Retailers who have successfully adapted have one thing in common: they have implemented loosely coupled or decoupled IT infrastructure, such as headless content management systems (CMS). When a customer requests a change, retailers have greater
Retailers who have successfully adapted have one thing in common: they have implemented loosely coupled or decoupled IT infrastructure, such as headless content management systems (CMS).
When a customer requests a change, retailers have greater flexibility and can introduce new services and update existing applications faster and easier than relying on inflexible monolithic IT systems.
However, delivering a more engaging user experience comes with a catch: as technical complexity increases, so does the need for robust software testing.
Headless commerce needs comprehensive testing for customer experience success
Headless architecture and microservices interoperate with various layers of technologies and applications, so comprehensive testing is essential if retailers are to deliver an experience that builds customer loyalty. These different layers include:
- Data base
- Application Programming Interfaces (APIs)
- Web objects or elements
- User interfaces (UI) or presentation layer
Through these layers, many communication paths between the backend and various user interfaces and interactions built with business logic must also be tested to maintain the end user experience.
Testing of APIs, in particular, is essential because they connect all UI elements to backend data sources and business logic. In retail, developers use APIs to connect inventory management and payment systems, CMSs, and customer relationship management platforms to deliver a customer-centric experience.
For headless commerce, APIs connect a single backend to third-party integrations and multiple front ends. For example, if you are using a headless CMS, content stored in the backend can be separated by APIs and simultaneously published to different customer channels. As a result, more unified content can be delivered faster to websites, mobile apps, in-store digital signage, or even smartwatches to deliver an optimized omnichannel experience.
However, interacting with so many different technology layers, systems, and applications makes comprehensive software testing challenging for QA teams.
Full stack testing challenges
Testing many layers of technology requires multiple tools, which quickly becomes a problem. Some teams will have a tool that only tests a specific API call or database layer request to verify data accuracy. For example, in retail, it might be checking stock levels in an inventory management system. Other testers will use a different tool to validate how the UI layer visually represents the API call, such as confirming that the number of jeans in stock is displayed correctly on an e-commerce site. However, if a fault occurs at any layer, the entire data journey will fail, creating an error-strewn user experience.
QA teams should combine testing to verify the correctness of API calls to and from backend systems and validate the correct response through the object layer to the UI. APIs don’t have a graphical user interface, so you need to validate that the visual representation of the end user is correct regardless of the customer touchpoint.
Multiple layers of technology also combine custom business logic, workflows and processes, so any instability can severely affect how a retailer serves their customer, impacting the bottom line.
Implementing multiple tools for each test case is possible, but maintaining scripts quickly becomes an obstacle to optimizing workflows and productivity. Soaring recurring costs and “shelfware” (lack of use due to skill gaps) will also slow software development cycles and increase time to market.
Optimize Full-Stack Testing with Eggplant DAI and Automation Intelligence
Keysight’s Eggplant DAI is a solution that combines multiple layers of technology and tests them together. It orchestrates full-stack testing by creating scenarios that verify API requests from a database through the object layers and validate the visual response at the UI level.
Eggplant DAI simplifies full-stack testing because QA teams only have to manage one layer of code on each technology layer of an application, facilitating fast and reliable software delivery.
Learn how Keysight’s Eggplant DAI can optimize full-stack testing for your organization with this helpful guide.
This article was originally posted by Mike Wagner of Keysight Technologies here.
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