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event-driven-architecture

event-driven-architecture

github.com/rade-nugrohoDevelopment1239 installsUpdated 23w ago
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About event-driven-architecture

A skill for designing event-driven integrations across bounded contexts and microservices. It guides decisions on messaging, event contracts, reliability, coordination patterns, and safe operations.

Key features

  1. 01Choose messaging patterns and brokers
  2. 02Model event types and schemas
  3. 03Plan ordering and delivery guarantees
  4. 04Design idempotency and outbox patterns
  5. 05Select choreography, orchestration, or sagas
  6. 06Plan schema governance and replay operations

Use cases

  1. 01Design event integration between services
  2. 02Set event schema compatibility rules
  3. 03Specify handling for retries and duplicate events
  4. 04Plan dead-letter queue replay procedures

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/rade-nugroho/agentic-enteprises-skill --skill event-driven-architecture

After installing, type/event-driven-architecturein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
event_driven_architecture_scope.md
event_sourcing_and_cqrs.md
messaging_patterns_and_brokers.md
orchestration_choreography_sagas.md
reliability_idempotency_outbox.md
schema_governance_operations.md

Details

From the project README

Event-Driven Architecture

When to Use

  • Design event-driven integration between bounded contexts or microservices
  • Choose pub/sub vs point-to-point, topics vs queues, and broker capabilities
  • Model domain events, integration events, and command vs event semantics
  • Apply event sourcing or CQRS at architecture level (not framework tutorials only)
  • Define schemas, compatibility rules, and event schema versioning strategy
  • Specify ordering, partition keys, and delivery guarantees (at-least-once, etc.)
  • Design idempotent consumers, deduplication, and exactly-once tradeoffs
  • Implement transactional outbox or inbox for reliable publish/consume
  • Decide choreography vs orchestration and saga compensation at pattern level
  • Operate dead-letter queues, replay, and stream reprocessing safely
  • Distinguish stream processing (Kafka Streams, Flink) from discrete business events

When NOT to Use

  • Implement microservice code, gRPC/REST APIs, or twelve-factor deployables only → microservices-developer
  • Design enterprise iPaaS hubs, canonical models, B2B partner APIs, or API gateway programs only → enterprise-integration-api-developer
  • Map X12/EDIFACT segments, AS2/VAN, or EDI partner certification → edi-engineer
  • Build generic application features without event/messaging architecture → senior-software-engineer
  • Operate classified air-gapped pipelines, ATO evidence, cleared promotion → classified-software-devsecops-engineer
  • Formulate VRP, MIP, scheduling, or optimization solvers → operations-research-algorithm-developer
  • CI/CD YAML, GitOps, and release automation only → devops
  • Landing zone, VPC, and managed cloud provisioning → cloud-engineer

Related skills

NeedSkill
Service boundaries, gRPC/REST, circuit breakers, contract testsmicroservices-developer
Enterprise integration hub, OpenAPI/AsyncAPI, iPaaS, B2B gatewaysenterprise-integration-api-developer
EDI standards and partner file exchangeedi-engineer
Application code and refactoring without EDA focussenior-software-engineer
Classified DevSecOps and artifact promotionclassified-software-devsecops-engineer
OR models, routing, allocation solversoperations-research-algorithm-developer
Kafka/Rabbit operational platform (brokers, K8s)platform-engineer, devops
Cross-system ADRs and NFR sign-offsenior-system-architecture
Pipeline security and supply chaindevsecops

Core Workflows

1. Scope and event boundaries

Define event types, producers/consumers, sync vs async boundaries, and non-goals.

See references/event_driven_architecture_scope.md.

2. Messaging and brokers

Select patterns, topics/queues, partitioning, and broker fit (Kafka, Pulsar, SNS/SQS, etc.).

See references/messaging_patterns_and_brokers.md.

3. Event sourcing and CQRS

When to use write models, projections, snapshots, and read-model consistency.

See references/event_sourcing_and_cqrs.md.

4. Reliability, idempotency, outbox

Delivery semantics, deduplication, outbox/inbox, and failure handling.

See references/reliability_idempotency_outbox.md.

5. Orchestration, choreography, sagas

Coordinate long-running flows without turning the bus into a distributed monolith.

See references/orchestration_choreography_sagas.md.

6. Schema governance and operations

Version events, operate DLQs, replay, and observability for event pipelines.

See references/schema_governance_operations.md.

Outputs

  • Event catalog — event name, schema version, producer, consumers, SLAs, PII classification
  • Context diagram — services, topics/queues, sync fallbacks, trust zones
  • Consistency note — outbox/saga/choreography choice with compensation and idempotency keys
  • Partitioning and ordering spec — keys, guarantees, hot-partition risks
  • Schema compatibility matrix — backward/forward rules, deprecation timeline
  • Operations runbook — DLQ drain, replay procedure, lag alerts, poison-message handling

Principles

  • Prefer explicit contracts (schemas, AsyncAPI/CloudEvents metadata) over implicit JSON blobs
  • Design consumers idempotent by default; treat exactly-once as a bounded, measured goal
  • Keep commands and events distinct—events are facts; commands request work
  • Avoid chatty orchestration over the bus; sagas compensate, they do not hide missing boundaries
  • Make failure observable—correlation ID, structured errors, DLQ with actionable payloads
  • Replay is a product feature—document ordering, side effects, and deduplication before reprocessing

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