Aplikasi moden menuntut kebolehskalaan, kebolehpercayaan dan kebolehselenggaraan. Dalam panduan ini, kami akan meneroka cara mereka bentuk dan melaksanakan seni bina perkhidmatan mikro yang boleh menangani cabaran dunia sebenar sambil mengekalkan kecemerlangan operasi.
Mari kita mulakan dengan prinsip teras yang membimbing seni bina kita:
graph TD A[Service Design Principles] --> B[Single Responsibility] A --> C[Domain-Driven Design] A --> D[API First] A --> E[Event-Driven] A --> F[Infrastructure as Code]
Berikut ialah contoh perkhidmatan mikro yang tersusun dengan baik menggunakan Go:
package main import ( "context" "log" "net/http" "os" "os/signal" "syscall" "time" "github.com/prometheus/client_golang/prometheus" "go.opentelemetry.io/otel" ) // Service configuration type Config struct { Port string ShutdownTimeout time.Duration DatabaseURL string } // Service represents our microservice type Service struct { server *http.Server logger *log.Logger config Config metrics *Metrics } // Metrics for monitoring type Metrics struct { requestDuration *prometheus.HistogramVec requestCount *prometheus.CounterVec errorCount *prometheus.CounterVec } func NewService(cfg Config) *Service { metrics := initializeMetrics() logger := initializeLogger() return &Service{ config: cfg, logger: logger, metrics: metrics, } } func (s *Service) Start() error { // Initialize OpenTelemetry shutdown := initializeTracing() defer shutdown() // Setup HTTP server router := s.setupRoutes() s.server = &http.Server{ Addr: ":" + s.config.Port, Handler: router, } // Graceful shutdown go s.handleShutdown() s.logger.Printf("Starting server on port %s", s.config.Port) return s.server.ListenAndServe() }
Lindungi perkhidmatan anda daripada kegagalan lata:
type CircuitBreaker struct { failureThreshold uint32 resetTimeout time.Duration state uint32 failures uint32 lastFailure time.Time } func NewCircuitBreaker(threshold uint32, timeout time.Duration) *CircuitBreaker { return &CircuitBreaker{ failureThreshold: threshold, resetTimeout: timeout, } } func (cb *CircuitBreaker) Execute(fn func() error) error { if !cb.canExecute() { return errors.New("circuit breaker is open") } err := fn() if err != nil { cb.recordFailure() return err } cb.reset() return nil }
Menggunakan Apache Kafka untuk penstriman acara yang boleh dipercayai:
type EventProcessor struct { consumer *kafka.Consumer producer *kafka.Producer logger *log.Logger } func (ep *EventProcessor) ProcessEvents(ctx context.Context) error { for { select { case <-ctx.Done(): return ctx.Err() default: msg, err := ep.consumer.ReadMessage(ctx) if err != nil { ep.logger.Printf("Error reading message: %v", err) continue } if err := ep.handleEvent(ctx, msg); err != nil { ep.logger.Printf("Error processing message: %v", err) // Handle dead letter queue ep.moveToDeadLetter(msg) } } } }
Menggunakan Terraform untuk pengurusan infrastruktur:
# Define the microservice infrastructure module "microservice" { source = "./modules/microservice" name = "user-service" container_port = 8080 replicas = 3 environment = { KAFKA_BROKERS = var.kafka_brokers DATABASE_URL = var.database_url LOG_LEVEL = "info" } # Configure auto-scaling autoscaling = { min_replicas = 2 max_replicas = 10 metrics = [ { type = "Resource" resource = { name = "cpu" target_average_utilization = 70 } } ] } } # Set up monitoring module "monitoring" { source = "./modules/monitoring" service_name = module.microservice.name alert_email = var.alert_email dashboard = { refresh_interval = "30s" time_range = "6h" } }
Tentukan kontrak API perkhidmatan anda:
openapi: 3.0.3 info: title: User Service API version: 1.0.0 description: User management microservice API paths: /users: post: summary: Create a new user operationId: createUser requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/CreateUserRequest' responses: '201': description: User created successfully content: application/json: schema: $ref: '#/components/schemas/User' '400': $ref: '#/components/responses/BadRequest' '500': $ref: '#/components/responses/InternalError' components: schemas: User: type: object properties: id: type: string format: uuid email: type: string format: email created_at: type: string format: date-time required: - id - email - created_at
Sediakan pemantauan menyeluruh:
# Prometheus configuration scrape_configs: - job_name: 'microservices' kubernetes_sd_configs: - role: pod relabel_configs: - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape] action: keep regex: true # Grafana dashboard { "dashboard": { "panels": [ { "title": "Request Rate", "type": "graph", "datasource": "Prometheus", "targets": [ { "expr": "rate(http_requests_total{service=\"user-service\"}[5m])", "legendFormat": "{{method}} {{path}}" } ] }, { "title": "Error Rate", "type": "graph", "datasource": "Prometheus", "targets": [ { "expr": "rate(http_errors_total{service=\"user-service\"}[5m])", "legendFormat": "{{status_code}}" } ] } ] } }
Laksanakan penggunaan masa sifar masa:
apiVersion: apps/v1 kind: Deployment metadata: name: user-service spec: replicas: 3 strategy: type: RollingUpdate rollingUpdate: maxSurge: 1 maxUnavailable: 0 template: spec: containers: - name: user-service image: user-service:1.0.0 ports: - containerPort: 8080 readinessProbe: httpGet: path: /health port: 8080 initialDelaySeconds: 5 periodSeconds: 10 livenessProbe: httpGet: path: /health port: 8080 initialDelaySeconds: 15 periodSeconds: 20
Membina perkhidmatan mikro yang berdaya tahan memerlukan pertimbangan yang teliti terhadap banyak faktor. Kuncinya ialah:
Apakah cabaran yang telah anda hadapi dalam membina perkhidmatan mikro? Kongsi pengalaman anda dalam komen di bawah!
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