
关于
迁移监控、变更数据捕获(CDC)和可观测性基础设施,确保数据库迁移过程的可见性和安全性。
name: database-migrations-migration-observability description: "迁移监控、CDC 和可观测性基础设施" risk: unknown source: community tags: "database, cdc, debezium, kafka, prometheus, grafana, monitoring" date_added: "2026-02-27"
迁移可观测性与实时监控
你是一位数据库可观测性专家,专注于变更数据捕获(CDC)、实时迁移监控和企业级可观测性基础设施。为数据库迁移创建包含 CDC 管道、异常检测和自动告警的综合监控方案。
适用场景
- 处理迁移可观测性和实时监控相关的任务或工作流
- 需要迁移可观测性和实时监控的指导、最佳实践或检查清单
不适用场景
- 任务与迁移可观测性和实时监控无关
- 需要此范围之外的其他领域或工具
上下文
用户需要数据库迁移的可观测性基础设施,包括通过 CDC 实现实时数据同步、全面的指标采集、告警系统和可视化仪表板。
需求
$ARGUMENTS
操作指南
1. 可观测的 MongoDB 迁移
const { MongoClient } = require('mongodb');
const { createLogger, transports } = require('winston');
const prometheus = require('prom-client');
class ObservableAtlasMigration {
constructor(connectionString) {
this.client = new MongoClient(connectionString);
this.logger = createLogger({
transports: [
new transports.File({ filename: 'migrations.log' }),
new transports.Console()
]
});
this.metrics = this.setupMetrics();
}
setupMetrics() {
const register = new prometheus.Registry();
return {
migrationDuration: new prometheus.Histogram({
name: 'mongodb_migration_duration_seconds',
help: 'Duration of MongoDB migrations',
labelNames: ['version', 'status'],
buckets: [1, 5, 15, 30, 60, 300],
registers: [register]
}),
documentsProcessed: new prometheus.Counter({
name: 'mongodb_migration_documents_total',
help: 'Total documents processed',
labelNames: ['version', 'collection'],
registers: [register]
}),
migrationErrors: new prometheus.Counter({
name: 'mongodb_migration_errors_total',
help: 'Total migration errors',
labelNames: ['version', 'error_type'],
registers: [register]
}),
register
};
}
async migrate() {
await this.client.connect();
const db = this.client.db();
for (const [version, migration] of this.migrations) {
await this.executeMigrationWithObservability(db, version, migration);
}
}
async executeMigrationWithObservability(db, version, migration) {
const timer = this.metrics.migrationDuration.startTimer({ version });
const session = this.client.startSession();
try {
this.logger.info(`Starting migration ${version}`);
await session.withTransaction(async () => {
await migration.up(db, session, (collection, count) => {
this.metrics.documentsProcessed.inc({
version,
collection
}, count);
});
});
timer({ status: 'success' });
this.logger.info(`Migration ${version} completed`);
} catch (error) {
this.metrics.migrationErrors.inc({
version,
error_type: error.name
});
timer({ status: 'failed' });
throw error;
} finally {
await session.endSession();
}
}
}
2. 使用 Debezium 进行变更数据捕获
import asyncio
import json
from kafka import KafkaConsumer, KafkaProducer
from prometheus_client import Counter, Histogram, Gauge
from datetime import datetime
class CDCObservabilityManager:
def __init__(self, config):
self.config = config
self.metrics = self.setup_metrics()
def setup_metrics(self):
return {
'events_processed': Counter(
'cdc_events_processed_total',
'Total CDC events processed',
['source', 'table', 'operation']
),
'consumer_lag': Gauge(
'cdc_consumer_lag_messages',
'Consumer lag in messages',
['topic', 'partition']
),
'replication_lag': Gauge(
'cdc_replication_lag_seconds',
'Replication lag',
['source_table', 'target_table']
)
}
async def consume_cdc_events(self):
consumer = KafkaConsumer(
self.config['topic'],
bootstrap_servers=self.config['kafka_brokers'],
value_deserializer=lambda m: json.loads(m.decode('utf-8'))
)
for message in consumer:
event = message.value
self.metrics['events_processed'].labels(
source=event.get('source', 'unknown'),
table=event.get('table', 'unknown'),
operation=event.get('op', 'unknown')
).inc()
lag = (datetime.now() - datetime.fromtimestamp(
event.get('ts_ms', 0) / 1000
)).total_seconds()
self.metrics['replication_lag'].labels(
source_table=event.get('table', 'unknown'),
target_table=event.get('target', 'unknown')
).set(lag)
兼容工具
Claude CodeCursor
标签
运维部署

