---
title: Services Layer
description: Comprehensive guide to TraceRTM's 70+ services that power business logic, analysis, and integrations
---

# Services Layer

The services layer is the heart of TraceRTM's business logic, providing a comprehensive suite of over 70 specialized services that handle everything from core item management to advanced graph analysis, agent coordination, and external integrations.

## Architecture Overview

### Design Principles

The services layer follows these key architectural principles:

1. **Separation of Concerns**: Each service has a single, well-defined responsibility
2. **Dependency Injection**: Services receive database sessions and other dependencies via constructor injection
3. **Repository Pattern**: Services use repositories to interact with the database, never directly accessing models
4. **Event Sourcing**: Critical operations are logged through the EventRepository for audit trails
5. **Optimistic Locking**: Update operations use version checking to prevent conflicts
6. **Async-First**: Most services support async/await for high-performance I/O operations

### Service Categories

Services are organized into several functional categories:

- **Core Services**: Essential item, link, and project operations
- **Analysis Services**: Graph analysis, impact analysis, cycle detection
- **Performance Services**: Caching, optimization, query tuning
- **Integration Services**: Webhooks, external system integrations
- **Agent Services**: Multi-agent coordination and monitoring
- **Specialized Services**: Chaos mode, compliance, testing utilities
- **Import/Export Services**: Data migration and format conversion
- **Workflow Services**: Status transitions, automation

## Core Services

### ItemService

The primary service for item lifecycle management.

**Location**: `/src/tracertm/services/item_service.py`

**Key Features**:
- CRUD operations with optimistic locking
- Hierarchical item management (parent/child relationships)
- Status workflow validation
- Bulk operations with preview
- Progress calculation based on child items
- Metadata management with merge/replace strategies

**Example Usage**:

```python
from tracertm.services import ItemService
from sqlalchemy.ext.asyncio import AsyncSession

async def create_requirement(session: AsyncSession):
    item_service = ItemService(session)

    # Create item with optional links
    item = await item_service.create_item(
        project_id="proj_123",
        title="User Authentication",
        view="requirements",
        item_type="functional",
        agent_id="agent_001",
        description="Implement OAuth2 authentication",
        status="todo",
        priority="high",
        link_to=["item_456"],  # Link to related items
        link_type="relates_to"
    )

    # Update with retry on conflict
    updated = await item_service.update_item(
        item_id=item.id,
        agent_id="agent_001",
        status="in_progress",
        owner="john@example.com"
    )

    # Get progress based on children
    progress = await item_service.get_item_progress(
        item_id=item.id,
        project_id="proj_123"
    )
    print(f"Progress: {progress['percentage']}%")
```

**Status Transitions**:
```python
# Valid status transitions enforced by ItemService
STATUS_TRANSITIONS = {
    "todo": ["in_progress", "blocked"],
    "in_progress": ["done", "blocked", "todo"],
    "blocked": ["todo", "in_progress"],
    "done": ["todo"],  # Allow reopening
}
```

### LinkService

Manages traceability relationships between items.

**Location**: `/src/tracertm/services/link_service.py`

**Key Features**:
- Create validated links between items
- Prevent duplicate links
- Cascade deletion handling
- Link type validation
- Metadata attachment

**Link Types**:
- `relates_to`: General relationship
- `depends_on`: Dependency relationship (cycle-checked)
- `implements`: Implementation link (e.g., code → requirement)
- `tests`: Test coverage link
- `derives_from`: Derivation relationship

### ProjectService

High-level project management operations.

**Location**: Managed through repositories with service-layer coordination

**Key Features**:
- Project initialization and configuration
- Cross-project querying
- Project-level statistics
- Backup and restore coordination

## Analysis Services

### ImpactAnalysisService

Analyzes the downstream and upstream impact of item changes using BFS graph traversal.

