diff --git a/docs/PRODUCTION_READINESS_ROADMAP.md b/docs/PRODUCTION_READINESS_ROADMAP.md new file mode 100644 index 0000000..da1eafa --- /dev/null +++ b/docs/PRODUCTION_READINESS_ROADMAP.md @@ -0,0 +1,526 @@ +# RingKernel Production Readiness Roadmap + +> A comprehensive analysis and strategic plan for taking RingKernel from a feature-complete +> framework (v0.4.2) to a battle-tested, production-grade GPU actor system. + +**Date**: February 2026 +**Current version**: 0.4.2 +**Target**: v1.0.0 stable release + +--- + +## Table of Contents + +1. [Executive Summary](#executive-summary) +2. [Current State Assessment](#current-state-assessment) +3. [Gap Analysis](#gap-analysis) +4. [Roadmap Phases](#roadmap-phases) + - [Phase A: Safety & Correctness](#phase-a-safety--correctness-q1-q2-2026) + - [Phase B: Operational Maturity](#phase-b-operational-maturity-q2-q3-2026) + - [Phase C: Performance Hardening](#phase-c-performance-hardening-q3-2026) + - [Phase D: Ecosystem & API Stability](#phase-d-ecosystem--api-stability-q3-q4-2026) + - [Phase E: Enterprise Deployment](#phase-e-enterprise-deployment-q4-2026-q1-2027) +5. [Detailed Work Items](#detailed-work-items) +6. [Risk Register](#risk-register) +7. [Success Criteria for v1.0](#success-criteria-for-v10) +8. [Research References](#research-references) + +--- + +## Executive Summary + +RingKernel has achieved 100% feature completion across its original 5-phase roadmap, delivering +a GPU-native persistent actor model with ~195K lines of Rust across 22 crates, 950+ tests, +5 fuzz targets, and multi-backend support (CUDA, WebGPU, Metal, CPU). The framework is +**feature-rich but pre-production**. + +This roadmap addresses the gap between "feature-complete" and "production-ready" by focusing on: + +1. **Safety verification** of ~290 `unsafe` blocks across 46 files via Miri/Kani integration +2. **Operational observability** using OpenTelemetry, structured metrics, and health endpoints +3. **API stability** through semver enforcement and a deliberate path to 1.0 +4. **Deployment infrastructure** with containerization, GPU passthrough, and orchestration +5. **Performance baselines** with regression detection and continuous benchmarking + +The estimated timeline is 9-12 months to reach a production-stable v1.0.0 release. + +--- + +## Current State Assessment + +### Codebase Metrics + +| Metric | Value | Assessment | +|--------|-------|------------| +| Total Rust LOC | ~195,000 | Large, well-structured workspace | +| Workspace crates | 22 (+ tutorials, fuzz) | Good modularity | +| Test count | 950+ (`#[test]` annotations) | Moderate coverage | +| Fuzz targets | 5 (IR, CUDA/WGSL transpilers, message queue, HLC) | Good foundation | +| `unsafe` blocks | ~290 across 46 files | Requires systematic audit | +| Doc comments | ~400+ across codebase | Moderate; gaps in newer crates | +| CI workflows | 4 (ci, gpu-tests, release, docs) | Good structure | +| Benchmark suites | Criterion benches + application benchmarks | Needs regression tracking | +| Version | 0.4.2 | Pre-1.0, no semver stability guarantee | + +### Architecture Strengths + +- **Clean workspace structure**: Well-separated concerns across core, backends, codegen, ecosystem +- **Feature flag discipline**: Backend selection via Cargo features with auto-detection fallback +- **Zero-copy serialization**: rkyv 0.7 with validation enabled (`bytecheck`, `strict` mode) +- **Multi-backend codegen**: Unified IR (`ringkernel-ir`) lowers to CUDA PTX, WGSL, and MSL +- **Enterprise features**: Checkpoint/restore, multi-GPU, security (AES-256-GCM, audit logging) +- **CI/CD