13 KiB
13 KiB
Kiến trúc Khả năng Quan sát / Observability Architecture
VI: Khả năng quan sát toàn diện với metrics, logging và tracing EN: Comprehensive observability with metrics, logging, and tracing
Sơ đồ Tổng quan / Overview Diagram
graph TD
subgraph "Services"
Service1[Service A]
Service2[Service B]
end
subgraph "Metrics"
Service1 -->|/metrics| Prom[Prometheus]
Service2 -->|/metrics| Prom
Prom --> Grafana[Grafana<br/>Dashboards]
end
subgraph "Logging"
Service1 -->|JSON Logs| Loki
Service2 -->|JSON Logs| Loki
Loki --> GrafanaLogs[Grafana<br/>Log Explorer]
end
subgraph "Tracing"
Service1 -->|Spans| Jaeger
Service2 -->|Spans| Jaeger
Jaeger --> JaegerUI[Jaeger UI]
end
style Prom fill:#d4edda
style Loki fill:#fff4e1
style Jaeger fill:#e1f5ff
## Bối cảnh Hệ thống / System Context
```mermaid
C4Context
title Sơ đồ Bối cảnh Khả năng Quan sát / Observability System Context
Person(dev, "Developer", "Uses dashboards to monitor system")
Person(sre, "SRE", "Manages infrastructure & alerts")
System(obs, "Observability Stack", "Prometheus, Loki, Jaeger, Grafana")
System_Ext(service, "Microservices", "Sends telemetry data")
System_Ext(k8s, "Kubernetes", "Sends cluster metrics")
Rel(dev, obs, "Views Dashboards", "HTTPS")
Rel(sre, obs, "Configures Alerts", "HTTPS")
Rel(service, obs, "Push/Pull Telemetry", "HTTP/gRPC")
Rel(k8s, obs, "Exposes Metrics", "HTTP")
VI Mô tả Bối cảnh
- Observability Stack: Trung tâm thu thập và hiển thị dữ liệu (Prometheus, Loki, Jaeger, Grafana).
- Microservices: Gửi logs, metrics và traces (OpenTelemetry).
- Developer/SRE: Sử dụng Grafana để theo dõi sức khỏe hệ thống và debug.
EN Context Description
- Observability Stack: Central collection and visualization (Prometheus, Loki, Jaeger, Grafana).
- Microservices: Send logs, metrics, and traces (OpenTelemetry).
- Developer/SRE: Use Grafana to monitor system health and debug.
Ba Trụ cột Khả năng Quan sát / Three Pillars of Observability
1. Metrics (Prometheus + Grafana)
graph LR
Service[Service] -->|Expose /metrics| Prom[Prometheus]
Prom -->|Scrape every 15s| Metrics[Time Series DB]
Metrics --> Grafana[Grafana]
Grafana --> Dashboard1[Request Dashboard]
Grafana --> Dashboard2[Error Dashboard]
Grafana --> Dashboard3[Performance Dashboard]
style Prom fill:#d4edda
style Grafana fill:#e1f5ff
VI: Các phép đo số theo thời gian (requests/sec, latency, errors).
EN: Numerical measurements over time (requests/sec, latency, errors).
Triển khai / Implementation:
import { Counter, Histogram, Gauge } from 'prom-client';
// VI: HTTP request metrics
// EN: HTTP request metrics
export const httpRequestDuration = new Histogram({
name: 'http_request_duration_seconds',
help: 'Duration of HTTP requests in seconds',
labelNames: ['method', 'route', 'status'],
buckets: [0.001, 0.01, 0.05, 0.1, 0.5, 1, 2, 5]
});
export const httpRequestTotal = new Counter({
name: 'http_requests_total',
help: 'Total HTTP requests',
labelNames: ['method', 'route', 'status']
});
export const activeRequests = new Gauge({
name: 'http_requests_active',
help: 'Number of active HTTP requests'
});
// VI: Middleware để track metrics
// EN: Middleware to track metrics
export function metricsMiddleware(req, res, next) {
const start = Date.now();
activeRequests.inc();
res.on('finish', () => {
const duration = (Date.now() - start) / 1000;
httpRequestDuration.observe(
{ method: req.method, route: req.route?.path || req.path, status: res.statusCode },
duration
);
httpRequestTotal.inc({
method: req.method,
route: req.route?.path || req.path,
status: res.statusCode
});
activeRequests.dec();
});
next();
}
2. Logging (Winston + Loki)
sequenceDiagram
participant Service
participant Winston as Winston Logger
participant Loki
participant Grafana
Service->>Winston: Log event
Winston->>Winston: Format JSON
Winston->>Winston: Add metadata<br/>(correlation ID, trace ID)
Winston->>Loki: Push logs
Loki->>Loki: Index & store
User->>Grafana: Query logs
Grafana->>Loki: LogQL query
Loki-->>Grafana: Log results
VI: Structured logging với correlation IDs để tracing requests.
