5 API Testing Roadblocks You Can Overcome With Virtual APIs
5 API Testing Roadblocks You Can Overcome With Virtual APIs
Today's software architecture relies on APIs as core to the application in much the same way as a database or user interface are considered core components to the architecture.
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Today’s software architecture relies on APIs as core to the application in much the same way as a database or user interface are considered core components to the architecture.
That reliance on APIs means that application testers have to test the application’s reaction to a variety of API responses. This can be a problem, especially when those APIs are still in development or are developed by a third party.
This is where API virtualization comes in.
Virtual APIs create an environment that testers can use to mimic the characteristics of the production environment and create simulated responses from all APIs the application relies on.
Instead of setting up a whole separate server stack to mimic production, API virtualization aims to simulate the minimum behaviors of one or more API endpoints.
With API virtualization, your development teams can create virtual APIs instead of production APIs, enabling frequent and comprehensive testing even when the API is still in the midst of being developed.
How can using virtual APIs help your team? Let’s take a look at five common API testing challenges:
1. Testing of APIs comes too late in the software development lifecycle
Solution: Enable parallel development with API virtualization
Running virtual services removes dependencies on external APIs during your application development lifecycle and allows you to validate your API model by virtualizing its actions before and during coding.
By virtualizing APIs that are still being developed, you can get ahead of the game by creating functional tests and/or performance tests against that API, so that you’ll be ready to hit the ground running as soon as the API is completed. Parallel development allows for continuous testing and feedback for dev to understand whether or not an API is meeting requirements and if there are defects early on.
2. Cross-team API dependencies slow release schedule
Solution: Isolate dev/testing teams from frequent changes as real APIs are developed.
By providing teams with virtual versions of an API, you eliminate the dependencies that can slow down the software delivery lifecycle. While teams still need to collaborate and work on a schedule, they won’t be hindered when changes or delays occur.
Prototyping an API that is still being developed will also allow you to test any dependent APIs and integrations that API supports, so that you can be ready for any bugs or issues that might arise with the new API when it becomes available.
3. Third-party vendor services are unable to scale for performance testing
Solution: Run performance tests against a virtual API, instead of a third-party service
Particularly in regression and load testing, relying on third party APIs can incur fees well beyond established budget constraints. As important as these types of testing methods are, without API virtualization, there is no way to perform these tests without either hitting rate limits or incurring overage fees.
Some third parties don’t even automatically cut off clients who exceed their limit, resulting in an unanticipated explosion in cost to the client at the end of the billing cycle. Virtualization of these external APIs is the easiest and fastest way to avoid these situations.
4. Environment instability leads to less time testing
Solution: Set up a virtual API sandbox
A virtual “API sandbox” mimics the characteristics of the production environment and creates simulated responses from all APIs an application relies on. The application under test still uses the same calls as before but points to the virtual API, which makes it possible to perform specific tests by simulating environment conditions or API responses.
API virtualization makes it possible to test an API in isolation, gauging the reaction against real data, under a variety of load conditions. This allows testing teams to conduct load tests repeatedly until the API demonstrates that it can perform under the strain of the desired number of concurrent users — no production system required or harmed.
5. Data creation takes too much developer/tester time
API virtualization allows you to re-execute tests without having to redo a complete data setup. A tool like ServiceV, enables you to generate dynamic mock data instantly or identify external data sources to use, so that tests accurately reflect real world examples. You can pull data from the following formats: Database, JDBC, Excel spreadsheet, XML file, Grid.
Once you’ve identified the data source, use our simple interface to specify the properties those data sources include. You can use this data source to generate appropriate context-specific responses based on the request parameters. As you modify those data sets, the responses will update automatically.
Build APIs Better, Faster, Stronger with Virtual APIs
Today’s applications depend heavily on APIs, which means testing those applications also depends heavily on those same APIs. With ServiceV Pro, you can keep your project moving on time and on budget by using virtual services as stand-ins for those APIs.
In our upcoming webinar, Build APIs Better, Faster, Stronger, we’ll look at three real-world examples of how development teams have transformed their software delivery strategy with API virtualization.
- How organizations speed time-to-market by reducing dependencies between API development and testing teams
- How companies have lowered delivery costs by overcoming third party rate limits
- How organizations achieve expanded testing capabilities by controlling API conditions
- A live demonstration of ServiceV
Join us on Tuesday, June 14 at 10am or 2pm ET.
Published at DZone with permission of Ryan Pinkham , DZone MVB. See the original article here.
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