Technical Service Documentation

Technical Service Documentation

This section provides detailed technical documentation for implementing and integrating AIMatrix services in production environments. Target audience includes software developers, system architects, and DevOps engineers.

Service Categories

AI Agent Services

Agent Design Service Technical

  • State machine implementation patterns
  • Code generation APIs and SDKs
  • Testing frameworks and methodologies
  • Performance optimization techniques
  • Integration with existing systems
  • Custom workflow development

AI Model Training Service Technical (Coming Soon)

  • MLOps pipeline implementation
  • Model deployment automation
  • Performance monitoring and optimization
  • Custom model development workflows

Data & Knowledge Services

Knowledge Pipeline Service Technical (Coming Soon)

  • Real-time data processing architectures
  • ETL pipeline implementation
  • Knowledge graph construction
  • Vector database optimization
  • Search and retrieval APIs

Data Hub Integration Service Technical (Coming Soon)

  • Enterprise data source connectors
  • API gateway implementation
  • Data transformation pipelines
  • Security and compliance patterns

Content & Communication Services

Content Publishing Service Technical (Coming Soon)

  • Multi-channel publishing APIs
  • Content management workflows
  • Template engine implementation
  • Automated content generation

Video Intelligence Service Technical (Coming Soon)

  • Computer vision pipeline architecture
  • Real-time video processing
  • AI-powered analysis workflows
  • Streaming optimization techniques

Architecture Patterns

Microservices Architecture

AIMatrix services are designed as cloud-native microservices:

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   API Gateway   │────│  Load Balancer  │────│ Service Mesh    │
│   (Kong/Nginx)  │    │   (HAProxy)     │    │  (Istio)        │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         └───────────────────────┼───────────────────────┘
                                 │
    ┌────────────────────────────┼────────────────────────────┐
    │                            │                            │
┌─────────┐              ┌─────────┐                ┌─────────┐
│ Agent   │              │ Knowledge│                │Content  │
│ Service │              │ Service  │                │Service  │
└─────────┘              └─────────┘                └─────────┘
    │                            │                            │
┌─────────┐              ┌─────────┐                ┌─────────┐
│PostgreSQL│              │Vector DB │                │MongoDB  │
│         │              │(Pinecone)│                │         │
└─────────┘              └─────────┘                └─────────┘

Event-Driven Architecture

Services communicate through event streams and message queues:

┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│   Service   │───▶│   Event     │───▶│  Consumer   │
│  Producer   │    │   Stream    │    │  Service    │
└─────────────┘    │  (Kafka)    │    └─────────────┘
                   └─────────────┘
                          │
                   ┌─────────────┐
                   │   Event     │
                   │   Store     │
                   │(EventStore) │
                   └─────────────┘

Technical Stack

Core Technologies

  • Runtime: Kubernetes, Docker
  • Languages: Kotlin, Python, TypeScript, Go
  • Databases: PostgreSQL, Redis, Vector Databases
  • Message Queues: Apache Kafka, RabbitMQ
  • API: REST, GraphQL, gRPC
  • Monitoring: Prometheus, Grafana, OpenTelemetry

Development Framework

  • Build System: Gradle, Docker Compose
  • Testing: JUnit, pytest, Jest, Testcontainers
  • CI/CD: GitHub Actions, GitLab CI, Jenkins
  • Documentation: OpenAPI, AsyncAPI
  • Code Quality: SonarQube, CodeQL

API Standards

REST API Design

All services follow consistent REST API patterns:

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// Standard response format
interface APIResponse<T> {
  data: T
  success: boolean
  message?: string
  errors?: Array<{
    code: string
    message: string
    field?: string
  }>
  meta?: {
    pagination?: {
      page: number
      limit: number
      total: number
      hasNext: boolean
    }
    version: string
    timestamp: string
  }
}

// Error handling
interface APIError {
  code: string           // Machine-readable error code
  message: string        // Human-readable error message
  field?: string         // Field name for validation errors
  details?: any          // Additional error context
}

