Today we’re excited to announce the RapidML-ReadyAPI-plugin, bridging SmartBear’s powerful testing and virtualization with RAPID-ML’s domain-driven API modeling. Together, these technologies extend API quality across the full lifecycle.
What’s the ROI on Your API?
At RepreZen, we talk about Integration ROI. Companies typically spend 20-30% of their IT budget on integration, and it's trending upward because of ongoing investments in digital, omnichannel, mobility, SaaS and microservices, all integration-intensive trends.
So we look at integration strategies, practices and technologies as an investment. Are we getting the ROI we expect for all these billions spent on integration? What's the full lifecycle cost and lifecycle value of an API that we build for internal or external integration?
API quality, in the broad sense, is almost synonymous with ROI. A high-quality API:
- provides high-value data and functionality that meets real needs or unlocks compelling opportunities;
- has a low integration cost because client integration is facilitated by a lucid, consistent API design, great documentation, interactive tooling and client SDKs, all wrapped into a smooth, developer-friendly onboarding experience;
- has low operational and support overhead because it's thoroughly tested in all aspects, and instrumented for reliability; and
- generates business value because it's highly adopted by client developers, for all of the above reasons.
Client Integration: API Quality in Context
API Clients -- the web apps, mobile apps and higher-level services at the edge of the API ecosystem -- are the real value in our value chain. So whether we're talking about internal, client-facing, or public APIs, high ROI means optimizing the full lifecycle, especially client integration, where the overall cost and value are concentrated.
RAPID-ML is an API description language that embraces an essential but often overlooked truth: Client developers use APIs in combination, not in isolation. No API is an island, and we can’t fully optimize API design quality without looking at the context in which it’s used.
Domain-Driven Design gives us the framework for interoperability:
- Identify a bounded context where we plan to provide a family of highly interoperable services. This could be a microservices architecture; an enterprise, or an entire industry.
- Formalize key concepts and relationships as a domain model. This should be natural to users, and may borrow familiar terminology and data structures from other systems well-known in that context.
- Align data representations, code, product documentation and team communication to the domain model, forming a ubiquitous language.
RAPID-ML incorporates these principles directly into API design, providing a powerful leverage point for API design quality. When all of your APIs “speak the same language,” clients don’t need to translate data structures across APIs. APIs are easier to comprehend, and faster to integrate.
From Design Quality to Production Ready
RAPID-ML introduces a holistic approach to API design quality. RepreZen API Studio provides a complete RAPID-ML design environment with advanced code gen, documentation, full integration with Swagger tooling and the OpenAPI ecosystem. But up until now, RAPID-ML users haven’t had a comprehensive QA solution.
That’s why we’re thrilled to partner with SmartBear on the RapidML-ReadyAPI-Plugin. Now you can import RAPID-ML API descriptions directly into Ready! API, for powerful virtualization and comprehensive API testing. You can even export from Ready! API’s other supported formats into RAPID-ML for editing, visualization and code gen in RepreZen API Studio.
API quality is a journey that starts with design in context, understanding how client developers use APIs in combination to create value. With Ready! API, quality continues through implementation, ensuring that APIs meet functional, security and performance requirements at scale. Ultimately, this is a journey to positive ROI – “Return On Integration,” to coin a phrase. Full-lifecycle API quality gets you there.