The mobile market is changing rapidly, from the explosive growth of apps and devices to the evolving complexity of software errors. The digital experience is now primary to our everyday lives. And customers expectations are escalating quickly: according to Sauce Labs’ Every Experience Matters report, 18% of users say they won’t wait any length of time for an error to be fixed, while long load times (58%) and app crashes (52%) are among the top five reasons that users will abandon an app.
To keep pace with the demand for a fast and continuous flow of high-value digital experiences, companies need to constantly iterate and improve their software. At the same time, they need to ensure that they can deliver the best possible experience on every device, browser, and operating system to every user, every time.
In response to the need for rapid change, we’ve seen the rise of DevOps, CI/CD, and cloud-based testing methodologies. We’ve also seen an increased need to embrace both shift-left (testing early in development) and shift-right (testing through to production) strategies – not just one or the other.
Traditional testing approaches that focus only on the pre-production stages don’t provide the risk visibility and coverage development teams need early in the software development lifecycle (SDLC). By dispersing tests across the entire SDLC, software organizations can create the continuous feedback loop necessary to drive quality at speed and provide for a more predictable release process that delivers value to customers.
Organizations that focus on only shifting left or shifting right and do not create a testing strategy that extends from development to production find themselves with testing bottlenecks that impede their ability to release high-quality code faster.
DevOps teams need to be equipped with testing and monitoring tools that can help manage the lifecycle of software applications beyond the pre-production stage. Combining test signals across the SDLC enables development teams to identify, prioritize, and fix issues as they happen, and maximize coverage, thereby increasing release velocity without sacrificing code quality.
Key benefits of integrating pre-production and production testing tools and unifying quality signals across your SDLC:
Holistic strategy for quality: With the proliferation of tools and personas for testing throughout the SDLC, isolated production environments no longer serve teams well. By integrating your test tools and quality signals across the SDLC, you can create a holistic strategy for driving quality at speed.
Continuous feedback loop: As developers shift testing left and right, they need tools to help them analyze and understand the data they’re collecting. If developers don’t understand how their test data from across the entire SDLC works together, they can lose valuable time that could be better spent on development and innovation.
Improving risk visibility and coverage: Teams need to create a critical safety net for exceptions as they move fast with DevOps. When pre-production and production signals are combined, it’s easier to get a more complete picture of application risk and ensure faster recovery by identifying which set of code changes led to test failures or production errors.
Understanding the user experience: Error monitoring and reporting tools in production, along with beta testing solutions, provide software development teams with deeper insights into how real users experience and interact with the app. This feedback helps teams define and build relevant requirements in the earlier stages of development and drive continuous improvements.
Guiding your testing strategy: Test signals from production can help guide your organization’s testing strategy in the earlier phases of the SDLC by helping to identify the error trends, prioritizing tests that are causing frequent failures, and eliminating tests that do not provide feedback on improvements.
Detecting and resolving bugs, faster: Production testing and error reporting tools allow software developers to get the much-needed context and data on errors, crashes, and hangs. This helps determine where an error was first seen and correlate the error and instability back to a root cause, thus reducing error resolution times to half.
Increasing development velocity: By quickly identifying issues that are often hard to detect in development and test environments and then refining the test scenarios that were not well defined in earlier stages of the SDLC, teams can increase their development velocity.
The Sauce Labs Real Device Cloud combined with error reporting from Backtrace provides development teams with in-depth insights into the root cause of application failures and further strengthens the coverage of front-end test automation frameworks such as Appium in pre-production environments.
With this integration, customers performing real device testing in Sauce Labs can reduce the time to detection and resolution of errors and crashes by:
Integrating pre-production and production quality signals to create a continuous feedback loop that allows for optimal risk coverage early in the development lifecycle
Gaining the depth and visibility into the root cause of failures
Quickly identifying where in the code the errors happened
Prioritizing errors that matter the most with full data and context
Better understanding error trends to guide your testing strategy (e.g., how often an error happens, on which devices, and more)
Sauce Labs plus error reporting with Backtrace allows customers to scale live and automated testing with instant access to thousands of Android and iOS devices in the Sauce Labs Real Device Cloud. Development teams can quickly run regression tests on real devices after they resolve errors to ensure their fixes do not cause any unexpected consequences.
When a mobile app is ready to move from development into production, the stakes become higher each time a new build is moved. Delivering quality mobile apps while mitigating the risk of bugs in production brings its own challenges given the complexity of mobile app development and testing. By leveraging a DevOps test toolchain (DevOTT) that helps teams collaborate across the entire SDLC and connect quality signals from coding to release, you can create optimal risk coverage to continually build confidence in your software quality while improving release velocity. And ultimately, deliver the best possible digital experiences to your users, every time!