Advanced Topics

Master advanced plugin development techniques for building high-performance, extensible, and production-ready plugin systems. Learn custom protocols, performance optimization, middleware patterns, and lifecycle management.

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Conceptual Examples - Not Current Implementation

IMPORTANT: The code examples on this page use conceptual APIs that represent future planned features and architectural patterns. These modules and classes do not currently exist in pyvider-rpcplugin:

• pyvider.rpcplugin.advanced - Planned advanced features module
• pyvider.rpcplugin.patterns - Planned microservices patterns
• pyvider.rpcplugin.events - Planned event-driven architecture
• pyvider.rpcplugin.composition - Planned plugin composition
• pyvider.rpcplugin.testing - Planned testing utilities

These examples serve as:

• Design documentation showing intended architecture
• Future roadmap illustrating planned capabilities
• Conceptual patterns for building advanced systems today using current APIs

For working code examples, see the individual topic pages linked below, which use actual current APIs.

Overview

Advanced topics in Pyvider RPC Plugin development focus on customization, optimization, and sophisticated architectural patterns. These techniques enable you to build enterprise-grade plugin systems that can scale and adapt to complex requirements.

Conceptual Architecture Example

# NOTE: This is a CONCEPTUAL example showing planned future APIs
# These imports DO NOT currently exist - see warning above

from pyvider.rpcplugin import plugin_server, plugin_client
from pyvider.rpcplugin.advanced import (
    CustomProtocol, PerformanceProfiler, MiddlewareStack, LifecycleManager
)

async def advanced_plugin_system_example():
    """Example showcasing advanced plugin system features."""

    # Custom protocol for domain-specific communication
    protocol = CustomProtocol(
        name="financial-data",
        version="2.0",
        compression="zstd",
        serialization="msgpack",
        encryption="aes-256-gcm"
    )

    # Performance profiling and optimization
    profiler = PerformanceProfiler(
        enable_tracing=True,
        enable_metrics=True,
        sample_rate=0.1
    )

    # Middleware stack for cross-cutting concerns
    middleware = MiddlewareStack([
        AuthenticationMiddleware(),
        RateLimitingMiddleware(requests_per_minute=1000),
        LoggingMiddleware(level="INFO"),
        MetricsMiddleware(),
        CachingMiddleware(ttl=300)
    ])

    # Lifecycle management for plugin orchestration
    lifecycle_manager = LifecycleManager(
        startup_timeout=30,
        shutdown_timeout=10,
        health_check_interval=30
    )

    # Advanced server with all features
    server = plugin_server(
        services=[AdvancedFinancialService()],
        protocol=protocol,
        profiler=profiler,
        middleware=middleware,
        lifecycle_manager=lifecycle_manager,
        enable_hot_reload=True,
        enable_clustering=True
    )

    try:
        await server.start()
        print("🚀 Advanced plugin system started")

        # Server runs with advanced features
        await server.wait_for_termination()

    finally:
        await server.stop()

# Usage
await advanced_plugin_system_example()

Advanced Topics Overview

🛠️ Custom Protocols

Build domain-specific communication protocols for specialized use cases:

• Protocol Design Patterns - Create efficient, type-safe protocols
• Binary Protocol Implementation - Low-overhead binary formats
• Streaming Protocol Support - Real-time data streaming protocols
• Protocol Versioning - Backward-compatible protocol evolution
• Compression and Encryption - Advanced data protection
• Cross-Language Interoperability - Multi-language plugin ecosystems

Use Cases: - High-frequency trading systems requiring microsecond latency - IoT sensor networks with bandwidth constraints - Real-time gaming protocols with custom message types - Financial data feeds with domain-specific compression - Video streaming with adaptive quality protocols

🏗️ Foundation Integration

Advanced integration patterns with Foundation infrastructure:

• Configuration Inheritance - Custom config classes extending RuntimeConfig
• Certificate Management - Dynamic certificate generation and rotation
• Per-Client Rate Limiting - Sophisticated rate limiting strategies
• Structured Logging - Context-aware observability patterns
• Circuit Breakers - Resilient error handling and recovery
• Connection Pooling - Efficient resource management

Use Cases: - Multi-tenant SaaS platforms with per-client rate limits - High-security environments requiring certificate rotation - Microservices with comprehensive observability requirements - Systems requiring automatic failover and recovery

⚡ Performance Tuning

Optimize plugin performance for production workloads:

• Profiling and Benchmarking - Identify performance bottlenecks
• Connection Pool Optimization - Efficient resource management
• Memory Management - Reduce allocations and GC pressure
• CPU Optimization - Multi-core processing and async patterns
• Network Optimization - Minimize latency and maximize throughput
• Caching Strategies - Smart caching for frequently accessed data
• Load Balancing - Distribute traffic across plugin instances