pipeline**: GitHub Actions with fmt, clippy, test, doc, MSRV (1.75), GPU-specific workflows +- **Fuzz testing**: 5 targets covering critical paths (transpilers, message queue, HLC, IR) +- **Release automation**: Multi-platform release workflow (Linux/Windows, CPU/CUDA) + +### Identified Gaps + +| Area | Current State | Gap | +|------|--------------|-----| +| **Unsafe audit** | ~290 unsafe blocks, no systematic review | No Miri/Kani CI integration | +| **Observability** | `tracing` crate used, basic spans | No OpenTelemetry export, no metrics pipeline | +| **Containerization** | No Docker/k8s configs | Missing production deployment path | +| **API stability** | v0.4.2, no semver checking | No `cargo-semver-checks` in CI | +| **Error recovery** | `thiserror` 2.0 typed errors | No circuit breaker, backpressure signals | +| **Load testing** | Application benchmarks exist | No sustained load / soak tests | +| **Dependency audit** | No `cargo-audit` in CI | Unmonitored supply chain | +| **Documentation** | 19 architecture docs, tutorials | Missing operations guide, runbooks | +| **Graceful shutdown** | `DegradationManager` exists | No signal handling / drain protocol | +| **Memory pressure** | `GpuMemoryDashboard` exists | No automatic OOM recovery | + +--- + +## Gap Analysis + +### 1. Safety & Soundness + +**The ~290 `unsafe` blocks are the highest-priority production risk.** They span: + +- **CUDA driver calls** (`ringkernel-cuda`): kernel launch, memory allocation, stream management (~99 occurrences) +- **GPU memory mapping** (`ringkernel-metal`, `ringkernel-wgpu`): buffer access, pointer casts +- **Zero-copy deserialization** (`ringkernel-core`): rkyv archive access +- **Lock-free queue operations** (`ringkernel-core`): atomic operations, memory ordering +- **FFI boundaries** (`ringkernel-cuda`, `ringkernel-metal`): cudarc, metal-rs interop +- **Proc macro code generation** (`ringkernel-derive`): generated unsafe code paths + +**Industry context**: A 2024 mixed-methods study on unsafe Rust found that developers "rarely +audited their dependencies and relied on ad-hoc reasoning" for unsafe code correctness. +AWS has launched a formal initiative to verify the safety of the Rust standard library +using Kani, signaling that model-checking unsafe code is becoming industry standard practice. + +### 2. Observability & Operations + +The framework uses `tracing` for structured logging but lacks: + +- **OpenTelemetry integration**: No OTLP exporter for traces, metrics, or logs +- **Four Golden Signals**: Latency, traffic, errors, saturation not exposed as metrics +- **Health check endpoints**: Enterprise `HealthChecker` exists but no standard HTTP endpoints +- **Structured alerting**: `alerting` feature flag exists but no Prometheus/Grafana integration +- **Distributed tracing context propagation**: Message headers support trace context but no + end-to-end demo with Jaeger/Tempo + +**Industry context**: The 2025 production readiness consensus recommends OpenTelemetry as the +standard instrumentation layer, with `tracing-opentelemetry` bridging Rust's tracing ecosystem +to vendor-agnostic backends. + +### 3. Deployment & Containerization + +No Docker images, Helm charts, or Kubernetes manifests exist. The release workflow builds +binaries but doesn't package them for container orchestration. + +**Industry context**: The NVIDIA Container Toolkit is the standard for GPU workloads in +containers. wgpu requires Vulkan ICD loaders inside containers. CubeCL (Burn's compute +backend) has demonstrated CUDA + wgpu from a single Rust binary in containers. + +### 