---
name: kafka-topic-designer-ea4c289d718b
description: Designs and optimizes Apache Kafka topics and configurations
version: 1.0.0
category: Streaming
skillId: SK-DEA-007
allowed-tools:
  - Read
  - Write
  - Edit
  - Glob
  - Grep
  - Bash
graph:
  domains: [domain:data-engineering]
  specializations: [specialization:data-engineering-analytics]
  skillAreas: [skill-area:messaging-queuing, skill-area:streaming-realtime-processing]
  roles: [role:data-engineer, role:analytics-engineer]
  workflows: [workflow:data-pipeline-deployment]
  topics: [topic:event-sourcing, topic:event-driven-architecture]
---

# Kafka Topic Designer

## Overview

Designs and optimizes Apache Kafka topics and configurations. This skill provides expertise in topic architecture, partitioning strategies, and producer/consumer configuration for optimal streaming performance.

## Capabilities

- Topic naming convention design
- Partition strategy optimization
- Replication factor recommendations
- Retention policy configuration
- Compaction strategy design
- Schema registry integration
- Consumer group design
- Throughput capacity planning
- Security configuration (ACLs, encryption)

## Input Schema

```json
{
  "requirements": {
    "throughputMBps": "number",
    "messageSize": "number",
    "retentionDays": "number",
    "orderingRequirements": "string"
  },
  "existingTopics": ["object"],
  "clusterConfig": "object"
}
```

## Output Schema

```json
{
  "topicDesign": {
    "name": "string",
    "partitions": "number",
    "replicationFactor": "number",
    "configs": "object"
  },
  "schemaDefinition": "object",
  "producerConfig": "object",
  "consumerConfig": "object"
}
```

## Target Processes

- Streaming Pipeline
- ETL/ELT Pipeline (CDC)
- Feature Store Setup

## Usage Guidelines

1. Define throughput and latency requirements
2. Specify message size and retention needs
3. Document ordering requirements (per-partition, global)
4. Include existing topic configurations for consistency

## Best Practices

- Use consistent naming conventions across all topics
- Size partitions based on consumer parallelism needs
- Configure appropriate retention for compliance and replay scenarios
- Implement schema registry for schema evolution
- Set up proper ACLs for security


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Development & Engineering
Roles: Backend Developer, Data Engineer, ML / AI Engineer
Specialties: API, Backend
Tools: Apache Kafka
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 098d94afe01ca688bf200605001dd3caa5714229087986868822893d4119a2ce