Performance Targets: - Sub-millisecond response times for simple operations - 100,000+ requests per second throughput - Linear scaling across multiple CPU cores - Memory usage optimization for long-running processes - Zero-copy data processing where possible

🔗 Middleware

Implement cross-cutting concerns with middleware patterns:

• Middleware Architecture - Flexible, composable middleware stacks
• Authentication Middleware - JWT, OAuth, and custom auth
• Rate Limiting - Protect against abuse and ensure fairness
• Logging and Tracing - Observability and debugging support
• Metrics Collection - Performance monitoring and alerting
• Error Handling - Consistent error processing and recovery
• Request/Response Transformation - Data format conversions
• Caching Middleware - Transparent caching layers

Middleware Examples:

# Authentication middleware
@middleware
async def jwt_auth_middleware(request, call_next):
    token = extract_jwt_token(request)
    user = validate_jwt_token(token)
    request.context.user = user
    return await call_next(request)

# Rate limiting middleware  
@middleware
async def rate_limit_middleware(request, call_next):
    client_id = get_client_id(request)
    if not rate_limiter.allow_request(client_id):
        raise RateLimitExceeded()
    return await call_next(request)

🔄 Plugin Lifecycle

Manage complex plugin lifecycles and orchestration:

• Startup Orchestration - Coordinated plugin initialization
• Dependency Management - Handle inter-plugin dependencies
• Hot Reloading - Update plugins without downtime
• Health Monitoring - Continuous health checks and recovery
• Graceful Shutdown - Clean resource cleanup and state persistence
• Plugin Registry - Dynamic plugin discovery and management
• Version Management - Plugin versioning and compatibility
• Clustering Support - Multi-instance plugin coordination

Lifecycle Stages: 1. Discovery - Find and register available plugins 2. Validation - Verify plugin compatibility and dependencies 3. Initialization - Start plugins in dependency order 4. Runtime - Normal operation with health monitoring 5. Update - Hot reload or version upgrades 6. Shutdown - Graceful cleanup and state preservation

Advanced Architecture Patterns

Microservices Integration

# NOTE: CONCEPTUAL example - pyvider.rpcplugin.patterns module does not exist yet
from pyvider.rpcplugin.patterns import MicroservicePlugin, ServiceMesh

class OrderManagementService(MicroservicePlugin):
    """Microservice for order processing."""

    def __init__(self):
        super().__init__(
            service_name="order-management",
            version="2.1.0",
            dependencies=["payment-service", "inventory-service"],
            health_check_endpoint="/health",
            metrics_endpoint="/metrics"
        )

    async def startup(self):
        """Initialize service dependencies."""
        self.payment_client = await self.get_dependency("payment-service")
        self.inventory_client = await self.get_dependency("inventory-service")

        # Register with service mesh
        await self.register_with_service_mesh()

    async def process_order(self, request):
        """Process order with dependent services."""

        # Check inventory
        inventory_result = await self.inventory_client.check_availability(
            items=request.items
        )

        if not inventory_result.available:
            raise InsufficientInventory()

        # Process payment
        payment_result = await self.payment_client.process_payment(
            amount=request.total_amount,
            payment_method=request.payment_method
        )

        # Create order
        order = await self.create_order(request, payment_result.transaction_id)

        # Update inventory
        await self.inventory_client.reserve_items(
            order_id=order.id,
            items=request.items
        )

        return OrderResponse(
            order_id=order.id,
            status="confirmed",
            estimated_delivery=order.estimated_delivery
        )

# Service mesh configuration
service_mesh = ServiceMesh(
    discovery_backend="consul",
    load_balancing="round_robin",
    circuit_breaker_enabled=True,
    timeout_seconds=30,
    retry_policy="exponential_backoff"
)

# Deploy microservice
await service_mesh.deploy_service(OrderManagementService())

Event-Driven Architecture

# NOTE: CONCEPTUAL example - pyvider.rpcplugin.events module does not exist yet
from pyvider.rpcplugin.events import EventBus, EventHandler, Event

class OrderCreated(Event):
    """Event emitted when order is created."""
    order_id: str
    customer_id: str
    total_amount: float
    items: list[dict]

class InventoryService(EventHandler):
    """Service that handles inventory events."""

    @event_handler("order.created")
    async def handle_order_created(self, event: OrderCreated):
        """Reserve inventory when order is created."""

        try:
            await self.reserve_inventory(event.order_id, event.items)

            # Emit inventory reserved event
            await self.emit_event(InventoryReserved(
                order_id=event.order_id,
                reserved_items=event.items
            ))

        except InsufficientInventory:
            # Emit inventory shortage event
            await self.emit_event(InventoryShortage(
                order_id=event.order_id,
                unavailable_items=event.items
            ))

class NotificationService(EventHandler):
    """Service that handles notification events."""