**Location**: `/src/tracertm/services/impact_analysis_service.py`

**Algorithm**: O(V + E) BFS traversal where V = items, E = links

**Example Usage**:

```python
from tracertm.services.impact_analysis_service import ImpactAnalysisService

async def analyze_requirement_change(session: AsyncSession):
    impact_service = ImpactAnalysisService(session)

    # Analyze downstream impact
    result = await impact_service.analyze_impact(
        item_id="req_001",
        max_depth=10,
        link_types=["implements", "tests"]  # Optional filter
    )

    print(f"Total affected: {result.total_affected}")
    print(f"Max depth: {result.max_depth_reached}")
    print(f"Affected by view: {result.affected_by_view}")

    # Analyze upstream dependencies
    reverse_impact = await impact_service.analyze_reverse_impact(
        item_id="req_001",
        max_depth=10
    )
    print(f"Depends on {reverse_impact.total_affected} items")
```

**Output Structure**:
```python
@dataclass
class ImpactAnalysisResult:
    root_item_id: str
    root_item_title: str
    total_affected: int
    max_depth_reached: int
    affected_by_depth: dict[int, int]  # depth -> count
    affected_by_view: dict[str, int]   # view -> count
    affected_items: list[dict[str, Any]]
    critical_paths: list[list[str]]     # Paths to leaf nodes
```

### CycleDetectionService

Prevents circular dependencies in `depends_on` relationships using graph algorithms.

**Location**: `/src/tracertm/services/cycle_detection_service.py`

**Key Features**:
- Pre-validation before link creation
- Tarjan's algorithm for strongly connected components
- Full cycle detection across project
- Support for both sync and async contexts

**Example Usage**:

```python
from tracertm.services.cycle_detection_service import CycleDetectionService

async def validate_dependency(session: AsyncSession):
    cycle_service = CycleDetectionService(session)

    # Check if adding link would create cycle
    would_cycle = cycle_service.has_cycle(
        project_id="proj_123",
        source_id="item_A",
        target_id="item_B",
        link_type="depends_on"
    )

    if would_cycle:
        raise ValueError("Cannot create dependency - would create cycle")

    # Detect all existing cycles
    result = await cycle_service.detect_cycles_async(
        project_id="proj_123",
        link_types=["depends_on"]
    )

    if result.has_cycles:
        print(f"Found {result.cycle_count} cycles:")
        for cycle in result.cycles:
            print(f"  Cycle: {' -> '.join(cycle)}")
```

### CriticalPathService

Identifies critical paths through the project graph (longest paths affecting project timeline).

**Location**: `/src/tracertm/services/critical_path_service.py`

**Example Usage**:

```python
from tracertm.services.critical_path_service import CriticalPathService

async def find_bottlenecks(session: AsyncSession):
    critical_path = CriticalPathService(session)

    result = await critical_path.calculate_critical_path(
        project_id="proj_123",
        start_item_id="epic_001"
    )

    print(f"Critical path length: {result.total_duration}")
    print(f"Path: {' -> '.join(result.path)}")
    print(f"Bottlenecks: {result.bottlenecks}")
```

### ShortestPathService

Finds shortest paths between items using Dijkstra's algorithm.

**Location**: `/src/tracertm/services/shortest_path_service.py`

**Example Usage**:

```python
from tracertm.services.shortest_path_service import ShortestPathService

async def trace_requirement_to_test(session: AsyncSession):
    path_service = ShortestPathService(session)

    path = await path_service.find_shortest_path(
        project_id="proj_123",
        source_id="req_001",
        target_id="test_042",
        max_depth=10
    )

    if path:
        print(f"Traceability path ({len(path)} hops):")
        for item_id in path:
            print(f"  -> {item_id}")
```

## Performance Services

### CacheService

Redis-based caching layer for frequently accessed data.

