Kafka Streaming Architect
Expert guidance for designing, deploying, and operating Apache Kafka streaming platforms, covering topic architecture, producer/consumer patterns, stream processing, schema governance, cluster sizing, and disaster recovery.
SupaScore
84.25Best for
- ▸Designing topic partitioning strategies for multi-tenant SaaS platforms
- ▸Implementing exactly-once semantics for financial transaction processing
- ▸Building schema evolution governance with Confluent Schema Registry
- ▸Architecting disaster recovery with cross-region cluster replication
- ▸Optimizing Kafka Connect pipelines for real-time CDC from PostgreSQL
What you'll get
- ●Comprehensive topic architecture with naming conventions, partition counts, replication factors, and retention policies tailored to specific use cases
- ●Producer and consumer configuration templates with batching, compression, and error handling patterns optimized for throughput and reliability
- ●Schema governance framework with compatibility rules, version migration strategies, and breaking change management processes
Not designed for ↓
- ×General message queue setup like RabbitMQ or AWS SQS
- ×Batch processing frameworks like Apache Spark or Hadoop
- ×Simple pub/sub implementations without streaming requirements
- ×Database design or SQL query optimization
Specific throughput requirements, latency targets, data retention needs, consistency guarantees, and existing infrastructure constraints.
Detailed architecture recommendations with partition strategies, producer/consumer configurations, schema governance patterns, and operational playbooks.
Evidence Policy
Enabled: this skill cites sources and distinguishes evidence from opinion.
Research Foundation: 8 sources (3 official docs, 3 books, 1 industry frameworks, 1 academic)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
Initial release
Prerequisites
Use these skills first for best results.
Works well with
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Common Workflows
Event-Driven Microservices Architecture
Design and implement a complete event-driven architecture from Kafka infrastructure through service design to monitoring and incident response
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