EN: Structured logging with correlation IDs for request tracing.
Triển khai / Implementation:
import winston from 'winston';
export const logger = winston.createLogger({
level: process.env.LOG_LEVEL || 'info',
format: winston.format.combine(
winston.format.timestamp(),
winston.format.errors({ stack: true }),
winston.format.json()
),
defaultMeta: {
service: process.env.SERVICE_NAME || 'unknown-service',
environment: process.env.NODE_ENV || 'development'
},
transports: [
new winston.transports.Console(),
// VI: Loki transport (nếu configured)
// EN: Loki transport (if configured)
]
});
// VI: Logger middleware
// EN: Logger middleware
export function loggerMiddleware(req, res, next) {
const correlationId = req.headers['x-correlation-id'] || generateId();
req.correlationId = correlationId;
req.logger = logger.child({ correlationId });
req.logger.info('Incoming request', {
method: req.method,
path: req.path,
ip: req.ip
});
res.on('finish', () => {
req.logger.info('Request completed', {
method: req.method,
path: req.path,
status: res.statusCode,
duration: Date.now() - req.startTime
});
});
next();
}
3. Tracing (OpenTelemetry + Jaeger)
graph LR
Request[Incoming Request] --> Trace[Create Trace]
Trace --> SpanA[Span: HTTP Request]
SpanA --> SpanB[Span: DB Query]
SpanA --> SpanC[Span: Cache Check]
SpanA --> SpanD[Span: External API]
SpanB --> Jaeger[Jaeger]
SpanC --> Jaeger
SpanD --> Jaeger
Jaeger --> Timeline[Trace Timeline]
style Trace fill:#e1f5ff
style Jaeger fill:#d4edda
VI: Distributed tracing để track requests giữa các services.
EN: Distributed tracing to track requests across services.
Triển khai / Implementation:
import { trace, SpanStatusCode } from '@opentelemetry/api';
// VI: Tạo traced function
// EN: Create traced function
export function traced<T>(
name: string,
fn: () => Promise<T>
): Promise<T> {
const tracer = trace.getTracer('app');
const span = tracer.startSpan(name);
return fn()
.then(result => {
span.setStatus({ code: SpanStatusCode.OK });
return result;
})
.catch(error => {
span.setStatus({
code: SpanStatusCode.ERROR,
message: error.message
});
span.recordException(error);
throw error;
})
.finally(() => {
span.end();
});
}
// VI: Sử dụng
// EN: Usage
async getUserWithTracing(userId: string): Promise<User> {
return traced('getUserById', async () => {
return await userRepository.findById(userId);
});
}
Kiểm tra Sức khỏe / Health Checks
// VI: Liveness probe - service có đang chạy không?
// EN: Liveness probe - is service running?
app.get('/health/live', (req, res) => {
res.json({ status: 'ok', timestamp: new Date().toISOString() });
});
// VI: Readiness probe - service có sẵn sàng nhận traffic không?
// EN: Readiness probe - is service ready for traffic?