**Location**: `/src/tracertm/services/cache_service.py`

**Key Features**:
- TTL-based expiration
- Key generation with MD5 hashing
- Hit/miss statistics
- Prefix-based cache invalidation
- Graceful degradation when Redis unavailable

**Example Usage**:

```python
from tracertm.services.cache_service import CacheService

async def cached_query():
    cache = CacheService(redis_url="redis://localhost:6379")

    # Try cache first
    key = "project:proj_123:items:view:requirements"
    cached_items = await cache.get(key)

    if cached_items:
        return cached_items

    # Cache miss - fetch from database
    items = await fetch_items_from_db()

    # Cache for 1 hour
    await cache.set(key, items, ttl_seconds=3600)

    return items

async def invalidate_project_cache():
    cache = CacheService()

    # Clear all project-related cache
    deleted = await cache.clear_prefix("project:proj_123")
    print(f"Invalidated {deleted} cache entries")

    # Get statistics
    stats = await cache.get_stats()
    print(f"Hit rate: {stats.hit_rate:.2f}%")
```

### QueryOptimizationService

Optimizes database queries for better performance.

**Location**: `/src/tracertm/services/query_optimization_service.py`

**Key Features**:
- Query analysis and recommendations
- Index suggestions
- Join optimization
- N+1 query detection

### PerformanceTuningService

Runtime performance monitoring and tuning.

**Location**: `/src/tracertm/services/performance_tuning_service.py`

**Key Features**:
- Slow query detection
- Memory usage monitoring
- Connection pool optimization
- Profiling integration

## Integration Services

### ExternalIntegrationService

Manages integrations with external systems (GitHub, Jira, Slack, etc.).

**Location**: `/src/tracertm/services/external_integration_service.py`

**Supported Integrations**:
- `GITHUB`: GitHub issues and pull requests
- `GITLAB`: GitLab issues and merge requests
- `SLACK`: Slack notifications
- `VSCODE`: VS Code extension
- `JIRA`: Jira issue tracking
- `CUSTOM`: Custom webhook integrations

**Example Usage**:

```python
from tracertm.services.external_integration_service import (
    ExternalIntegrationService,
    IntegrationType
)

def setup_integrations():
    integration_service = ExternalIntegrationService()

    # Register GitHub integration
    github = integration_service.register_integration(
        name="github_main",
        integration_type=IntegrationType.GITHUB,
        config={
            "repo": "owner/repo",
            "token": "ghp_xxx",
            "sync_interval": 3600
        }
    )

    # Register Slack notifications
    slack = integration_service.register_integration(
        name="slack_alerts",
        integration_type=IntegrationType.SLACK,
        config={
            "webhook_url": "https://hooks.slack.com/xxx",
            "channel": "#tracertm-alerts"
        }
    )

    # List all integrations
    integrations = integration_service.list_integrations()

    # Disable integration temporarily
    integration_service.disable_integration("slack_alerts")
```

### ApiWebhooksService

Webhook management for real-time event notifications.

**Location**: `/src/tracertm/services/api_webhooks_service.py`

**Key Features**:
- Webhook registration and management
- Event filtering
- Retry logic with exponential backoff
- Signature verification
- Rate limiting

**Example Usage**:

```python
from tracertm.services.api_webhooks_service import ApiWebhooksService

async def setup_webhooks(session: AsyncSession):
    webhook_service = ApiWebhooksService(session)

    # Register webhook for item events
    webhook = await webhook_service.register_webhook(
        project_id="proj_123",
        url="https://api.example.com/webhooks/tracertm",
        events=["item_created", "item_updated", "item_deleted"],
        secret="webhook_secret_key"
    )

    # Test webhook
    await webhook_service.test_webhook(webhook.id)
```

### CommitLinkingService

Links Git commits to TraceRTM items for code traceability.