4. API Stability & Semver + +At v0.4.2, the project is pre-1.0 with no formal semver enforcement. The `cargo-semver-checks` +tool should be integrated into CI before any 1.0 declaration. + +**Industry context**: The Rust ecosystem strongly recommends not staying at 0.x indefinitely, +as it reduces semver expressivity from three categories to two. The Cargo SemVer Compatibility +Guide and RFC 1105 provide detailed definitions of breaking vs. non-breaking changes. + +### 5. Lock-Free Queue Reliability + +The lock-free message queue is a critical path for all actor communication. While it has +fuzz testing, it needs: + +- **Linearizability proof or testing**: Loom-based concurrency testing +- **Boundary condition handling**: Recent GPU queue research (BACQ, 2025) shows that + boundary-aware designs significantly improve reliability under high contention +- **Backpressure signaling**: No mechanism to signal queue saturation to producers + +--- + +## Roadmap Phases + +### Phase A: Safety & Correctness (Q1-Q2 2026) + +**Goal**: Achieve verifiable safety for all `unsafe` code and critical data structures. + +| # | Work Item | Priority | Effort | Description | +|---|-----------|----------|--------|-------------| +| A1 | **Unsafe code audit** | P0 | Large | Systematic review of all ~290 unsafe blocks; document safety invariants | +| A2 | **Miri CI integration** | P0 | Medium | Add Miri test runs for core crate, message queue, HLC | +| A3 | **Kani verification harnesses** | P1 | Large | Model-check lock-free queue, memory mapping, archive access | +| A4 | **Loom concurrency testing** | P0 | Medium | Test lock-free queue and HLC under all possible thread interleavings | +| A5 | **`cargo-audit` in CI** | P0 | Small | Add dependency vulnerability scanning to CI pipeline | +| A6 | **rkyv migration plan** | P1 | Medium | Evaluate rkyv 0.8 (pre-1.0) or pin 0.7 with safety wrappers | +| A7 | **SAFETY.md documentation** | P1 | Small | Document all unsafe invariants, audit status, and verification coverage | +| A8 | **Clippy strictness** | P1 | Small | Enable `clippy::pedantic` and `clippy::nursery` lint groups | + +**Key risks**: rkyv 0.7 has known alignment issues (RUSTSEC-2021-0054); `AlignedVec` must be +used consistently. The lock-free queue needs formal testing beyond fuzz (Loom provides +exhaustive scheduling exploration). + +### Phase B: Operational Maturity (Q2-Q3 2026) + +**Goal**: Make RingKernel observable, operable, and recoverable in production. + +| # | Work Item | Priority | Effort | Description | +|---|-----------|----------|--------|-------------| +| B1 | **OpenTelemetry integration** | P0 | Large | Add `tracing-opentelemetry` bridge; OTLP exporter for traces + metrics | +| B2 | **Prometheus metrics endpoint** | P0 | Medium | Expose four golden signals + GPU-specific metrics (memory, utilization, queue depth) | +| B3 | **Health check HTTP endpoints** | P0 | Small | `/healthz`, `/readyz`, `/livez` per Kubernetes conventions | +| B4 | **Graceful shutdown protocol** | P0 | Medium | Signal handling (SIGTERM/SIGINT), kernel drain, checkpoint-on-shutdown | +| B5 | **Circuit breaker pattern** | P1 | Medium | Automatic fallback when GPU backends fail; CPU degradation path | +| B6 | **Backpressure signaling** | P1 | Medium | Queue saturation detection with producer flow control | +| B7 | **Structured error taxonomy** | P1 | Medium | Classify errors: retriable vs. fatal, user-facing vs. internal | +| B8 | **Operations runbook** | P1 | Medium | Document common failure modes, debugging procedures, recovery steps | +| B9 | **Log correlation** | P2 | Small | Ensure trace IDs propagate through K2K messages and across GPU boundaries | +| B10 | **GPU OOM recovery** | P1 | Medium | Automatic memory pressure relief: eviction, checkpoint-to-disk, degradation | + +**Key insight**: The existing `GpuMemoryDashboard` and `DegradationManager` provide a +foundation; this phase wires them into standard observability pipelines and adds missing +recovery paths. + +### Phase C: Performance Hardening (Q3 2026) + +**Goal**: Establish performance baselines, detect regressions, and optimize critical paths. + +| # | Work Item | Priority | Effort | Description | +|---|-----------|----------|--------|-------------| +| C1 | **Continuous benchmarking** | P0 | Medium | Integrate Criterion results into CI with regression detection (e.g., `bencher.dev` or `codspeed`) | +| C2 | **Soak testing framework** | P0 | Medium | 24-hour sustained load tests for message throughput, memory stability | +| C3 | **Lock-free queue optimization** | P1 | Large | Evaluate BACQ-style warp-level optimizations for GPU-side queues | +| C4 | **Memory pool tuning** | P1 | Medium | Profile and optimize CUDA memory pool allocation patterns | +| C5 | **Latency percentile tracking** | P1 | Small | p50/p95/p99/p999 latency histograms for message send/receive | +| C6 | **GPU kernel occupancy profiling** | P1 | Medium | Automated occupancy analysis integrated with `GpuProfilerManager` | +| C7 | **Zero-copy path audit** | P2 | Medium | Verify zero-copy is maintained end-to-end; identify hidden copies | +| C8 | **Compile time optimization** | P2 | Medium | Profile and reduce workspace build times; evaluate `cargo-nextest` | + +**Research context**: The 2025 BACQ paper (Polak et al., Applied Sciences) demonstrates that +boundary-aware concurrent queue designs on GPUs achieve superior throughput through warp-level +coordination and virtual caching layers, directly applicable to RingKernel's GPU-side queues. + +### Phase D: Ecosystem & API Stability (Q3-Q4 2026) + +**Goal**: Stabilize public APIs and prepare the crate ecosystem for 1.0. + +| # | Work Item | Priority | Effort | Description | +|---|-----------|----------|--------|-------------| +| D1 | **`cargo-semver-checks` in CI** | P0 | Small | Automated semver compliance on every PR | +| D2 | **API review: `ringkernel-core`** | P0 | Large | Audit all public types, traits, and functions for 1.0 stability | +| D3 | **API review: `ringkernel-derive`** | P0 | Medium | Stabilize proc macro attributes and generated code shape | +| D4 | **API review: backend traits** | P0 | Medium | Finalize `RingKernelRuntime`, `PersistentHandle`, `ControlBlock` | +| D5 | **Migration guide (0.x → 1.0)** | P1 | Medium | Document all breaking changes and migration paths | +| D6 | **Deprecation protocol** | P1 | Small | Mark items for removal with `#[deprecated]` before 1.0 | +| D7 | **Feature flag audit** | P1 | Small | Ensure no feature flag combination produces unsound code | +| D8 | **`#[doc(hidden)]` audit** | P2 | Small | Verify internal-only items are not accidentally public | +| D9 | **MSRV policy** | P1 | Small | Decide on MSRV policy for 1.x (currently 1.75) | +| D10 | **Dependency minimum versions** | P2 | Medium | Test with `-Z minimal-versions` to verify lower bounds | + +**Key principle**: Per the Cargo SemVer Compatibility Guide and Effective Rust (Item 21), +reaching 1.0 is a commitment that the public API is stable. The pre-1.0 period is the +time to make breaking changes freely. + +### Phase E: Enterprise Deployment (Q4 2026 - Q1 2027) + +**Goal**: Provide production deployment artifacts and operational