Enterprise

Build production-ready systems with confidence. Cello's enterprise features deliver observability, integration, deployment tooling, and architectural patterns -- all implemented in Rust for maximum throughput and reliability at scale.

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Enterprise Capabilities

• Observability

  ---

  Full-stack visibility into your running services with distributed tracing, metrics collection, structured logging, and automated health checks.

  • OpenTelemetry integration
  • Prometheus metrics endpoint
  • UUID request ID tracing
  • Liveness, readiness & startup probes

  Observability

• Integration

  ---

  Connect to databases, caches, message brokers, and multi-protocol APIs with async-first, pooled clients built in Rust.

  • Async database connection pooling
  • Redis with Pub/Sub & cluster
  • GraphQL & gRPC support
  • Kafka, RabbitMQ & SQS adapters

  Integration

• Deployment

  ---

  Deploy anywhere with first-class support for containers, orchestrators, and service mesh architectures.

  • Optimized Docker images
  • Kubernetes manifests & Helm charts
  • Service mesh (Istio/Linkerd)
  • Cluster mode with multi-worker

  Deployment

• Patterns

  ---

  Battle-tested architectural patterns for building resilient, scalable distributed systems.

  • Event Sourcing with snapshots
  • CQRS command/query buses
  • Saga orchestration
  • Circuit breaker fault tolerance

  Patterns

---

Architecture Overview

graph TB
    subgraph Clients["Clients"]
        Browser["Browser / Mobile"]
        Service["Service-to-Service"]
        Queue["Message Queue"]
    end

    subgraph LB["Load Balancer / Ingress"]
        Ingress["Kubernetes Ingress<br/>or Reverse Proxy"]
    end

    subgraph Cello["Cello Application Cluster"]
        direction TB

        subgraph Worker1["Worker 1"]
            MW1["Middleware Pipeline"]
            RT1["Radix Router"]
            HN1["Handlers"]
        end

        subgraph Worker2["Worker 2"]
            MW2["Middleware Pipeline"]
            RT2["Radix Router"]
            HN2["Handlers"]
        end

        subgraph WorkerN["Worker N"]
            MWN["Middleware Pipeline"]
            RTN["Radix Router"]
            HNN["Handlers"]
        end

        subgraph Shared["Shared Components"]
            OTEL["OpenTelemetry<br/>Tracing & Metrics"]
            Health["Health Checks<br/>/health /ready /live"]
            Prom["Prometheus<br/>/metrics"]
        end
    end

    subgraph Data["Data Layer"]
        DB[("PostgreSQL<br/>Connection Pool")]
        Redis[("Redis<br/>Cache & Pub/Sub")]
        Kafka["Kafka / RabbitMQ<br/>Message Broker"]
    end

    subgraph Observability["Observability Stack"]
        Jaeger["Jaeger / Zipkin"]
        Grafana["Grafana"]
        AlertManager["AlertManager"]
    end

    Browser --> Ingress
    Service --> Ingress
    Queue --> Kafka

    Ingress --> Worker1
    Ingress --> Worker2
    Ingress --> WorkerN

    HN1 --> DB
    HN1 --> Redis
    HN1 --> Kafka
    HN2 --> DB
    HN2 --> Redis
    HNN --> DB
    HNN --> Redis

    OTEL --> Jaeger
    Prom --> Grafana
    Grafana --> AlertManager

    style Cello fill:#1a1a2e,stroke:#ff9100,stroke-width:2px
    style Data fill:#16213e,stroke:#ff9100,stroke-width:1px
    style Observability fill:#0f3460,stroke:#ff9100,stroke-width:1px

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Feature Highlights

OpenTelemetry Health Checks Database Pooling GraphQL Message Queues

Distributed tracing with OpenTelemetry

from cello import App
from cello.enterprise import OpenTelemetryConfig

app = App(name="order-service")

# Auto-instrument all routes with distributed tracing
app.enable_telemetry(OpenTelemetryConfig(
    service_name="order-service",
    exporter="otlp",
    endpoint="http://jaeger:4317",
    sample_rate=0.1,  # Sample 10% of traces in production
    propagators=["tracecontext", "baggage"]
))

@app.get("/orders/{id}")
async def get_order(request):
    # Spans are auto-created for each request
    # Trace context propagates across service boundaries
    order = await db.fetch_one("SELECT * FROM orders WHERE id = $1",
                               request.params["id"])
    return order

Kubernetes-ready health probes

from cello import App
from cello.enterprise import HealthCheck

app = App()

# Register health checks for dependencies
health = HealthCheck()
health.add_check("database", check_database_connection)
health.add_check("redis", check_redis_connection)
health.add_check("kafka", check_kafka_connection)

app.enable_health_checks(health)
# GET /health  -> overall status
# GET /ready   -> readiness (all checks pass)
# GET /live    -> liveness (process is running)