**Location**: `/src/tracertm/services/commit_linking_service.py`

**Example Usage**:

```python
from tracertm.services.commit_linking_service import CommitLinkingService

async def link_commits(session: AsyncSession):
    commit_service = CommitLinkingService(session)

    # Parse commit message for item references
    commit_msg = "Fix authentication bug [REQ-123] [TEST-456]"

    linked = await commit_service.link_commit_to_items(
        project_id="proj_123",
        commit_sha="abc123def456",
        commit_message=commit_msg,
        author="developer@example.com",
        repository="github.com/owner/repo"
    )

    print(f"Linked commit to {len(linked)} items")
```

## Agent Services

### AgentCoordinationService

Coordinates multiple agents working on the same project, detecting and resolving conflicts.

**Location**: `/src/tracertm/services/agent_coordination_service.py`

**Key Features**:
- Agent registration and lifecycle
- Conflict detection between concurrent agents
- Conflict resolution strategies
- Agent activity monitoring

**Example Usage**:

```python
from tracertm.services.agent_coordination_service import AgentCoordinationService

async def coordinate_agents(session: AsyncSession):
    coordination = AgentCoordinationService(session)

    # Register agents
    agent1 = await coordination.register_agent(
        project_id="proj_123",
        name="Developer Agent",
        agent_type="human",
        metadata={"user_id": "user_001"}
    )

    agent2 = await coordination.register_agent(
        project_id="proj_123",
        name="AI Assistant",
        agent_type="ai",
        metadata={"model": "gpt-4"}
    )

    # Detect conflicts
    conflicts = await coordination.detect_conflicts(project_id="proj_123")

    if conflicts:
        for conflict in conflicts:
            print(f"Conflict between {conflict.agent1_id} and {conflict.agent2_id}")
            print(f"Type: {conflict.conflict_type}")
            print(f"Entity: {conflict.entity_id}")

            # Resolve conflict (various strategies available)
            resolution = await coordination.resolve_conflict(
                conflict=conflict,
                strategy="last_write_wins"
            )
```

### AgentMonitoringService

Monitors agent health, performance, and activity.

**Location**: `/src/tracertm/services/agent_monitoring_service.py`

**Example Usage**:

```python
from tracertm.services.agent_monitoring_service import AgentMonitoringService

async def monitor_agents(session: AsyncSession):
    monitoring = AgentMonitoringService(session)

    # Get agent health
    health = await monitoring.get_agent_health(agent_id="agent_001")
    print(f"Agent status: {health.status}")
    print(f"Last heartbeat: {health.last_heartbeat}")
    print(f"Error count: {health.error_count}")

    # Get performance metrics
    metrics = await monitoring.get_agent_metrics(
        agent_id="agent_001",
        timeframe="1h"
    )
    print(f"Operations/min: {metrics.operations_per_minute}")
    print(f"Average latency: {metrics.avg_latency_ms}ms")
```

### AgentPerformanceService

Tracks and optimizes agent performance.

**Location**: `/src/tracertm/services/agent_performance_service.py`

**Key Features**:
- Operation timing and profiling
- Throughput analysis
- Resource usage tracking
- Performance recommendations

## Specialized Services

### ChaosModeService

Advanced testing and debugging utilities including chaos engineering features.

**Location**: `/src/tracertm/services/chaos_mode_service.py`

**Key Features**:
- Zombie detection (orphaned/stale items)
- Impact simulation
- Random failure injection
- Performance degradation simulation

**Example Usage**:

```python
from tracertm.services.chaos_mode_service import ChaosModeService

async def chaos_testing(session: AsyncSession):
    chaos = ChaosModeService(session)

    # Detect zombie items (orphaned and inactive)
    zombies = await chaos.detect_zombies(
        project_id="proj_123",
        days_inactive=30
    )

    print(f"Found {zombies['zombie_count']} zombie items")
    print(f"Zombie percentage: {zombies['zombie_percentage']:.2f}%")

    for zombie in zombies['zombies']:
        print(f"  {zombie['title']} - {zombie['days_inactive']} days inactive")

    # Analyze impact of changes
    impact = await chaos.analyze_impact(
        project_id="proj_123",
        item_id="item_001"
    )
```

### SecurityComplianceService

Security and compliance features including audit logging and access control.

