fields for BouncerWeights, plus a minor macro typo fix, improving consistency and future-proofing. Impact: - Business value: Higher transaction throughput, improved accuracy in reporting, and clearer operational dashboards reduce manual debugging and improve confidence in system state. - Technical achievements: Effective memory management, careful refactoring with minimal risk, and consistent initialization across components. Technologies and skills demonstrated: Rust performance tuning, memory allocation optimization, logging accuracy, API refactors, type-safety enhancements, and cross-module coordination.
March 2025 — starkware-libs/sequencer Overview: Delivered performance and reliability improvements to the Starknet sequencer with targeted optimizations, user-facing label improvements, and critical internal maintenance. The changes collectively enhanced throughput, accuracy, and maintainability while reducing future risk. Key deliverables: - Performance optimizations: Mempool pruning now computes submission cutoff once and the batcher pre-allocates capacity to avoid reallocations, boosting throughput and efficiency. - Observability and correctness: Fixed logging of total transactions in the consensus orchestrator to correctly sum batch lengths, preventing inaccurate tx counts. - UX improvements: Dashboard now displays accurate and readable transaction reception rate labels, improving operator visibility. - Maintainability: Refactors to internal APIs included renaming eth_to_strk_rate to eth_to_fri_rate (u64 to u128) and reordering init fields for BouncerWeights, plus a minor macro typo fix, improving consistency and future-proofing. Impact: - Business value: Higher transaction throughput, improved accuracy in reporting, and clearer operational dashboards reduce manual debugging and improve confidence in system state. - Technical achievements: Effective memory management, careful refactoring with minimal risk, and consistent initialization across components. Technologies and skills demonstrated: Rust performance tuning, memory allocation optimization, logging accuracy, API refactors, type-safety enhancements, and cross-module coordination.

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