> ## Documentation Index > Fetch the complete documentation index at: https://docs.lerian.studio/llms.txt > Use this file to discover all available pages before exploring further. # Architecture > Explore Matcher's modular monolith built on DDD, hexagonal architecture, and CQRS, with seven bounded contexts that evolve independently. Matcher is built as a **modular monolith** using Domain-Driven Design (DDD) and hexagonal architecture. CQRS separates commands (writes) from queries (reads). This keeps operations simple while maintaining clear boundaries. Each module can evolve independently without the complexity of microservices. ## Architecture overview *** Matcher Architecture ## Bounded contexts *** Matcher has seven modules. Each owns its data and exposes clean interfaces to the others. * **Configuration**: What you're reconciling (contexts, sources, field maps, rules) * **Discovery**: External data source connections, schema detection, and extraction orchestration with the embedded Fetcher engine * **Ingestion**: Getting data in (parsing, validation, normalization) * **Matching**: The engine (rule execution, confidence scoring) * **Exception**: Handling unmatched items (workflow, routing, resolution) * **Governance**: Audit trails (immutable logs for compliance) * **Reporting**: Visibility (reports, exports, dashboards) ### Configuration Defines **what** you're reconciling and **how**. **Handles:** * Contexts (what's being reconciled) * Sources (where data comes from) * Field maps (translating external fields) * Rules (how to match) **Key models:** * `ReconciliationContext`: The reconciliation scope * `ReconciliationSource`: Source configuration * `FieldMap`: Field translation rules * `MatchRule`: Matching logic ### Discovery The Discovery bounded context manages external data source connectivity, schema detection, and extraction orchestration with Fetcher's embedded engine. Matcher hosts that engine in-process; Fetcher is not a remote service. **Responsibilities:** * Manage external data source connections * Detect and cache source schemas * Run in-process extractions and hand results directly to Ingestion * Track connection and extraction lifecycles **Key entities:** * `FetcherConnection`: External source connection managed locally by the embedded engine * `ExtractionRequest`: Tracks an extraction lifecycle run by the embedded engine See [Discovery](/en/matcher/integrations/matcher-discovery) for how Discovery connects to external databases with the embedded Fetcher engine. ### Ingestion The Ingestion bounded context handles data intake and normalization. **Responsibilities:** * Parse uploaded files (CSV, JSON, XML) * Validate incoming data against configured schemas * Normalize external data into a canonical representation * Detect and handle duplicate records * Emit domain events when ingestion completes **Key entities:** * `IngestionJob`: Tracks ingestion lifecycle and status * `Transaction`: Normalized canonical transaction record **Events published:** * `ingestion.completed`: Indicates data readiness for matching ### Matching The Matching bounded context contains the reconciliation engine. **Responsibilities:** * Load applicable rules for a reconciliation context * Execute matching strategies (exact, tolerance, date-based) * Calculate confidence scores * Create match groups and allocate transactions * Identify unmatched transactions **Key entities:** * `MatchRun`: Execution of a matching job * `MatchGroup`: Group of reconciled transactions * `MatchItem`: Individual transaction allocation **Events published:** * `match_group.confirmed`: A match group has been finalized * `match_group.unmatched`: A previously confirmed match was reverted * `transaction.pending_review`: A non-automatic candidate needs review ### Exception management The Exception bounded context manages unresolved transactions. **Responsibilities:** * Classify exceptions by severity * Route exceptions to internal teams or external systems * Support manual overrides and adjustments * Track resolution status and SLAs * Integrate with external workflow tools **Key entities:** * `Exception`: An unresolved transaction * `Resolution`: Outcome of exception handling * `RoutingRule`: Routing and escalation logic **Integrations:** * JIRA for issue tracking * Webhooks for custom workflows ServiceNow is an accepted routing target, but its HTTP connector is not implemented. ### Governance The Governance bounded context preserves reconciliation traceability. **Responsibilities:** * Record instrumented auditable mutation workflows in immutable audit logs * Provide queryable audit history * Support regulatory and compliance reporting **Key entities:** * `AuditLog`: Append-only record of instrumented auditable mutation workflows Audit logs are append-only by design. Entries cannot be modified or removed to preserve compliance integrity. ### Reporting The Reporting bounded context provides operational visibility. **Responsibilities:** * Generate reconciliation reports * Expose dashboard metrics * Export reconciliation data in multiple formats **Key entities:** * `Report`: Reconciliation summary * `Dashboard`: Aggregated operational metrics * `ExportJob`: Asynchronous export execution ## Data flow *** Reconciliation follows a deterministic pipeline across bounded contexts: Reconciliation contexts, sources, field mappings, and rules are defined through the API. Discovery connects to external sources, detects their schemas, and runs extractions in-process with the embedded Fetcher engine. Extracted results are handed directly to Ingestion. Uploaded files and data extracted by Discovery are parsed, validated, normalized, and deduplicated. An `ingestion.completed` event is emitted. Matching rules are applied to eligible transactions, producing match groups with confidence scores on an integer scale of 0 to 100. EXACT and TOLERANCE groups with a confidence of at least 90 out of 100 can auto-confirm; FUZZY and DATE\_LAG groups always require manual review. Unmatched items become exceptions. Exceptions are classified, routed, and resolved either manually or via external systems. Resolution updates are propagated back to Matcher. Instrumented auditable mutation workflows across the pipeline are recorded in immutable audit logs. Users access reports and dashboards showing reconciliation status, match rates, and exception aging. ## Infrastructure components *** Matcher relies on the following infrastructure services: | Component | Purpose | Usage | | ----------------------------- | -------------------------- | ------------------------------------------------------------------------------- | | **PostgreSQL** | Primary data store | Domain data; configured multi-tenant deployments resolve a pool for each tenant | | **Valkey (Redis-compatible)** | Cache and coordination | Deduplication, locks, idempotency keys | | **Streaming backbone** | Business-event publication | Domain events published via lib-streaming | | **RabbitMQ** | Infrastructure queues | Internal work queues and dead-letter handling | | **Systemplane** | Runtime configuration | Hot-reload settings without restart via `/system/matcher/:key` admin API | ### Database architecture * **Tenant-specific pool resolution** in configured multi-tenant deployments for data separation * **Strong consistency** for matching and exception state * **Eventual consistency** for reporting views ### Multi-tenancy Matcher enforces strict tenant isolation: * With `AUTH_PROVIDER=plugin-auth`, tenant identity is extracted from `tenant_id` or `tenantId` JWT claims * `workos`, single-tenant, and authentication-disabled deployments use the configured default tenant * Tenant identifiers are never accepted via request parameters * Database access is scoped through the active tenant's connection pool * All queries are automatically constrained to the active tenant This model prevents cross-tenant data access and supports regulatory and audit requirements. ## Design patterns *** ### Hexagonal architecture Each bounded context follows the ports-and-adapters pattern: ``` context/ ├── adapters/ │ ├── http/ │ ├── postgres/ │ └── redis/ ├── ports/ ├── services/ │ ├── command/ │ ├── query/ │ └── worker/ └── domain/ ├── entities/ └── errors/ ``` ### Cqrs-light Write and read paths are separated at the service level: * `*_commands.go` for state mutations * `*_queries.go` for read operations This improves code organization and allows independent optimization of query paths. ### Outbox pattern Matcher uses per-event delivery policies. Outbox-backed events persist an outbox record and are dispatched asynchronously; other events can use direct delivery with an outbox fallback when the circuit is open. ## Next steps *** Explore the architecture through a guided example. Review authentication, authorization, and tenant isolation mechanisms.