Modern Architecture Patterns (2024+)

AI/ML Integration Patterns

Model Serving Architecture

apiVersion: serving.kubeflow.org/v1beta1
kind: InferenceService
metadata:
  name: llm-service
spec:
  predictor:
    model:
      modelFormat:
        name: pytorch
      storage:
        path: s3://models/llm
        key: model.pt
      framework:
        name: pytorch
        version: "2.1"

Edge Computing Patterns

Distributed Edge

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: edge-agent
spec:
  selector:
    matchLabels:
      app: edge-compute
  template:
    spec:
      containers:
      - name: edge-runtime
        image: edge-runtime:latest
        resources:
          limits:
            memory: 512Mi
            cpu: "1"

Event-Driven Architecture

Event Mesh Configuration

apiVersion: eventing.knative.dev/v1
kind: Broker
metadata:
  name: event-mesh
spec:
  config:
    apiVersion: v1
    kind: ConfigMap
    name: kafka-broker-config
---
apiVersion: sources.knative.dev/v1
kind: KafkaSource
metadata:
  name: kafka-source
spec:
  topics:
  - events.input
  bootstrapServers:
  - kafka:9092
  sink:
    ref:
      apiVersion: eventing.knative.dev/v1
      kind: Broker
      name: event-mesh

Best Practices

1. Scalability
   • Horizontal scaling
   • Load distribution
   • Resource optimization
   • State management
2. Resilience
   • Circuit breaking
   • Retry patterns
   • Fallback strategies
   • Health monitoring
3. Security
   • Zero trust
   • Service mesh
   • Identity management
   • Access control
4. Observability
   • Distributed tracing
   • Metrics collection
   • Log aggregation
   • Performance analysis