Use Cases

Description

Run backups on a schedule to reduce human error and ensure critical data is always protected.

Who is it for?

• Sysadmins
• DBAs
• Ops engineers
• Anyone who needs regular backups

Steps

1. Choose source & destination
2. Set a schedule
3. Pick full/incremental strategy
4. Define retention
5. Enable and monitor

Example config

task:
  name: "数据备份"
  schedule: "0 2 * * *"  # 每天凌晨2点
  action:
    type: "backup"
    source: "/data/important"
    destination: "/backup/daily"
    compression: true
    retention: 30  # 保留30天

Expected outcome

• Hands-off scheduled backups
• Lower risk of data loss
• Save time and effort
• Traceable history

Description

Watch a folder for new or modified files and automatically convert, compress, or move them.

Who is it for?

• Content admins
• Workflow builders
• Media teams
• Automation users

Steps

1. Set watch path
2. Select events
3. Define rules
4. Choose post-actions
5. Start the watcher

Example config

task:
  name: "文件监控处理"
  watch:
    path: "/uploads"
    recursive: true
    events: ["create", "modify"]
    filters:
      extensions: [".jpg", ".png", ".pdf"]
  action:
    type: "process"
    steps:
      - type: "convert"
        format: "webp"
      - type: "move"
        destination: "/processed"

Expected outcome

• Real-time processing
• Less manual work
• Consistent outputs
• Higher throughput

Description

Keep systems in sync by periodically pulling from APIs or databases and writing to your destination.

Who is it for?

• Developers
• DevOps engineers
• Analysts
• Teams with multi-system data

Steps

1. Configure source
2. Configure destination
3. Set interval
4. Transform if needed
5. Add retries
6. Enable

Example config

task:
  name: "API数据同步"
  schedule: "*/15 * * * *"  # 每15分钟
  action:
    type: "sync"
    source:
      type: "api"
      url: "https://api.example.com/data"
      method: "GET"
      headers:
        Authorization: "Bearer ${API_TOKEN}"
    destination:
      type: "database"
      connection: "postgresql://localhost/db"
      table: "synced_data"

Expected outcome

• Always-fresh data
• Fewer inconsistencies
• Better accuracy
• Less operational toil

Description

Check CPU/memory/disk on a schedule and send alerts (or take action) when thresholds are exceeded.

Who is it for?

• Ops engineers
• Admins
• DevOps teams
• Anyone monitoring servers

Steps

1. Pick metrics
2. Set thresholds
3. Configure notifications
4. Define actions (optional)
5. Enable monitoring

Example config

task:
  name: "系统监控"
  schedule: "*/5 * * * *"  # 每5分钟检查
  action:
    type: "monitor"
    metrics:
      - name: "cpu_usage"
        threshold: 80
      - name: "memory_usage"
        threshold: 85
      - name: "disk_usage"
        threshold: 90
    alerts:
      - type: "email"
        recipients: ["admin@example.com"]
      - type: "webhook"
        url: "https://hooks.example.com/alert"

Expected outcome

• Catch issues early
• Automatic notifications
• Less downtime
• Improved stability