infrastructure. + +| # | Work Item | Priority | Effort | Description | +|---|-----------|----------|--------|-------------| +| E1 | **Docker images** | P0 | Medium | Multi-stage Dockerfiles: CUDA base + Rust builder + slim runtime | +| E2 | **NVIDIA Container Toolkit integration** | P0 | Small | Document and test GPU passthrough with `--gpus` flag | +| E3 | **Helm chart** | P1 | Medium | Kubernetes deployment with GPU node selector, resource limits | +| E4 | **Docker Compose profiles** | P1 | Small | Development (CPU), staging (GPU), production profiles | +| E5 | **GPU device scheduling** | P1 | Medium | Kubernetes `nvidia.com/gpu` resource requests; multi-GPU pod affinity | +| E6 | **Configuration management** | P1 | Medium | Environment-based config with validation; 12-factor compliance | +| E7 | **Secret management** | P1 | Small | Integration with Kubernetes secrets, Vault, or AWS Secrets Manager | +| E8 | **Horizontal scaling guide** | P2 | Medium | Document multi-node deployment with gRPC K2K bridge | +| E9 | **Disaster recovery playbook** | P2 | Medium | Checkpoint-based DR with RTO/RPO targets | +| E10 | **Compliance validation** | P2 | Large | End-to-end validation of SOC2/GDPR/HIPAA compliance features | + +**Industry context**: PhoenixOS (SOSP '25) demonstrates OS-level concurrent GPU +checkpoint/restore for fault tolerance and process migration. NVIDIA's GTC 2025 session +on HPC GPU fault tolerance provides cluster-level strategies. These inform the checkpoint +and migration features already in RingKernel. + +--- + +## Detailed Work Items + +### A1: Unsafe Code Audit — Detailed Plan + +The ~290 `unsafe` blocks fall into these categories: + +| Category | Count (approx.) | Risk Level | Verification Strategy | +|----------|-----------------|------------|----------------------| +| CUDA driver FFI (`cudarc` calls) | ~100 | Medium | Wrapper review + integration tests | +| GPU memory mapping / pointer casts | ~40 | High | Miri (where possible) + Kani harnesses | +| Lock-free atomics / memory ordering | ~30 | Critical | Loom exhaustive testing | +| rkyv zero-copy archive access | ~20 | High | Validation-gated access patterns | +| Proc macro generated code | ~15 | Medium | Generated code review + expanded test matrix | +| SIMD intrinsics (CPU backend) | ~15 | Low | Miri + standard test coverage | +| Transmutes / pointer arithmetic | ~20 | High | Case-by-case Kani proofs | +| Other (FFI, alignment) | ~50 | Medium | Documentation + defensive wrappers | + +**Deliverable**: Each `unsafe` block annotated with a `// SAFETY:` comment explaining +the invariants relied upon, per Rust API Guidelines. + +### B1: OpenTelemetry Integration — Architecture + +``` +┌─────────────────────────────────────────────────────────┐ +│ RingKernel Application │ +│ │ +│ ┌──────────┐ ┌──────────┐ ┌──────────────────────┐ │ +│ │ tracing │ │ metrics │ │ GPU Profiler Manager │ │ +│ │ spans │ │ counters │ │ (NVTX, events) │ │ +│ └────┬─────┘ └────┬─────┘ └──────────┬───────────┘ │ +│ │ │ │ │ +│ ▼ ▼ ▼ │ +│ ┌─────────────────────────────────────────────────┐ │ +│ │ tracing-opentelemetry bridge │ │ +│ │ + opentelemetry-otlp exporter │ │ +│ └────────────────────┬────────────────────────────┘ │ +└───────────────────────┼─────────────────────────────────┘ + │ OTLP/gRPC + ▼ + ┌─────────────────┐ + │ OTel Collector │ + └────┬───────┬────┘ + │ │ + ┌────────┘ └────────┐ + ▼ ▼ + ┌──────────────┐ ┌──────────────┐ + │ Prometheus │ │ Grafana Tempo │ + │ (metrics) │ │ (traces) │ + └──────────────┘ └──────────────┘ +``` + +**Proposed metrics**: + +| Metric | Type | Description | +|--------|------|-------------| +| `ringkernel_message_send_duration_seconds` | Histogram | H2K message send latency | +| `ringkernel_message_recv_duration_seconds` | Histogram | K2H message receive latency | +| `ringkernel_queue_depth` | Gauge | Current queue occupancy per kernel | +| `ringkernel_queue_capacity_ratio` | Gauge | Queue fill ratio (saturation signal) | +| `ringkernel_kernel_active_count` | Gauge | Number of active GPU kernels | +| `ringkernel_gpu_memory_allocated_bytes` | Gauge | GPU memory in use | +| `ringkernel_gpu_memory_pool_hit_ratio` | Gauge | Memory pool cache hit rate | +| `ringkernel_checkpoint_duration_seconds` | Histogram | Checkpoint operation latency | +| `ringkernel_k2k_messages_total` | Counter | Inter-kernel messages by route | +| `ringkernel_errors_total` | Counter | Errors by category and severity | + +### E1: Docker Images — Multi-Stage Build + +```dockerfile +# === Builder stage === +FROM nvidia/cuda:12.5.0-devel-ubuntu22.04 AS builder +RUN apt-get update && apt-get install -y curl build-essential pkg-config libssl-dev +RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y +WORKDIR /build +COPY . . +RUN cargo build --release --features cuda + +# === Runtime stage === +FROM nvidia/cuda:12.5.0-runtime-ubuntu22.04 +RUN apt-get update && apt-get install -y ca-certificates && rm -rf /var/lib/apt/lists/* +COPY --from=builder /build/target/release/ringkernel-app /usr/local/bin/ +EXPOSE 8080 4317 +HEALTHCHECK --interval=30s --timeout=3s CMD curl -f http://localhost:8080/healthz || exit 1 +ENTRYPOINT ["ringkernel-app"] +``` + +--- + +## Risk Register + +| # | Risk | Likelihood | Impact | Mitigation | +|---|------|-----------|--------|------------| +| R1 | rkyv 0.7 has known soundness issues | Medium | High | Pin version, use `AlignedVec` everywhere, evaluate 0.8 migration | +| R2 | Lock-free queue has undiscovered race conditions | Low | Critical | Loom testing, linearizability verification | +| R3 | `cudarc` 0.18 API changes break builds | Medium | Medium | Pin version, wrap in abstraction layer | +| R4 | GPU driver bugs cause silent data corruption | Low | High | Checksums on critical data paths, ABFT techniques | +| R5 | wgpu in containers fails to find GPU adapter | Medium | Medium | Document Vulkan ICD requirements, provide fallback to CPU | +| R6 | 1.0 API proves too restrictive | Medium | Medium | Generous use of `#[non_exhaustive]`, extension traits | +| R7 | MSRV 1.75 becomes limiting | Low | Low | Evaluate bumping to 1.80+ for 1.0 | +| R8 | Performance regression goes undetected | Medium | Medium | Continuous benchmarking in CI with alerting | +| R9 | Enterprise features (encryption, audit) not validated by auditor | Medium | High | Engage third-party security audit pre-1.0 | +| R10 | Metal backend incomplete at 1.0 | High | Medium | Mark as experimental in 1.0; stable in 1.1 | + +--- + +## Success Criteria for v1.0 + +### Hard Requirements (Must-Have) + +- [ ] All `unsafe` blocks have `// SAFETY:` comments and are covered by Miri or Kani +- [ ] Loom tests pass for lock-free queue under all interleavings +- [ ] `cargo-audit` reports zero known vulnerabilities +- [ ] `cargo-semver-checks` integrated in CI; public API frozen +- [ ] OpenTelemetry traces and metrics exportable to standard backends +- [ ] Health check endpoints (`/healthz`, `/readyz`) available +- [ ] Graceful shutdown with kernel drain and optional checkpoint +- [ ] Docker images published for CPU and CUDA variants +- [ ] Operations runbook covering top 10 failure modes +- [ ] 24-hour soak test passes without memory leaks or panics +- [ ] All clippy warnings