Async connection pool with transactions

from cello import App
from cello.enterprise import Database

app = App()
db = Database(
    url="postgresql://localhost/mydb",
    pool_size=20,
    max_overflow=10,
    pool_timeout=30,
    health_check_interval=60
)

@app.post("/orders")
async def create_order(request):
    data = request.json()
    async with db.transaction() as tx:
        order = await tx.fetch_one(
            "INSERT INTO orders (user_id, total) VALUES ($1, $2) RETURNING *",
            data["user_id"], data["total"]
        )
        for item in data["items"]:
            await tx.execute(
                "INSERT INTO order_items (order_id, product_id, qty) VALUES ($1, $2, $3)",
                order["id"], item["product_id"], item["quantity"]
            )
    return {"order_id": order["id"], "status": "created"}

GraphQL with DataLoader

from cello import App
from cello.enterprise import GraphQL, Schema

app = App()

schema = Schema()

@schema.query("user")
async def resolve_user(info, id: str):
    return await db.fetch_one("SELECT * FROM users WHERE id = $1", id)

@schema.query("users")
async def resolve_users(info, limit: int = 10):
    return await db.fetch_all("SELECT * FROM users LIMIT $1", limit)

@schema.mutation("createUser")
async def create_user(info, name: str, email: str):
    return await db.fetch_one(
        "INSERT INTO users (name, email) VALUES ($1, $2) RETURNING *",
        name, email
    )

app.mount_graphql("/graphql", schema)

Kafka consumer with message routing

from cello import App
from cello.enterprise import Kafka

app = App()
kafka = Kafka(brokers=["localhost:9092"])

@kafka.consumer("orders.created", group="order-processor")
async def handle_order_created(message):
    order = message.value
    # Process the order
    await send_confirmation_email(order["user_id"])
    await update_inventory(order["items"])

@kafka.producer
async def publish_event(topic, event):
    await kafka.send(topic, event)

@app.post("/orders")
async def create_order(request):
    order = request.json()
    saved = await db.save_order(order)
    await publish_event("orders.created", saved)
    return {"order_id": saved["id"]}

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Enterprise Features by Version

timeline
    title Cello Enterprise Feature Timeline
    section Foundation
        v0.4.0 : Cluster Mode
               : TLS/SSL (rustls)
               : HTTP/2 & HTTP/3
               : Security Headers
               : Session Management
    section Monitoring
        v0.5.0 : Prometheus Metrics
               : Request ID Tracing
               : OpenAPI/Swagger
               : RFC 7807 Errors
    section Resilience
        v0.6.0 : Circuit Breaker
               : Smart Caching
               : Adaptive Rate Limiting
    section Observability
        v0.7.0 : OpenTelemetry
               : Health Checks
               : Distributed Tracing
               : Structured Logging
    section Data Layer
        v0.8.0 : Database Pooling
               : Redis Integration
               : Transaction Management
    section Protocols
        v0.9.0 : GraphQL
               : gRPC
               : Kafka & RabbitMQ
               : SQS/SNS
    section Patterns
        v0.10.0 : Event Sourcing
                : CQRS
                : Saga Pattern

---

Enterprise Feature Status

Category	Feature	Status	Version
Security	JWT Authentication		v0.4.0
	RBAC Guards		v0.5.0
	Adaptive Rate Limiting		v0.6.0
	Security Headers (CSP, HSTS)		v0.4.0
	CSRF Protection		v0.4.0
	Session Management		v0.4.0
Observability	Prometheus Metrics		v0.5.0
	Request ID Tracing		v0.4.0
	OpenTelemetry		v0.7.0
	Health Checks		v0.7.0
Scalability	Cluster Mode		v0.4.0
	HTTP/2 & HTTP/3 (QUIC)		v0.4.0
	TLS/SSL (rustls)		v0.4.0
	Circuit Breaker		v0.6.0
Integration	Database Pooling		v0.8.0
	Redis		v0.8.0
	GraphQL		v0.9.0
	gRPC		v0.9.0
	Kafka, RabbitMQ, SQS		v0.9.0
Patterns	Event Sourcing		v0.10.0
	CQRS		v0.10.0
	Saga Pattern		v0.10.0

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Enterprise Documentation

• Observability

  ---

  • OpenTelemetry
  • Distributed Tracing
  • Metrics
  • Health Checks

• Integration

  ---

  • Database
  • Message Queues
  • GraphQL
  • gRPC

• Deployment

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  • Docker
  • Kubernetes
  • Service Mesh

• Roadmap

  ---

  • Enterprise Roadmap

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Enterprise Support

Enterprise Support & Consulting

For enterprise support, custom integrations, and consulting:

• enterprise@cello-framework.dev
• Schedule a Demo
• Enterprise Licensing