app.get('/health/ready', async (req, res) => {
const checks = {
database: await checkDatabase(),
redis: await checkRedis(),
disk: await checkDiskSpace()
};
const ready = Object.values(checks).every(check => check === true);
res.status(ready ? 200 : 503).json({
ready,
checks,
timestamp: new Date().toISOString()
});
});
async function checkDatabase(): Promise<boolean> {
try {
await prisma.$queryRaw`SELECT 1`;
return true;
} catch {
return false;
}
}
Quy tắc Cảnh báo / Alerting Rules
# VI: Prometheus alerting rules
# EN: Prometheus alerting rules
groups:
- name: service_alerts
interval: 30s
rules:
# VI: Tỷ lệ lỗi cao
# EN: High error rate
- alert: HighErrorRate
expr: |
rate(http_requests_total{status=~"5.."}[5m]) > 0.05
for: 2m
labels:
severity: warning
annotations:
summary: "High error rate detected"
description: "Error rate is {{ $value }} (> 5%)"
# VI: Độ trễ cao
# EN: High latency
- alert: HighLatency
expr: |
histogram_quantile(0.95, http_request_duration_seconds_bucket) > 1
for: 5m
labels:
severity: warning
annotations:
summary: "High latency detected"
description: "P95 latency is {{ $value }}s"
# VI: Service down
# EN: Service down
- alert: ServiceDown
expr: up == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Service is down"
Đặc điểm Hiệu suất / Performance Characteristics
VI: Mục tiêu Hiệu suất
| Chỉ số / Metric | Mục tiêu / Target | Ghi chú / Notes |
|---|---|---|
| Metric Scrape Interval | 15s | Critical services |
| Log Ingestion Latency | < 1s | Time from emit to queryable |
| Trace Sampling Rate | 10% | Production (100% in Dev/Staging) |
| Dashboard Load Time | < 2s | P95 Latency |
| Alert Evaluation | Every 1m | Evaluation interval |
| Retention Policy | 14 days | Logs & Traces (Metrics: 30 days) |
EN: Performance Targets
| Metric | Target | Notes |
|---|---|---|
| Metric Scrape Interval | 15s | Critical services |
| Log Ingestion Latency | < 1s | Time from emit to queryable |
| Trace Sampling Rate | 10% | Production (100% in Dev/Staging) |
| Dashboard Load Time | < 2s | P95 Latency |
| Alert Evaluation | Every 1m | Evaluation interval |
| Retention Policy | 14 days | Logs & Traces (Metrics: 30 days) |
Cân nhắc Bảo mật / Security Considerations
VI: Bảo mật Observability
- Log Scrubbing: Tự động loại bỏ PII (emails, ssn, credit cards) và secrets khỏi logs trước khi ingestion.
- Access Control: Grafana integrated với OAuth2/OIDC, phân quyền Viewer/Editor/Admin.
- Network Policy: Chỉ cho phép traffic từ namespace nội bộ tới các cổng ingestion (9090, 3100, 14268).
- TLS: Mã hóa traffic giữa agents và collectors.
EN: Observability Security
- Log Scrubbing: Automatically scrub PII (emails, ssn, credit cards) and secrets from logs before ingestion.
- Access Control: Grafana integrated with OAuth2/OIDC, roles for Viewer/Editor/Admin.
- Network Policy: Allow traffic only from internal namespaces to ingestion ports (9090, 3100, 14268).
- TLS: Encrypt traffic between agents and collectors.
Triển khai / Deployment
graph TD
subgraph "Kubernetes Monitoring Namespace"
Grafana[Grafana]
Prom[Prometheus Server]
Loki[Loki Gateway]
Jaeger[Jaeger Collector]
end
subgraph "App Namespace"
App[Application Pods]
Agent[Grafana Agent / Promtail]
end
App -->|Push Logs| Agent
Agent -->|Push| Loki
Prom -->|Pull Metrics| App
Prom -->|Pull Metrics| Agent
App -->|Push Traces| Jaeger
Grafana --> Prom
Grafana --> Loki
Grafana --> Jaeger
style Grafana fill:#ffe1e1
style Prom fill:#d4edda
style Loki fill:#fff4e1
style Jaeger fill:#e1f5ff
VI Mô tả Triển khai:
- Agent: Promtail hoặc Grafana Agent chạy như DaemonSet hoặc Sidecar để thu thập logs.
- Pull Model: Prometheus scrape metrics từ endpoints
/metrics. - Push Model: Traces và Logs được push tới collectors.
- Resources: Dedicated nodes cho monitoring stack trong production để tránh ảnh hưởng workload chính.
EN Deployment Description:
- Agent: Promtail or Grafana Agent runs as DaemonSet or Sidecar to collect logs.
- Pull Model: Prometheus scrapes metrics from
/metricsendpoints. - Push Model: Traces and Logs are pushed to collectors.
- Resources: Dedicated nodes for monitoring stack in production to prevent impact on main workload.
Tài liệu Liên quan / Related Documentation
- System Design - Kiến trúc tổng thể / Overall architecture
- Caching Architecture - Cache metrics
Cập nhật Lần cuối / Last Updated: 2026-01-07
Tác giả / Authors: GoodGo Architecture Team