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概览
Every enterprise is, in part, an integration problem. Orders, customers, inventory and payments cross dozens of systems, and the connections between them often matter more than any single application. When those connections are point-to-point scripts and shared databases, every change carries hidden risk.
We design APIs as durable products and integrations as observable systems. Contract-first specifications, event-driven architecture where timing allows, and integration patterns with clear ownership give your organization connections that can be versioned, secured, monitored and changed without coordinating every team at once.
业务应用
- 01
Enterprise API platforms
Internal and partner APIs with OpenAPI or GraphQL contracts, gateway policies, developer portals and versioning rules that let consumers integrate without constant coordination between teams.
- 02
Event-driven integration
Replacing batch file transfers and polling with event streams on Kafka or cloud messaging services, so downstream systems react to orders, shipments and payments as they happen.
- 03
Systems-of-record integration
Connecting SAP, Odoo, Dynamics 365, Salesforce, HubSpot and other platforms through an integration layer that handles mapping, retries, idempotency and error queues consistently, instead of each project inventing its own approach.
- 04
Partner and ecosystem connectivity
Exposing secure APIs and webhooks to customers, suppliers and marketplaces, and consuming external payment, logistics and identity services through resilient client patterns with timeouts and circuit breakers.
工程方法
- 01
Integration landscape mapping
We inventory systems, data flows, ownership and failure history to find where integrations are fragile, duplicated or missing, and which flows carry the most business risk.
- 02
Contract-first design
APIs and events are specified in OpenAPI, AsyncAPI or Protocol Buffers before implementation, reviewed with consumers, and governed by explicit versioning and deprecation policies.
- 03
Pattern selection
For each flow we choose synchronous APIs, asynchronous events, change data capture or managed connectors based on latency needs, tolerance for coupling and the capabilities of each system.
- 04
Resilient implementation
Integrations are built with idempotency keys, retries with backoff, dead-letter queues, schema validation and the outbox pattern, so failures are contained and recoverable rather than silent.
- 05
Govern and observe
Gateway policies enforce authentication and rate limits, distributed tracing follows requests across systems, and dashboards show throughput, latency and error queues for every integration.
技术与平台
API design and gateways
- OpenAPI
- GraphQL
- gRPC
- AsyncAPI
- Kong
- AWS API Gateway
- Azure API Management
Event streaming and messaging
- Apache Kafka
- Confluent Schema Registry
- RabbitMQ
- Amazon EventBridge
- Debezium
Integration platforms
- MuleSoft
- Apache Camel
- Azure Logic Apps
- Workato
- Boomi
Security and observability
- OAuth 2.0
- Mutual TLS
- OpenTelemetry
- Jaeger
- Grafana
文中提及的技术名称均为其各自所有者的商标，并不代表任何合作或背书关系。
交付成果
- Integration landscape map with risk and ownership assessment
- API and event contracts in OpenAPI, AsyncAPI or Protocol Buffers
- API gateway configuration with security and rate-limiting policies
- Integration services with retry, idempotency and dead-letter handling
- Developer portal and consumer onboarding documentation
- End-to-end tracing and integration health dashboards
决策者关心的问题
Should we use an iPaaS or build integrations in code?
Both have a place. Managed integration platforms work well for standard SaaS-to-SaaS flows and teams with limited engineering capacity. Custom integration services suit high-volume, latency-sensitive or logic-heavy flows where testing, versioning and performance control matter. Many organizations use a mix, and we help decide which flows belong where.
How do you version APIs without breaking existing consumers?
We favor additive, backward-compatible changes, use contract tests to detect breaking changes before release, and introduce new major versions only when necessary. Deprecation follows a published policy backed by usage monitoring at the gateway, so we know which consumers still depend on an old version before it is retired.
When does event-driven architecture make sense?
When several systems need to react to the same business event, when producers should not depend on consumer availability, or when a durable record of changes has value in itself. It adds operational complexity, so for simple request-response needs a well-designed synchronous API is often the better choice.