**Location**: `/src/tracertm/services/security_compliance_service.py`

**Key Features**:
- Audit trail generation
- Compliance report generation
- Access control validation
- Data retention policies

### BulkOperationService

Handles bulk operations with preview, validation, and atomic execution.

**Location**: `/src/tracertm/services/bulk_operation_service.py`

**Key Features**:
- Preview changes before execution
- Batch validation
- Atomic transactions
- Progress tracking
- Error handling with partial rollback

**Example Usage**:

```python
from tracertm.services.bulk_operation_service import BulkOperationService

def bulk_update_items(session: Session):
    bulk_service = BulkOperationService(session)

    # Preview bulk update
    preview = bulk_service.bulk_update_preview(
        project_id="proj_123",
        filters={"view": "requirements", "status": "todo"},
        updates={"status": "in_progress", "owner": "john@example.com"},
        limit=5
    )

    print(f"Will update {preview['total_count']} items")
    print(f"Estimated duration: {preview['estimated_duration_ms']}ms")
    print(f"Warnings: {preview['warnings']}")

    # Execute bulk update
    result = bulk_service.bulk_update_items(
        project_id="proj_123",
        filters={"view": "requirements", "status": "todo"},
        updates={"status": "in_progress"},
        agent_id="agent_001"
    )

    print(f"Updated {result['items_updated']} items")
```

### ConcurrentOperationsService

Handles concurrent operations with conflict detection and resolution.

**Location**: `/src/tracertm/services/concurrent_operations_service.py`

**Example Usage**:

```python
from tracertm.services.concurrent_operations_service import (
    ConcurrentOperationsService
)

async def concurrent_updates(session: AsyncSession):
    concurrent = ConcurrentOperationsService(session)

    # Execute operations with conflict detection
    await concurrent.execute_with_lock(
        entity_id="item_001",
        operation=lambda: update_item(item_id="item_001")
    )
```

## Import/Export Services

### ImportService

Imports data from various formats.

**Location**: `/src/tracertm/services/import_service.py`

**Supported Formats**:
- JSON
- CSV
- Excel
- YAML

### ExportService

Exports project data to various formats.

**Location**: `/src/tracertm/services/export_service.py`

**Supported Formats**:
- JSON (full project export)
- CSV (tabular data)
- Excel (multi-sheet workbooks)
- PDF (reports)
- Markdown (documentation)

**Example Usage**:

```python
from tracertm.services.export_service import ExportService

async def export_project(session: AsyncSession):
    export_service = ExportService(session)

    # Export to JSON
    json_data = await export_service.export_project(
        project_id="proj_123",
        format="json",
        include_deleted=False
    )

    # Export to CSV
    csv_data = await export_service.export_items(
        project_id="proj_123",
        view="requirements",
        format="csv"
    )

    # Export traceability matrix
    matrix = await export_service.export_traceability_matrix(
        project_id="proj_123",
        source_view="requirements",
        target_view="tests",
        format="excel"
    )
```

### GitHubImportService / JiraImportService

Specialized importers for external systems.

**Locations**:
- `/src/tracertm/services/github_import_service.py`
- `/src/tracertm/services/jira_import_service.py`

**Example Usage**:

```python
from tracertm.services.github_import_service import GitHubImportService

async def import_from_github(session: AsyncSession):
    github = GitHubImportService(session)

    result = await github.import_issues(
        project_id="proj_123",
        repo="owner/repo",
        token="ghp_xxx",
        view="requirements",
        label_filter="enhancement"
    )

    print(f"Imported {result['imported_count']} issues")
```

## Workflow Services

### StatusWorkflowService

Manages status transitions and workflow automation.

**Location**: `/src/tracertm/services/status_workflow_service.py`

### ProgressService

Tracks and calculates project progress.

