By Michael Olechna, Product Marketing Manager, SmartBear
As the world continues to digitize, user experience is one of the top priorities in app development. And since it’s impossible to test all scenarios prior to releasing your app in the wild, teams need rapid insights into how users are interacting with their apps in real-time.
Development teams have always been pressed for greater visibility into their apps. This is true whether developers are focused on the pre- or post-production stage of their applications. What’s changed the most in recent years is where the emphasis is being placed. Hint – it’s the moment where your users are interacting with your app.
Teams need to be able to identify bugs, prioritize them, and remedy them – fast. To consumers, every second counts. Companies unable to keep up often pay the price. A one second delay in webpage load times can lower conversion rates by up to 20%. When on mobile apps, 70% of users will quit an app if it takes too long to load.
Without proper visibility, fixing inferior performance can be time consuming and fruitless. After all, 76% of mobile users state they use mobile apps for purchasing specifically because it saves them time. The damage has been done – either your user has left your app due to the error, or you’re too late to address the issue.
That is why development teams facing what at times feels like unconquerable odds need to maximize their efforts. The question is, how?
Zeroing in on critical app functions and segmenting your user base is a good starting point. But we also need to look at the code before it’s shipped. By employing progressive delivery tactics like feature flags and experiments, you can save your team (and users) future headaches. Lastly, tracing issues back to their root cause and examining your microservices deliver insight into unseen blind spots.
We’ll dive into each of these in more detail, beginning with our previously identified starting point.
How and Where to Slice and Dice Your App
Technical debt continues to pile up as a casualty in the race to deliver better user experiences. But there is an important rule that developers should keep in mind in this race against time. Not all bugs are worth fixing. It’s a mantra that should be reiterated by all development teams. Not all bugs are worth fixing. The real challenge is deciding which bugs are worth fixing.
The best way to decide what to fix is to think back to what matters most to your app’s users. For instance, users would expect a flawless shopping experience when using an e-commerce app. Therefore, developers of this hypothetical app would prioritize its checkout function when it comes to bugs or slow performance.
Prioritizing crucial app functions, like the checkout example, establishes an easy-to-follow hierarchy for competing real-time alerts. Once prioritized, your team can immediately begin issue resolution by leveraging user metadata and breadcrumbs. User metadata delivers important diagnostics to make sure the issue isn’t widespread, while breadcrumbs will help replay the user’s actions before the issue occurred.
Segmenting your app enables your team to view your app through an acute lens. But this only applies to when your app has already been released. What if there was a way to reduce the number of issues in production before release?
Deliver Faster Releases with Less Headaches
While consumers have come to expect faster app response times, the same can be said for the development of the apps themselves. Many organizations have long since moved on to continuous delivery workflows so they can easily roll back mistakes released to their users. While this approach is an improvement, it’s still not without its faults. Bugs can and do make it out to the entire user base.
The risk for widespread errors is still present, even if a release can be rolled back. Often development teams are releasing multiple updates per day to remedy bug fixes or satisfy consumers’ appetite for new and better features. This haste and need for constant updates can cause further bugs to be released.
Progressive delivery is an evolution of the continuous delivery method that will continue to pay dividends long after release. It begins with segmenting a portion of your user base (echoing the theme of our first tip). Think small: one percent or less of your user base.
After identifying this segment, your team deploys a code change via feature flags or experiments to this new subset. From there, your team can monitor any unexpected changes that occur due to this new code. If errors do occur because of this new feature, you can quickly roll it back for remediation. If all goes as planned, you can take the next step to release to a wider subset of your audience for further monitoring.
By incorporating this feedback loop into your development, you are taking less risk of an unexpected bug wreaking havoc. After releasing to your subset users with no errors, you can be rest assured when deploying at full scale. Your team will be able to confidently make changes to the code knowing it won’t reset your app, while leveraging data to accelerate your release cycle.
Trace Back to the Root Cause
Microservices have quickly gained steam in development communities. Its rapid adoption has been a great contributor to the age of fast development and accelerated release cycles. However, it has presented a unique set of challenges.
Distributed microservices are inherently complex. This complexity can block visibility into the underlying root cause of production issues. Error and performance monitoring provide great insights, but their capabilities are insufficient for dealing with microservices. Their application insights lack critical details about the interaction between microservices.
Lack of insight into the path service requests take through microservices architecture leaves blind spots into components they touch and the subsequent effect it has on related code. Errors are directly affected – it becomes harder to understand their context, where they occurred, and how to resolve them.
Distributed tracing gives developers a flashlight that illuminates the path across their microservices. Why? Because tracing establishes a complete trail of requests in our systems. This trail includes important site markers that were previously missing – errors that occurred, vital data about services that requests touched, as well as their flow between different services.
To add further complexity, these requests span multiple services, which can make it that much more difficult to get to the root cause of an issue. Implementing distributed tracing helps development teams determine the length of each request, the services it encountered, and the latency of each step. All this information helps developers identify and understand the root cause faster, improving mean time to resolution and preventing future bottlenecks.
Elevate Performance and User Loyalty with Better Developer Visibility
The race for faster application development is one that will never cease. Development teams have long known this. They’ve moved swiftly through the days of waterfall environments to agile development on to continuous delivery and landed on today’s nonstop release cycle.
Consumers around the globe have responded with delight but now expect a higher standard. They’ve grown an insatiable appetite for consistent, frequent updates and will deliver vocal feedback about their approval or disapproval. If an application does not meet their requirements, they’ll willingly walk toward eagerly waiting competitors.
Prioritizing the performance of critical app functions with your users’ input will boost their loyalty. Using progressive delivery to examine and test releases before going live to your entire user base avoids potentially catastrophic issues. Implementing distributed tracing of your microservices covers the gaps in error monitoring to help your teams identify and understand root causes of issues faster.
When combined, these principles deliver visibility into your microservices architecture and your pre- and post-production stages. Most importantly, it alleviates stress on your development team while delivering to your users the app experience they expect and one they will return to for more.
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ABOUT THE AUTHOR
Michael Olechna is Product Marketing Manager at SmartBear, a leading provider of software development and visibility tools. He has earned a reputation as a data-driven advisor for companies like Dassault Systèmes and MatTek Corporation, among others.
