CDC Pattern Implementer
// Implements Change Data Capture patterns for real-time data integration
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updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
nameCDC Pattern Implementer
descriptionImplements Change Data Capture patterns for real-time data integration
version1.0.0
categoryData Integration
skillIdSK-DEA-013
allowed-toolsRead,Write,Edit,Glob,Grep,Bash
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
{
"sourceDatabase": {
"type": "postgres|mysql|oracle|sqlserver",
"connection": "object"
},
"tables": ["string"],
"targetSystem": "kafka|kinesis|pubsub",
"requirements": {
"latencyMs": "number",
"exactlyOnce": "boolean"
}
}
Output Schema
{
"connectorConfig": "object",
"snapshotStrategy": "object",
"schemaConfig": "object",
"monitoringConfig": "object",
"documentation": "string"
}
Target Processes
- ETL/ELT Pipeline
- Streaming Pipeline
- Data Warehouse Setup
Usage Guidelines
- Identify source database and tables for CDC
- Define target streaming system
- Specify latency and delivery guarantees
- 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