**Location**: `/src/tracertm/services/progress_service.py`

**Example Usage**:

```python
from tracertm.services.progress_service import ProgressService

async def track_progress(session: AsyncSession):
    progress = ProgressService(session)

    # Get project progress
    project_progress = await progress.get_project_progress(
        project_id="proj_123"
    )

    print(f"Overall: {project_progress.percentage}%")
    print(f"By view:")
    for view, pct in project_progress.by_view.items():
        print(f"  {view}: {pct}%")
```

## Advanced Services

### TraceabilityMatrixService

Generates comprehensive traceability matrices showing coverage between views.

**Location**: `/src/tracertm/services/traceability_matrix_service.py`

### VisualizationService

Generates visualizations of project data (graphs, charts, diagrams).

**Location**: `/src/tracertm/services/visualization_service.py`

### BenchmarkService

Performance benchmarking and comparison tools.

**Location**: `/src/tracertm/services/benchmark_service.py`

### DocumentationService

Automated documentation generation from project data.

**Location**: `/src/tracertm/services/documentation_service.py`

## Service Dependencies and Injection

### Dependency Pattern

Services follow a consistent dependency injection pattern:

```python
class MyService:
    def __init__(self, session: AsyncSession):
        self.session = session
        # Initialize repositories
        self.items = ItemRepository(session)
        self.links = LinkRepository(session)
        self.events = EventRepository(session)
```

### Service Composition

Services can depend on other services:

```python
class CompositeService:
    def __init__(self, session: AsyncSession):
        self.session = session
        # Compose with other services
        self.item_service = ItemService(session)
        self.impact_service = ImpactAnalysisService(session)
        self.cache_service = CacheService()

    async def complex_operation(self, item_id: str):
        # Use multiple services
        item = await self.item_service.get_item(item_id)
        impact = await self.impact_service.analyze_impact(item_id)

        # Cache the result
        await self.cache_service.set(
            f"impact:{item_id}",
            impact,
            ttl_seconds=300
        )
```

### Testing with Mocks

Services are designed to be easily testable with mock repositories:

```python
import pytest
from unittest.mock import AsyncMock, MagicMock

@pytest.fixture
def mock_item_repository():
    repo = AsyncMock()
    repo.get_by_id.return_value = MagicMock(
        id="item_001",
        title="Test Item",
        status="todo"
    )
    return repo

async def test_item_service(mock_item_repository):
    session = AsyncMock()

    # Inject mock repository
    service = ItemService(session)
    service.items = mock_item_repository

    item = await service.get_item("proj_123", "item_001")
    assert item.title == "Test Item"

    mock_item_repository.get_by_id.assert_called_once_with(
        "item_001", "proj_123"
    )
```

## Service Layer Best Practices

### 1. Transaction Management

Services should use transactions for multi-step operations:

```python
async def complex_operation(self, project_id: str):
    async with self.session.begin():
        # All operations in this block are atomic
        item = await self.items.create(...)
        link = await self.links.create(...)
        await self.events.log(...)
        # Automatically commits on success, rolls back on exception
```

### 2. Error Handling

Services should raise meaningful exceptions:

```python
class ItemNotFoundError(Exception):
    pass

class InvalidStatusTransitionError(Exception):
    pass

async def update_status(self, item_id: str, new_status: str):
    item = await self.items.get_by_id(item_id)
    if not item:
        raise ItemNotFoundError(f"Item {item_id} not found")

    if not self._is_valid_transition(item.status, new_status):
        raise InvalidStatusTransitionError(
            f"Cannot transition from {item.status} to {new_status}"
        )
```

### 3. Event Logging

Log significant operations for audit trails:

```python
async def delete_item(self, item_id: str, agent_id: str):
    item = await self.items.get_by_id(item_id)
    await self.items.delete(item_id)

    # Always log deletions
    await self.events.log(
        project_id=item.project_id,
        event_type="item_deleted",
        entity_type="item",
        entity_id=item_id,
        data={"title": item.title},
        agent_id=agent_id
    )
```