resolved (including `pedantic` group) +- [ ] Documentation coverage >95% for public API items + +### Soft Requirements (Should-Have) + +- [ ] Helm chart for Kubernetes deployment with GPU scheduling +- [ ] Continuous benchmarking with regression alerting +- [ ] Third-party security audit completed +- [ ] Migration guide from 0.4.x to 1.0 +- [ ] Metal backend at feature parity with CUDA (or marked experimental) +- [ ] Python bindings (`ringkernel-python`) stable and published to PyPI +- [ ] p99 latency < 1μs for H2K message send (CUDA backend) +- [ ] Example production deployment architecture document + +### Aspirational (Nice-to-Have for 1.0, otherwise 1.1) + +- [ ] WebAssembly/WebGPU deployment path documented +- [ ] GPU-native distributed consensus (Raft on GPU) +- [ ] Automatic GPU kernel hot-patching in production +- [ ] PhoenixOS-style concurrent checkpoint/restore integration +- [ ] CubeCL interoperability for kernel portability + +--- + +## Milestone Timeline + +``` +2026 Q1 Q2 Q3 Q4 2027 Q1 + │ │ │ │ │ + ├─ Phase A ─────┤ │ │ │ + │ Safety & ├─ Phase B ─────┤ │ │ + │ Correctness │ Operational ├─ Phase C ─────┤ │ + │ │ Maturity │ Performance │ │ + │ │ ├─ Phase D ─────┤ │ + │ │ │ API Stability │ │ + │ │ │ ├─ Phase E ─────┤ + │ │ │ │ Enterprise │ + │ │ │ │ Deployment │ + │ │ │ │ │ + ▼ ▼ ▼ ▼ ▼ +v0.5.0 v0.6.0 v0.8.0 v0.9.0-rc v1.0.0 +(safety) (observability) (performance) (API freeze) (stable) +``` + +### v0.5.0 — Safety Milestone (Q1 2026) +- Unsafe audit complete with SAFETY.md +- Miri and Loom integrated in CI +- `cargo-audit` + `cargo-deny` in CI +- Clippy pedantic clean + +### v0.6.0 — Observability Milestone (Q2 2026) +- OpenTelemetry integration +- Prometheus metrics endpoint +- Health check endpoints +- Graceful shutdown protocol + +### v0.8.0 — Performance Milestone (Q3 2026) +- Continuous benchmarking in CI +- Soak test framework +- Latency percentile tracking +- Memory pool optimization + +### v0.9.0-rc — API Freeze (Q4 2026) +- `cargo-semver-checks` enforced +- Public API reviewed and documented +- Migration guide from 0.4.x +- Feature flag audit complete + +### v1.0.0 — Stable Release (Q1 2027) +- Docker images published +- Helm chart available +- Operations runbook complete +- All hard requirements met + +--- + +## Research References + +This roadmap was informed by the following research and industry resources: + +### GPU Fault Tolerance & Checkpoint/Restore +- [PhoenixOS: Concurrent OS-level GPU Checkpoint and Restore](https://arxiv.org/html/2405.12079) — SOSP '25 +- [FT K-Means: High-Performance K-Means on GPU with Fault Tolerance](https://arxiv.org/html/2408.01391v1) — Algorithm-based fault tolerance +- [Build a Customizable HPC Platform With Enhanced GPU Fault Tolerance](https://www.nvidia.com/en-us/on-demand/session/gtc25-s72096/) — NVIDIA GTC 2025 +- [Characterizing GPU Resilience and Impact on AI/HPC Systems](https://arxiv.org/html/2503.11901v1) — 2025 + +### Lock-Free GPU Queues +- [Boundary-Aware Concurrent Queue (BACQ)](https://www.mdpi.com/2076-3417/15/4/1834) — Applied Sciences, 2025 +- [Toward Concurrent Lock-Free Queues on GPUs](https://www.researchgate.net/publication/275603769_Toward_Concurrent_Lock-Free_Queues_on_GPUs) +- [IPC: Shared Memory vs. Message Queues Performance Benchmarking](https://howtech.substack.com/p/ipc-mechanisms-shared-memory-vs-message) — 2025 + +### Rust Safety Verification +- [Rust Auditing Tools in 2025](https://markaicode.com/rust-auditing-tools-2025-automated-security-scanning/) — Miri, Kani, Rudra +- [Making Unsafe Rust a Little