July 2026 monthly summary for the kms performance effort focused on benchmarking overhaul, cryptographic performance optimizations, and CI improvements to reliability and throughput.

June 2026 monthly summary for zama-ai/kms focused on reliability, security, and performance improvements across data handling, MPC lifecycle, CI efficiency, and measurement capabilities. Delivered memory-efficient data processing, safer serialization/deserialization, SystemTime-based timestamps, RPC-driven destruction of MPC contexts with complete epoch cleanup, CI/build modernization to reduce overhead, and enhanced throughput measurement with micro-optimizations.

May 2026 performance summary for zama-ai development: - Delivered scalable, profile-driven test material generation and parallel CI enhancements for kms, improving test coverage while reducing CI wall time. API now supports explicit profiles and parties, enabling CI to fetch only necessary test materials and speeding up feedback loops. - Strengthened test infrastructure and reliability across kms with independent task retries, unified data access, and hard errors on missing data; introduced TestEnv builders and centralized material management to lower flaky-test risk and improve debugability. - Enhanced CI stability and security: pinned dylint revision to stabilize CI tooling; removed insecure test flag from kms tests to reduce noise without sacrificing validation. - Observability and performance: refined logging levels for better observability and introduced core computation optimizations (bivariate polynomials and matrix ops) with benches for measurable gains. - tfhe-rs: introduced SystemTime versioning with serialization support for better data compatibility; refactored decompression logic for simpler error handling; and optimized ServerKey destructuring to avoid unnecessary cloning, improving memory efficiency. - Cross-repo impact: CI tooling stability improvements contributing to more predictable CI runs and faster iteration cycles.

April 2026 performance snapshot: Core build-system modernization and CI stabilization for kms, coupled with test reliability and crypto workflow optimizations. The month focused on delivering business value through faster, more reliable builds, safer release pipelines, and more efficient crypto processing across kms and tfhe-rs.

March 2026 performance: Implemented modular, crate-based architecture in zama-ai/kms by extracting algebra and execution into dedicated crates (threshold-algebra and threshold-execution), introducing a thread-handles crate, and tightening dependencies; reduced maintenance and improved integration paths for threshold components. In addition, deduplicated dependencies and restructured crates to streamline build and collaboration. Removed StorageCache and related debug code to simplify storage management and reduce surface area. In tfhe-rs, introduced a safe-serialization crate moved to its own crate and wired into the workspace to improve reuse. Overall impact: cleaner separation of concerns, faster onboarding for new threshold components, improved build times, and more robust, reusable crates across the workspace. Technologies demonstrated: Rust crate-level modularization, workspace management, dependency deduplication, clippy/cleanup discipline, and cross-crate integration; demonstrated ability to drive architectural improvements with concrete commits.

February 2026 monthly summary for zama-ai/kms: Delivered improvements to custodian backup test reliability by introducing a purge utility and updating tests to purge data after each run. This eliminated residual data interference, enabling reliable re-runs and more deterministic CI outcomes. The work directly supports faster feedback and safer test-driven changes in the KMS feature set.