    @event_handler("order.created")
    async def send_order_confirmation(self, event: OrderCreated):
        """Send order confirmation to customer."""

        await self.send_email(
            to=event.customer_id,
            template="order_confirmation",
            context={
                "order_id": event.order_id,
                "total_amount": event.total_amount,
                "items": event.items
            }
        )

    @event_handler("inventory.shortage")
    async def notify_inventory_team(self, event: InventoryShortage):
        """Notify inventory team of shortages."""

        await self.send_slack_message(
            channel="#inventory",
            message=f"Inventory shortage for order {event.order_id}"
        )

# Event bus setup
event_bus = EventBus(
    backend="redis",
    persistence=True,
    retry_failed_events=True,
    dead_letter_queue=True
)

# Register event handlers
event_bus.register_handler(InventoryService())
event_bus.register_handler(NotificationService())

# Emit events from business logic
async def create_order(order_request):
    """Create order and emit events."""

    order = await save_order(order_request)

    # Emit order created event
    await event_bus.emit(OrderCreated(
        order_id=order.id,
        customer_id=order.customer_id,
        total_amount=order.total_amount,
        items=order.items
    ))

    return order

Plugin Composition Patterns

# NOTE: CONCEPTUAL example - pyvider.rpcplugin.composition module does not exist yet
from pyvider.rpcplugin.composition import PluginComposer, CompositionStrategy

class DataProcessingPipeline:
    """Composable data processing pipeline."""

    def __init__(self):
        self.composer = PluginComposer(
            strategy=CompositionStrategy.PIPELINE
        )

        # Register processing stages
        self.composer.add_stage("validation", DataValidationPlugin())
        self.composer.add_stage("transformation", DataTransformationPlugin()) 
        self.composer.add_stage("enrichment", DataEnrichmentPlugin())
        self.composer.add_stage("persistence", DataPersistencePlugin())

    async def process_data(self, raw_data: dict) -> dict:
        """Process data through plugin pipeline."""

        return await self.composer.execute(raw_data)

class DataValidationPlugin:
    """Plugin for data validation."""

    async def process(self, data: dict, context: dict) -> dict:
        """Validate input data."""

        if not data.get("id"):
            raise ValidationError("Missing required field: id")

        if not isinstance(data.get("timestamp"), (int, float)):
            raise ValidationError("Invalid timestamp format")

        context["validation_passed"] = True
        return data

class DataTransformationPlugin:
    """Plugin for data transformation."""

    async def process(self, data: dict, context: dict) -> dict:
        """Transform data format."""

        # Convert timestamp to ISO format
        data["timestamp"] = datetime.fromtimestamp(
            data["timestamp"]
        ).isoformat()

        # Normalize field names
        data = {self.normalize_key(k): v for k, v in data.items()}

        context["transformation_applied"] = True
        return data

    def normalize_key(self, key: str) -> str:
        """Normalize field names to snake_case."""
        return key.lower().replace(" ", "_").replace("-", "_")

# Usage with composition
pipeline = DataProcessingPipeline()

processed_data = await pipeline.process_data({
    "id": "12345",
    "timestamp": 1677648000.0,
    "User Name": "john_doe",
    "order-total": 99.99
})

Development Workflow

Advanced Testing Strategies

# NOTE: CONCEPTUAL example - pyvider.rpcplugin.testing module does not exist yet
import pytest
from pyvider.rpcplugin.testing import (
    PluginTestCase, MockPlugin, PerformanceTest, IntegrationTest
)

class AdvancedPluginTest(PluginTestCase):
    """Advanced plugin testing with performance and integration tests."""

    @pytest.fixture
    async def plugin_cluster(self):
        """Setup plugin cluster for testing."""

        # Create test cluster with multiple plugin instances
        cluster = await self.create_test_cluster([
            ("payment-service", 3),    # 3 instances
            ("inventory-service", 2),  # 2 instances
            ("order-service", 1)       # 1 instance
        ])

        yield cluster

        await cluster.shutdown()

    @PerformanceTest(
        target_rps=1000,
        duration_seconds=30,
        max_response_time_ms=100
    )
    async def test_high_load_performance(self, plugin_cluster):
        """Test plugin performance under high load."""

        async def make_request():
            result = await plugin_cluster.order_service.create_order({
                "customer_id": "test_customer",
                "items": [{"id": "item1", "quantity": 1}],
                "total_amount": 99.99
            })
            return result

        # Performance test framework handles load generation
        results = await self.run_load_test(make_request)

        # Assertions
        assert results.success_rate > 0.99
        assert results.p95_response_time < 50  # milliseconds
        assert results.error_rate < 0.01

    @IntegrationTest
    async def test_end_to_end_order_flow(self, plugin_cluster):
        """Test complete order processing flow."""

