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Event Processing Specialist

Design and build robust event-driven architectures and stream processing systems — from event modeling and schema design to Kafka/Flink implementation, failure handling, and operational observability at scale.

Gold
v1.0.00 activationsSoftware EngineeringEngineeringexpert

SupaScore

83.8
Research Quality (15%)
8.4
Prompt Engineering (25%)
8.5
Practical Utility (15%)
8.4
Completeness (10%)
8.5
User Satisfaction (20%)
8.2
Decision Usefulness (15%)
8.3

Best for

  • Design Kafka topic partitioning strategy for order processing with strict ordering guarantees
  • Implement exactly-once delivery semantics for financial transaction events across microservices
  • Build CQRS event sourcing architecture for audit-heavy regulatory compliance systems
  • Create dead letter queue handling for failed payment processing events with automatic retry logic
  • Design event schema evolution strategy using Avro for backward compatibility across service versions

What you'll get

  • Complete Kafka topic design with partition key strategy, consumer group configuration, and schema registry setup for specific business domain
  • Event sourcing implementation guide with event store design, projection patterns, and snapshot strategies with code examples
  • Comprehensive failure handling architecture including circuit breakers, dead letter queues, and retry policies with operational runbooks
Not designed for ↓
  • ×Simple request-response API design or synchronous microservices communication
  • ×Batch processing jobs that don't require real-time streaming capabilities
  • ×Basic message queuing for fire-and-forget notifications without ordering requirements
  • ×Traditional database design for CRUD applications without event sourcing needs
Expects

Clear event processing requirements including throughput, latency, ordering guarantees, delivery semantics, and failure scenarios with specific business domain context.

Returns

Detailed event architecture design with schema definitions, infrastructure configuration, failure handling patterns, and operational monitoring recommendations with implementation guidance.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

event-drivenstream-processingkafkaevent-sourcingcqrsdistributed-systemsmessage-brokerflinkcloudeventssaga-patterndead-letter-queuereal-time

Research Foundation: 8 sources (3 books, 3 official docs, 2 industry frameworks)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/16/2026

Initial release

Prerequisites

Use these skills first for best results.

Works well with

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Common Workflows

Event-Driven System Design

Complete workflow from initial event architecture design through implementation to production monitoring and observability

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