Client Tracing: Understanding Mobile and Desktop Application Performance at Scale

A customer writes in and says the dreaded words: “My app is slow”. Here we go…  Performance problems can be a real struggle to track down, especially if they aren’t easily reproducible. Looking at the customer’s logs, you see that it takes over 1.5 seconds to switch between channels on their Android client! That must…

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Slack
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Justin Rushing
•21 min read•advanced•
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Overview

The article discusses the implementation of client tracing at Slack to enhance the performance of mobile and desktop applications. It details how distributed tracing was utilized to diagnose and improve latency issues, providing insights into client-server interactions and database performance.

What You'll Learn

1

How to implement distributed tracing in mobile and desktop applications

2

Why understanding client-server latency is crucial for user experience

3

When to apply performance tracing to diagnose application issues

Prerequisites & Requirements

  • Understanding of distributed systems and performance metrics
  • Familiarity with tracing tools like Honeycomb(optional)

Key Questions Answered

How does distributed tracing improve application performance?
Distributed tracing allows developers to pinpoint latency issues by providing a detailed view of client-server interactions. By breaking down actions into smaller spans, engineers can identify where delays occur, whether in API calls, database transactions, or network latency, leading to more effective optimizations.
What are the phases of an API request in client tracing?
The API request in client tracing is broken down into three phases: queue time, HTTP request time, and parsing time. This breakdown helps developers understand where delays are occurring and allows for targeted optimizations in the application.
What insights can be gained from tracing user interactions?
Tracing user interactions provides insights into how application performance impacts user experience. By measuring view load times and actions like message sending, developers can identify bottlenecks and improve the overall responsiveness of the application.
How does tracing help in diagnosing database performance issues?
Tracing helps diagnose database performance issues by recording transaction times and the number of times different tables are accessed. This information allows developers to understand the impact of database interactions on overall application performance and identify areas for improvement.

Key Statistics & Figures

Percentage of API requests sampled for tracing
1%
This sampling strategy was implemented to gather sufficient data without overwhelming the system.
Reduction in performance for specific cases after optimizations
40%
After addressing issues identified through tracing, performance for certain user interactions improved significantly.

Technologies & Tools

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Observability
Honeycomb
Used to interact with traces and visualize performance data.
Database
Sqlite
Utilized in mobile applications to cache information and enhance performance.

Key Actionable Insights

1
Implement distributed tracing to gain visibility into application performance.
By using distributed tracing, teams can identify latency issues across different components of their applications, leading to faster diagnosis and resolution of performance problems.
2
Break down API requests into detailed phases for better performance analysis.
Understanding the distinct phases of API requests allows developers to pinpoint specific areas of delay, enabling targeted optimizations that enhance user experience.
3
Utilize tracing to monitor user interactions and their impact on performance.
Modeling user interactions with tracing provides insights into how application performance affects user satisfaction, guiding further optimizations.

Common Pitfalls

1
Assuming that all performance issues are due to network latency.
Performance issues can arise from various sources, including inefficient database queries or slow client-side processing. It's essential to analyze all components of the application to accurately diagnose and resolve performance problems.

Related Concepts

Distributed Tracing
Performance Optimization
Client-server Architecture