### 4. Optimistic Locking

Use version checks for concurrent updates:

```python
async def update_item(self, item_id: str, **updates):
    item = await self.items.get_by_id(item_id)

    # Include version in update
    updated = await self.items.update(
        item_id=item_id,
        expected_version=item.version,  # Prevents lost updates
        **updates
    )

    return updated
```

### 5. Caching Strategy

Cache expensive operations:

```python
async def get_traceability_matrix(self, project_id: str, ...):
    cache_key = f"matrix:{project_id}:{source_view}:{target_view}"

    # Try cache first
    cached = await self.cache.get(cache_key)
    if cached:
        return cached

    # Compute expensive matrix
    matrix = await self._compute_matrix(...)

    # Cache for 5 minutes
    await self.cache.set(cache_key, matrix, ttl_seconds=300)

    return matrix
```

## Complete Service Reference

### Alphabetical Service List

1. **AdvancedAnalyticsService** - Advanced analytics and metrics
2. **AdvancedTraceabilityService** - Enhanced traceability features
3. **AdvancedTraceabilityEnhancementsService** - Additional traceability utilities
4. **AgentCoordinationService** - Multi-agent coordination
5. **AgentMetricsService** - Agent performance metrics
6. **AgentMonitoringService** - Agent health monitoring
7. **AgentPerformanceService** - Agent optimization
8. **ApiWebhooksService** - Webhook management
9. **AutoLinkService** - Automatic link suggestion
10. **BenchmarkService** - Performance benchmarking
11. **BulkOperationService** - Bulk operations with preview
12. **BulkService** - Simple bulk operations
13. **CacheService** - Redis caching layer
14. **ChaosModeService** - Chaos engineering and testing
15. **CommitLinkingService** - Git commit traceability
16. **ConcurrentOperationsService** - Concurrent operation handling
17. **ConflictResolutionService** - Conflict detection and resolution
18. **CriticalPathService** - Critical path analysis
19. **CycleDetectionService** - Circular dependency detection
20. **DocumentationService** - Auto-documentation generation
21. **EventService** - Event handling
22. **EventSourcingService** - Event sourcing implementation
23. **ExportImportService** - Combined import/export
24. **ExportService** - Data export
25. **ExternalIntegrationService** - External system integration
26. **GraphService** - Graph operations
27. **ImpactAnalysisService** - Impact analysis
28. **ImportService** - Data import
29. **ItemService** - Core item operations
30. **JiraImportService** - Jira integration
31. **LinkService** - Link management
32. **MaterializedViewService** - Materialized views
33. **PerformanceOptimizationService** - Query optimization
34. **PerformanceService** - Performance monitoring
35. **PerformanceTuningService** - Runtime tuning
36. **PluginService** - Plugin system
37. **ProgressService** - Progress tracking
38. **ProjectBackupService** - Project backup/restore
39. **QueryOptimizationService** - Query analysis
40. **QueryService** - Advanced querying
41. **SearchService** - Full-text search
42. **SecurityComplianceService** - Security and compliance
43. **ShortestPathService** - Shortest path finding
44. **StatelessIngestionService** - Stateless data ingestion
45. **StatusWorkflowService** - Status workflows
46. **SyncService** - Data synchronization
47. **TraceabilityMatrixService** - Matrix generation
48. **TraceabilityService** - Core traceability
49. **TuiService** - Terminal UI support
50. **VerificationService** - Data verification
51. **ViewRegistryService** - View management
52. **VisualizationService** - Data visualization

And many more specialized services for specific use cases.

## Next Steps

- Learn about [Repositories](/docs/development/internals/repositories) that services depend on
- Explore [API Endpoints](/docs/development/api) that expose service functionality
- Understand [Event System](/docs/development/internals/events) for audit logging
- Review [Testing Services](/docs/development/testing) for service testing patterns

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For questions or contributions, see our [Developer Guide](/docs/development).