Authentication & Authorization

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// JWT token structure
interface JWTPayload {
  sub: string              // User ID
  iss: string              // Issuer (service)
  aud: string[]            // Audience (services)
  exp: number              // Expiration timestamp
  iat: number              // Issued at timestamp
  roles: string[]          // User roles
  permissions: string[]    // Specific permissions
  scopes: string[]         // OAuth scopes
}

// Authorization header format
// Authorization: Bearer <jwt_token>

// API key format (for service-to-service)
// X-API-Key: amx_<environment>_<random_string>

Rate Limiting

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# Rate limiting configuration
rate_limiting:
  default:
    requests_per_minute: 1000
    burst: 100
  authenticated:
    requests_per_minute: 5000
    burst: 500
  premium:
    requests_per_minute: 10000
    burst: 1000
  
  # Per-endpoint limits
  endpoints:
    "/api/v1/agents/*/execute":
      requests_per_minute: 100
      burst: 20
    "/api/v1/models/train":
      requests_per_minute: 10
      burst: 2

Development Guidelines

Service Development Lifecycle

  1. Design Phase

    • API specification (OpenAPI)
    • Architecture design review
    • Security assessment
    • Performance requirements
  2. Implementation Phase

    • Test-driven development
    • Code review process
    • Security scanning
    • Performance testing
  3. Deployment Phase

    • Container packaging
    • Kubernetes manifests
    • Configuration management
    • Monitoring setup
  4. Operations Phase

    • Health monitoring
    • Performance optimization
    • Security updates
    • Documentation maintenance

Code Standards

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// Service implementation example
@Service
@RestController
@RequestMapping("/api/v1/agents")
@Validated
class AgentService(
    private val agentRepository: AgentRepository,
    private val executionService: ExecutionService,
    private val metricsService: MetricsService
) {
    
    @PostMapping("/{agentId}/execute")
    @PreAuthorize("hasPermission(#agentId, 'agent', 'execute')")
    suspend fun executeAgent(
        @PathVariable agentId: String,
        @Valid @RequestBody request: ExecutionRequest,
        @AuthenticationPrincipal user: User
    ): ResponseEntity<ApiResponse<ExecutionResult>> {
        
        return try {
            // Validate agent exists and is active
            val agent = agentRepository.findById(agentId)
                ?: throw AgentNotFoundException(agentId)
            
            if (!agent.isActive) {
                throw AgentInactiveException(agentId)
            }
            
            // Execute agent with timeout and resource limits
            val result = executionService.execute(
                agent = agent,
                input = request.input,
                context = request.context,
                timeout = request.timeout ?: Duration.ofSeconds(30)
            )
            
            // Record metrics
            metricsService.recordExecution(
                agentId = agentId,
                userId = user.id,
                duration = result.duration,
                success = true
            )
            
            ResponseEntity.ok(
                ApiResponse.success(result)
            )
            
        } catch (e: AgentException) {
            metricsService.recordExecution(
                agentId = agentId,
                userId = user.id,
                duration = Duration.ZERO,
                success = false,
                error = e::class.simpleName
            )
            
            ResponseEntity.badRequest().body(
                ApiResponse.error<ExecutionResult>(
                    code = e.code,
                    message = e.message
                )
            )
        }
    }
}

Testing Standards

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// Integration test example
@SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.RANDOM_PORT)
@Testcontainers
@ActiveProfiles("test")
class AgentServiceIntegrationTest {
    
    @Container
    val postgres = PostgreSQLContainer("postgres:13")
        .withDatabaseName("test_db")
        .withUsername("test_user")
        .withPassword("test_password")
    
    @Container
    val redis = GenericContainer("redis:6-alpine")
        .withExposedPorts(6379)
    
    @Autowired
    lateinit var testRestTemplate: TestRestTemplate
    
    @Test
    fun `should execute agent successfully`() = runTest {
        // Given
        val agent = createTestAgent()
        val request = ExecutionRequest(
            input = mapOf("message" to "Hello, world!"),
            context = mapOf("user_id" to "test_user")
        )
        