Safer](https://blog.colinbreck.com/making-unsafe-rust-a-little-safer-tools-for-verifying-unsafe-code/) +- [Surveying the Rust Verification Landscape](https://arxiv.org/html/2410.01981v1) — Comprehensive tool survey +- [Kani Rust Verifier: Safety-Critical Tool Submission](https://github.com/rustfoundation/safety-critical-rust-consortium/issues/380) +- [Verify the Safety of the Rust Standard Library](https://aws.amazon.com/blogs/opensource/verify-the-safety-of-the-rust-standard-library/) — AWS/Kani initiative +- [Sherlock Rust Security & Auditing Guide 2026](https://sherlock.xyz/post/rust-security-auditing-guide-2026) + +### Rust Production Observability +- [Rust Real-World Observability](https://medium.com/@wedevare/rust-real-world-observability-health-checks-metrics-tracing-and-logs-fd229ea8ec96) — Health checks, metrics, tracing +- [Monitor Data Pipelines in Rust Using OpenTelemetry](https://www.shuttle.dev/blog/2025/09/23/monitor-data-pipelines-in-rust) +- [How to Monitor Rust Applications with OpenTelemetry](https://www.datadoghq.com/blog/monitor-rust-otel/) — Datadog +- [Implementing OpenTelemetry in Rust](https://signoz.io/blog/opentelemetry-rust/) — SigNoz +- [Production Readiness Checklist: 7 Key Steps for 2025](https://goreplay.org/blog/production-readiness-checklist-20250808133113/) + +### Rust Actor Frameworks in Production +- [Ractor: Rust Actor Framework](https://github.com/slawlor/ractor) — Erlang/OTP-inspired, used at Meta +- [Comparing Rust Actor Libraries](https://tqwewe.com/blog/comparing-rust-actor-libraries/) — Actix, Coerce, Kameo, Ractor, Xtra +- [Quickwit Actor Framework](https://quickwit.io/blog/quickwit-actor-framework) — Custom framework with backpressure +- [Rust in Distributed Systems, 2025 Edition](https://disant.medium.com/rust-in-distributed-systems-2025-edition-175d95f825d6) + +### API Stability & Semver +- [Cargo SemVer Compatibility Guide](https://doc.rust-lang.org/cargo/reference/semver.html) — Official reference +- [RFC 1105: API Evolution](https://rust-lang.github.io/rfcs/1105-api-evolution.html) — Foundational RFC +- [Effective Rust — Item 21: Semantic Versioning](https://effective-rust.com/semver.html) +- [cargo-semver-checks](https://crates.io/crates/cargo-semver-checks) — Automated compliance tool + +### GPU Containerization & Deployment +- [NVIDIA Container Toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) +- [Docker GPU Support](https://docs.docker.com/desktop/gpu/) +- [Rust GPU: Running on Every GPU](https://rust-gpu.github.io/blog/2025/07/25/rust-on-every-gpu/) — Cross-platform GPU compute +- [CubeCL: Multi-Platform GPU Compute](https://github.com/tracel-ai/cubecl) — CUDA + wgpu from single codebase + +### Zero-Copy Serialization Safety +- [rkyv Validation Documentation](https://rkyv.org/validation.html) +- [RUSTSEC-2021-0054: rkyv Archives May Contain Uninitialized Memory](https://rustsec.org/advisories/RUSTSEC-2021-0054.html) +- [rkyv FAQ: Alignment and Safety](https://rkyv.org/faq.html) + +--- + +## Appendix: Priority Definitions + +| Priority | Definition | Timeline | +|----------|-----------|----------| +| **P0** | Blocks production deployment; must resolve | Current phase | +| **P1** | High value; important for production confidence | Next phase | +| **P2** | Improves quality; can defer to post-1.0 | Backlog | + +## Appendix: Effort Estimates + +| Estimate | Duration | Description | +|----------|----------|-------------| +| **Small** | < 1 week | Configuration, docs, small tool integration | +| **Medium** | 1-4 weeks | Feature implementation, significant testing | +| **Large** | 1-3 months | Major subsystem work, cross-cutting concerns |