        # Setup test data
        customer_id = "integration_test_customer"
        order_items = [
            {"id": "product_1", "quantity": 2, "price": 29.99},
            {"id": "product_2", "quantity": 1, "price": 49.99}
        ]

        # Step 1: Check inventory
        inventory_result = await plugin_cluster.inventory_service.check_availability(
            items=order_items
        )
        assert inventory_result.available

        # Step 2: Process payment
        payment_result = await plugin_cluster.payment_service.process_payment(
            customer_id=customer_id,
            amount=109.97,
            payment_method="credit_card"
        )
        assert payment_result.status == "success"

        # Step 3: Create order
        order_result = await plugin_cluster.order_service.create_order({
            "customer_id": customer_id,
            "items": order_items,
            "payment_transaction_id": payment_result.transaction_id,
            "total_amount": 109.97
        })

        assert order_result.status == "confirmed"
        assert order_result.order_id is not None

        # Step 4: Verify inventory update
        updated_inventory = await plugin_cluster.inventory_service.get_inventory(
            item_ids=["product_1", "product_2"]
        )

        # Verify quantities were reserved
        for item in updated_inventory.items:
            if item.id == "product_1":
                assert item.reserved_quantity >= 2
            elif item.id == "product_2":
                assert item.reserved_quantity >= 1

    async def test_plugin_failure_recovery(self, plugin_cluster):
        """Test plugin system recovery from failures."""

        # Simulate payment service failure
        await plugin_cluster.payment_service.simulate_failure()

        # Verify other services continue working
        inventory_result = await plugin_cluster.inventory_service.check_availability(
            items=[{"id": "test_item", "quantity": 1}]
        )
        assert inventory_result.available

        # Verify circuit breaker activates
        with pytest.raises(ServiceUnavailableError):
            await plugin_cluster.order_service.create_order({
                "customer_id": "test",
                "items": [{"id": "test_item", "quantity": 1}],
                "total_amount": 10.00
            })

        # Recover payment service
        await plugin_cluster.payment_service.recover()

        # Verify system returns to normal
        await asyncio.sleep(5)  # Wait for circuit breaker reset

        order_result = await plugin_cluster.order_service.create_order({
            "customer_id": "recovery_test",
            "items": [{"id": "test_item", "quantity": 1}],
            "total_amount": 10.00
        })

        assert order_result.status == "confirmed"

Production Deployment Patterns

Kubernetes Deployment

# advanced-plugin-deployment.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: plugin-config
data:
  plugin.yaml: |
    server:
      port: 8080
      workers: 4
      max_connections: 1000

    performance:
      enable_profiling: true
      metrics_endpoint: "/metrics"
      health_endpoint: "/health"

    middleware:
      - name: "authentication"
        config:
          jwt_secret: "${PLUGIN_JWT_SECRET}"
      - name: "rate_limiting"
        config:
          requests_per_minute: 1000
      - name: "logging"
        config:
          level: "INFO"

    protocols:
      - name: "financial-data"
        version: "2.0"
        compression: "zstd"

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: advanced-plugin-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: advanced-plugin-server
  template:
    metadata:
      labels:
        app: advanced-plugin-server
    spec:
      containers:
      - name: plugin-server
        image: my-company/advanced-plugin-server:latest
        ports:
        - containerPort: 8080
          name: grpc
        - containerPort: 8081
          name: metrics
        env:
        - name: PLUGIN_JWT_SECRET
          valueFrom:
            secretKeyRef:
              name: plugin-secrets
              key: jwt-secret
        - name: PLUGIN_CONFIG_PATH
          value: "/etc/plugin/plugin.yaml"
        volumeMounts:
        - name: config
          mountPath: /etc/plugin
          readOnly: true
        livenessProbe:
          httpGet:
            path: /health
            port: 8081
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /health
            port: 8081
          initialDelaySeconds: 5
          periodSeconds: 5
        resources:
          limits:
            memory: "1Gi"
            cpu: "1000m"
          requests:
            memory: "512Mi"
            cpu: "500m"
      volumes:
      - name: config
        configMap:
          name: plugin-config

---
apiVersion: v1
kind: Service
metadata:
  name: advanced-plugin-service
spec:
  selector:
    app: advanced-plugin-server
  ports:
  - name: grpc
    port: 8080
    targetPort: 8080
  - name: metrics
    port: 8081
    targetPort: 8081

Next Steps

Ready to master advanced plugin development? Choose your focus area:

• Custom Protocols - Build specialized communication protocols
• Performance Tuning - Optimize for production workloads
• Middleware - Implement cross-cutting concerns
• Plugin Lifecycle - Master plugin orchestration and management

Each section provides practical examples, performance benchmarks, and production-ready implementations for advanced plugin development scenarios.