        // When
        val response = testRestTemplate.postForEntity(
            "/api/v1/agents/${agent.id}/execute",
            request,
            ApiResponse::class.java
        )
        
        // Then
        assertThat(response.statusCode).isEqualTo(HttpStatus.OK)
        assertThat(response.body?.success).isTrue()
        assertThat(response.body?.data).isNotNull()
    }
}

Deployment Patterns

Kubernetes Deployment

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# Service deployment template
apiVersion: apps/v1
kind: Deployment
metadata:
  name: agent-service
  namespace: aimatrix
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: agent-service
        version: v1.0.0
    spec:
      containers:
      - name: agent-service
        image: aimatrix/agent-service:1.0.0
        ports:
        - containerPort: 8080
          name: http
        - containerPort: 9090
          name: metrics
        env:
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: database-credentials
              key: url
        - name: REDIS_URL
          valueFrom:
            secretKeyRef:
              name: redis-credentials
              key: url
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "1Gi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health/live
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 30
        readinessProbe:
          httpGet:
            path: /health/ready
            port: 8080
          initialDelaySeconds: 15
          periodSeconds: 10

Security Considerations

Service-to-Service Communication

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# Istio service mesh configuration
apiVersion: security.istio.io/v1beta1
kind: PeerAuthentication
metadata:
  name: default
  namespace: aimatrix
spec:
  mtls:
    mode: STRICT

---
apiVersion: security.istio.io/v1beta1
kind: AuthorizationPolicy
metadata:
  name: agent-service-policy
  namespace: aimatrix
spec:
  selector:
    matchLabels:
      app: agent-service
  rules:
  - from:
    - source:
        principals: ["cluster.local/ns/aimatrix/sa/api-gateway"]
  - to:
    - operation:
        methods: ["GET", "POST"]
        paths: ["/api/v1/agents/*"]

Data Encryption

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// Data encryption at rest and in transit
@Configuration
class SecurityConfig {
    
    @Bean
    fun encryptionService(): EncryptionService {
        return AESEncryptionService(
            keyProvider = VaultKeyProvider(),
            algorithm = "AES/GCM/NoPadding"
        )
    }
    
    @Bean
    fun databaseEncryption(): DatabaseEncryption {
        return TransparentDataEncryption(
            encryptionService = encryptionService(),
            encryptedFields = setOf("personal_data", "sensitive_content")
        )
    }
}

Performance Optimization

Caching Strategies

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// Multi-level caching implementation
@Service
class CachingService {
    
    @Cacheable(
        value = ["agent-cache"],
        key = "#agentId",
        condition = "#result.cacheable"
    )
    suspend fun getAgent(agentId: String): Agent {
        return agentRepository.findById(agentId)
    }
    
    @CacheEvict(
        value = ["agent-cache"],
        key = "#agentId"
    )
    suspend fun invalidateAgent(agentId: String) {
        // Cache eviction handled by annotation
    }
}

Database Optimization

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-- Performance optimization indexes
CREATE INDEX CONCURRENTLY idx_agents_active_created 
ON agents (active, created_at DESC) 
WHERE active = true;

CREATE INDEX CONCURRENTLY idx_executions_agent_timestamp 
ON agent_executions (agent_id, created_at DESC);

-- Partitioning for large tables
CREATE TABLE agent_executions_2024 PARTITION OF agent_executions
FOR VALUES FROM ('2024-01-01') TO ('2025-01-01');

Monitoring & Observability

Metrics Collection

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// Custom metrics implementation
@Component
class ServiceMetrics {
    
    private val executionTimer = Timer.builder("service.execution.duration")
        .description("Service execution time")
        .register(Metrics.globalRegistry)
    
    private val executionCounter = Counter.builder("service.execution.total")
        .description("Total service executions")
        .register(Metrics.globalRegistry)
    
    fun recordExecution(duration: Duration, success: Boolean) {
        executionTimer.record(duration)
        executionCounter.increment(
            Tags.of(
                "success", success.toString(),
                "service", "agent-service"
            )
        )
    }
}

For business-oriented service information, see our Business Service Documentation.