Claims now flow through StemeDB's append-only knowledge graph instead of
mutable TOML files. This resolves all 6 critical claim-bypass code paths:
- Bridge: lossless AuthoredClaim ↔ Assertion round-trip (comparison, status, lifecycle mapping)
- LocalEpisteme: ingest_authored_claim() and fetch_authored_claims() with AUTHORED_CLAIM predicate index
- EpistemeClaimStore: ClaimStore trait backed by StemeDB (append-only delete via deprecation)
- CLI handlers: all claim commands read/write through StemeDB
- Scanner: loads claims from StemeDB with auto-migration fallback to TOML
- Export: new `aphoria claims export` serializes StemeDB claims to TOML/JSON
Also cleans up dead code (EpistemeConfig.url), renames ingest_claims→ingest_observations,
fixes ClaimFilter.authority_tier type, adds Draft variant to ClaimStatus, and fixes
pre-existing clippy warnings (too_many_arguments, filter_next→rfind).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit implements comprehensive production hardening across multiple
layers to prepare StemeDB for enterprise pilot deployments:
## API Layer
- Add rate limiting middleware with configurable limits per endpoint
- Enhance error handling with detailed context and proper HTTP status codes
- Add security hardening tests for input validation and boundary conditions
- Create store_helpers module for defensive storage access patterns
## Storage & WAL
- Optimize group commit batching for higher throughput
- Add defensive error handling in hybrid backend with proper fallbacks
- Enhance WAL journal durability guarantees with fsync validation
- Improve index store query performance with better caching
## Operations & Deployment
- Add comprehensive operations documentation (deployment, monitoring, DR)
- Create systemd units for backup, WAL archival, and verification
- Add monitoring configs (Prometheus alerts, metrics exporters)
- Implement backup/restore scripts with verification and S3 archival
- Add DR drill automation and runbook procedures
- Create load balancer configs (nginx, envoy) with health checks
## Documentation
- Update CLAUDE.md with operations and troubleshooting guides
- Expand roadmap with production readiness milestones
- Add pilot success criteria and deployment reference architecture
- Document TLS setup, monitoring integration, and incident response
## Configuration
- Add .env.example with all required environment variables
- Document resource sizing for different deployment scales
- Add configuration examples for various deployment topologies
This positions StemeDB for successful enterprise pilots with proper
operational discipline, monitoring, backup/DR, and security hardening.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Enterprise Features:
- Hosted mode with remote sync for team pattern aggregation
- Community sharing with privacy-preserving anonymization
- LLM-based semantic claim extraction with Gemini integration
- Pattern learning with promotion to declarative extractors
- High-entropy secrets extractor with configurable thresholds
- Auth bypass and insecure cookies extractors
Module Refactoring:
- Split oversized files to comply with 500-line limit
- Config split: types/core.rs, types/extractors.rs, types/hosted.rs, etc.
- Handlers split: scan.rs, policy.rs, report.rs modules
- Extractors split: declarative/, high_entropy_secrets/, insecure_cookies/
- Learning split: store modules with metrics and persistence
SDK & Ontology:
- stemedb-ontology SDK with fluent builders and StemeDB client
- Pharma domain extractors for FDA Orange Book data
- Consumer health UAT test infrastructure
Code Quality:
- Fixed clippy warnings (needless_borrows_for_generic_args)
- Added KVStore trait imports where needed
- Fixed utoipa path re-exports for OpenAPI docs
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add CRC32C checksums to WAL record format (v2), implement crash recovery
with automatic truncation of corrupt records, add feature-gated group commit
buffer for batched fsync under concurrent load, and implement log rotation
via segment files with global offset addressing.
Key changes:
- Record format v2: [len:u32][crc32c:u32][blake3:32][payload:N]
- recover_file() scans and truncates corrupt tail records
- GroupCommitBuffer batches fsync via MPSC channel (tokio feature gate)
- SegmentManager with binary search resolution and cursor-based cleanup
- Journal::read() auto-refreshes segments on miss for writer/reader split
- Split recovery.rs and key_codec.rs into directory modules for 500-line max
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Phase 1 delivers the complete durability and storage layer:
- WAL with crash recovery: Append-only journal with BLAKE3 checksums,
fsync guarantees, and proper seek-to-EOF on reopen
- Storage engine: sled-backed KVStore with scan_prefix for range queries
- Content-addressed storage: H:{hash}, V:{hash}, E:{hash} key patterns
- Ingestor: Background worker tailing WAL, writing to KV with 8-byte
aligned record headers for rkyv zero-copy deserialization
- Comprehensive tests: 31 tests covering crash recovery, round-trips,
and multi-cycle durability
New crates: stemedb-wal, stemedb-storage, stemedb-ingest
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
