Reference patterns for reliable enterprise integration, workflow automation, and system-of-record synchronization.
Project description
integration-automation-patterns
Practical patterns for enterprise integration, workflow orchestration, and system-of-record synchronization in complex operating environments.
Why this repo exists
Enterprise modernization usually breaks down at the integration layer:
- brittle handoffs between systems
- inconsistent event handling
- weak retry and idempotency models
- workflow logic scattered across tools
- poor visibility into operational state
This repository is a public-safe reference for patterns that help teams build more reliable integration and automation systems. The patterns are platform-agnostic and cloud-agnostic — applicable across any combination of CRM, ERP, ITSM, and custom services, on any cloud environment (AWS, GCP, Azure, OCI) or on-premises.
Scope
This repo focuses on:
- event-driven integration patterns with explicit retry and idempotency models
- system-of-record synchronization with authority boundaries
- workflow orchestration and escalation boundaries
- observability for automation flows
- public-safe architecture notes for enterprise operations
The patterns do not assume any specific vendor, broker, or cloud platform.
Modules
Core reliability:
event_envelope.py— reliable event transport with explicit delivery status, bounded retry, and audit logging. Works with any broker (Kafka, SQS, Azure Service Bus, GCP Pub/Sub, RabbitMQ).sync_boundary.py— bi-directional system-of-record sync with field-level authority assignment, conflict detection, and exclusion management.
Resilience patterns (v0.2.0):
circuit_breaker.py— thread-safe CLOSED/OPEN/HALF_OPEN state machine with automatic recovery probing and.calldecorator.saga.py— distributed saga orchestrator: forward execution with automatic backward compensation on failure, fluent.add_step()API.
Messaging patterns (v0.2.0):
outbox.py— transactional outbox for at-least-once delivery: write events in the same DB transaction, relay separately.kafka_envelope.py— Kafka-aware envelope: partition key routing, schema version, DLQ routing, producer/consumer roundtrip serialization.webhook_handler.py— HMAC-SHA256 webhook verification compatible with GitHub, Stripe, Salesforce, and ServiceNow signature formats.
Change Data Capture (v0.2.0):
cdc_event.py— typed CDC event envelope: INSERT/UPDATE/DELETE/SNAPSHOT/TRUNCATE, Debezium format parsing, changed-field diff, audit dict.
Ecosystem
See ECOSYSTEM.md for full broker, connector, and framework coverage matrix.
Repository structure
src/integration_automation_patterns/
├── event_envelope.py # Reliable event transport + retry
├── sync_boundary.py # Bi-directional SOR sync
├── circuit_breaker.py # CLOSED/OPEN/HALF_OPEN state machine
├── saga.py # Distributed saga orchestrator
├── outbox.py # Transactional outbox pattern
├── kafka_envelope.py # Kafka-aware event envelope
├── webhook_handler.py # HMAC-SHA256 webhook verification
└── cdc_event.py # Change Data Capture event types
docs/
├── architecture.md
├── implementation-note-01.md
├── implementation-note-02.md
└── adr/
Published notes
docs/implementation-note-01.md— event-driven integration reliabilitydocs/implementation-note-02.md— idempotency in enterprise event processing
Intended audience
- enterprise architects
- integration engineers
- workflow and automation operators
- platform teams responsible for system-of-record reliability across CRM, ERP, and service platforms
Citing this work
If you use these patterns in your work, see CITATION.cff or use GitHub's "Cite this repository" button above.
Part of the enterprise AI patterns trilogy
| Library | Focus | Regulation |
|---|---|---|
| enterprise-rag-patterns | What to retrieve | FERPA identity-scoped RAG |
| regulated-ai-governance | What agents may do | FERPA, HIPAA, GLBA policy enforcement |
| integration-automation-patterns | How data flows | Event-driven enterprise integration |
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