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mobile app performance

Optimizing mobile performance with tracing

Find out how to optimize your mobile app performance with tracing. With tracing, you can create a better mobile experience for your users and improve revenue.

Mobile app revenue today has eclipsed $500B, and the industry is expected to surpass $670B by 2027.

Meanwhile, people are spending more time on their phones than ever before, with some spending an average of more than 4 hours daily with nonvoice activities.

If we’re truly in an Attention Economy, then the primary battlefields are iOS and Android devices.

As mobile becomes increasingly competitive, it’s also become more complex. To produce high quality apps worthy of people’s attention and dollars, you need to be able to understand and address performance bottlenecks that cause user frustration and abandonment.

In that regard, the importance of tracing in mobile app development today, cannot be overstated.

What is tracing in mobile app development?

Tracing is a crucial tool for identifying and rectifying performance bottlenecks in mobile applications, and its utility is somewhat different than how tracing is typically used in the backend. 

From the mobile perspective, it stands apart from traditional performance monitoring by offering detailed context into the user experience that leads to poor or unexpected performance. 

The current status quo in mobile app development — only measuring the duration of completed key user flows, like startup time — often overlooks the nuanced analysis that can be done by examining traces. Ultimately, this leads to less efficient troubleshooting and optimization strategies.

The difference between mobile client and backend tracing

The main difference between mobile client and backend tracing lies in the usefulness of looking at individual trace instances, and thus how the level of detail and context that are captured can be used. 

Backend tracing is typically focused on analyzing trace data in aggregate. This involves looking at the overall performance of a system or service, and identifying patterns and trends of aggregates when certain context filters are applied to identify unique cases. 

Backend tracing is often used to identify bottlenecks and production issues, optimize resource allocation, and improve overall system performance in a distributed system where basic metrics are not sufficient. It is less concerned with individual trace instances or the specific user experiences they affect. 

On the other hand, mobile client tracing can be used more granularly to analyze individual user experiences. It captures detailed data about specific user interactions, such as app startup time, network requests, UI rendering, and other contextual data that may not be aggregatable. 

Mobile client tracing allows for richer analysis of specific user sessions, identifying issues that may impact individual users and their interactions with the app, where the cause or effect of the poor performance is not captured in the trace itself. It provides more context and visibility into the user experience beyond just knowing a workflow is slow, allowing for more targeted optimizations and faster issue resolution because of the insights derived by combining the trace with app and device conditions that it was captured under. 

In sum, backend tracing is more about aggregating and analyzing data at a high level to optimize system performance. And, while mobile client tracing can be used that way, it can also be used to contextualize and analyze individual user experiences to improve the overall user satisfaction.

Using tracing to optimize mobile user flows

Tracing can be utilized to enhance important user flows by providing valuable insights into the timing and behavior of these flows in production. 

To maintain or improve the performance of key user flows with tracing, consider doing the following: 

    1. Identify the key user flow: Determine which user flow is critical to the success of your app or website. This could be the startup process, a specific action like a checkout confirmation, or any other flow that is important for user experience. 
    2. Add a trace to the user flow: Implement a trace that captures the start and stop of the entire user flow, even if it was interrupted and didn’t succeed. This allows you to not only capture the duration of successful instances, but also know how many didn’t succeed, which could be just as valuable. 
    3. Add sub workflows: Within the trace, create spans to represent sub workflows within the main user flow. This allows you to track and analyze specific components or actions within the flow. 
    4. Add metadata and contextual information: Include relevant metadata and contextual information in the trace. This could include device information, network conditions, or any other factors that may impact the performance of the user flow. Data that you can aggregate are important, but even contextual information you can’t aggregate can be useful on its own.
    5. Monitor the trace: Once the trace is implemented, you can monitor it in production through dashboards and alerts. This allows you to observe any changes to performance or unexpected failures in that user flow. You can also set up alerts based on specific metrics or thresholds to be notified of any production issues. 
    6. Analyze trace in aggregate: Look at the performance of the workflow overall and to identify particularly slow spans to see if they can be optimized to improve the overall performance of the workflow.
    7. Investigate outliers: Look into trace instances that are outliers to see if the performance is explainable. Perhaps there are edge cases that were not anticipated given the context the workflow is running under based on factors that are not captured in the trace (e.g. garbage collection is happening concurrently).

By following these steps, you can use tracing to gain insights into the timing and behavior of important user flows. 

This information can help you identify and address performance issues, optimize workflows, and improve the overall user experience.

When to use tracing in mobile app development

Tracing is appropriate to utilize in mobile app development when you want to validate, monitor, and debug performance in production at scale. 

It allows you to capture production performance information and identify areas that may be causing slowdowns or behaving unexpectedly that can only be replicated in real world conditions. 

Tracing is particularly useful for optimizing key workflows in your app. It helps you understand the timing and behavior of different components and can provide insights into potential bottlenecks or areas for improvement.

That said, tracing should be employed not just when issues arise, but also proactively. 

Adding tracing to important workflows ensures that you can uncover potential issues before they impact the user experience, and verify the effectiveness of new features or improvements in real-world scenarios, beyond benchmarking. It also gives you the data you need to debug performance issues when problems in production arise.

Embracing tracing for mobile

Incorporating tracing into the mobile app development process is essential for creating efficient, user-friendly applications. And in an increasingly competitive mobile space, a great user experience is often the difference between success and failure.

To help engineers build better mobile experiences, Embrace offers a tracing solution specifically designed for mobile called Performance Tracing.

With Embrace Performance Tracing, engineers can closely monitor and instrument key flows in their apps, and get detailed insights for optimizing their user experience. 

Embrace also provides custom instrumentation, detailed monitoring, and efficient debugging, aiming to help developers improve app responsiveness and user satisfaction.

Learn more about Embrace Performance Tracing here.

Embrace Embrace Performance Tracing

Want to see how Performance Tracing works? Learn how Embrace helps build better mobile experiences via a demo with one of our experts.

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