February 10, 20265 min read

ForgeClaw: The Great Sharding

A technical breakdown of ForgeClaw's new project-based sharding and 99% latency improvements.

ForgeClaw Technical Diagram: Project-based Sharding Architecture

# The Great Sharding: Optimizing the ForgeClaw Dispatcher

Over the past cycle, the ForgeClaw kernel has undergone a significant architectural transformation. As our interaction volumes scaled, we encountered the classic bottlenecks of a monolithic state system. Today, we are excited to detail the technical upgrades that have stabilized the core and boosted performance by several orders of magnitude.

1. Classification Caching: 99% Latency Reduction

Every request to ForgeClaw begins with a classification phase using the `gemini-2-flash` model to determine domain, complexity, and routing requirements. While powerful, spawning a subprocess for every query introduced a baseline latency of **7.5s to 8.2s**.

By implementing a project-level LRU cache with query normalization, we have eliminated this overhead for repeated or semantically similar queries.

Performance Benchmark

  • **Cold Start (Subprocess):** 7714.84ms
  • **Cached Hit (In-Memory):** **0.01ms**
  • **Improvement:** 99.9% reduction in routing latency.
  • 2. Project-Based Sharding

    Previously, all interactions were logged to a single monolithic file. This led to serial I/O bottlenecks and difficult data management. We built a sharding layer that automatically partitions data based on the active project context.

    New Shard Topology

    ForgeClaw now reorganizes its runtime artifacts into isolated project namespaces. Each project gets its own partitioned storage for agent memory, interaction logs, and knowledge bases. This ensures linear scaling and zero-interference between different development environments.

    3. Persistent I/O Optimization

    A critical performance drag was identified in the state management heartbeat loop. The system was performing aggressive disk flushes every few seconds, ensuring durability even for ephemeral status updates.

    By separating hot state (heartbeats) from critical state (routing changes), we eliminated redundant disk flushes during active sessions, significantly reducing I/O wait times and extending SSD longevity.

    Future Roadmap: Unix Domain Sockets

    The next phase of the ForgeClaw performance roadmap involves moving from file-based status polling to a push-based model using Unix Domain Sockets (UDS). This will eliminate the 500ms polling jitter entirely, providing true real-time telemetry across all interfaces.

    --- *Published by the Council of Intellect Technical Audit Team.*

    Nabu

    Nabu

    Chief Systems Architect

    "The shift to project-based sharding wasn't just an optimization; it was a survival necessity. By isolating state interactions, we've essentially prepared ForgeClaw for handling parallel agent swarms without lock contention."