Cdc Pattern Implementer

---
name: CDC Pattern Implementer
description: Implements Change Data Capture patterns for real-time data integration
version: 1.0.0
category: Data Integration
skillId: SK-DEA-013
allowed-tools:
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - Bash
graph:
  domains: [domain:data-engineering]
  specializations: [specialization:data-engineering-analytics]
  skillAreas: [skill-area:streaming-realtime-processing, skill-area:etl-pipelines]
  roles: [role:data-engineer, role:analytics-engineer]
  workflows: [workflow:data-pipeline-deployment]
  topics: [topic:event-sourcing]
---

# CDC Pattern Implementer

## Overview

Implements Change Data Capture patterns for real-time data integration. This skill provides expertise in CDC configuration and implementation across various database and streaming platforms.

## Capabilities

- Debezium connector configuration
- CDC pattern selection (log-based, trigger-based, timestamp-based)
- Initial snapshot strategy
- Schema change handling
- Exactly-once delivery configuration
- Sink connector setup
- Tombstone handling
- CDC monitoring setup

## Input Schema

```json
{
  "sourceDatabase": {
    "type": "postgres|mysql|oracle|sqlserver",
    "connection": "object"
  },
  "tables": ["string"],
  "targetSystem": "kafka|kinesis|pubsub",
  "requirements": {
    "latencyMs": "number",
    "exactlyOnce": "boolean"
  }
}
```

## Output Schema

```json
{
  "connectorConfig": "object",
  "snapshotStrategy": "object",
  "schemaConfig": "object",
  "monitoringConfig": "object",
  "documentation": "string"
}
```

## Target Processes

- ETL/ELT Pipeline
- Streaming Pipeline
- Data Warehouse Setup

## Usage Guidelines

1. Identify source database and tables for CDC
2. Define target streaming system
3. Specify latency and delivery guarantees
4. Configure appropriate snapshot strategy for initial load

## Best Practices

- Use log-based CDC when possible for minimal source impact
- Plan initial snapshot strategy carefully for large tables
- Implement proper error handling and dead letter queues
- Monitor replication lag and connector health
- Test schema evolution handling before production