Preface
This article will detail the viewing methods and tool usage by role, and build a practical process from "understanding battery status → power consumption analysis → problem localization → optimization verification" to help you effectively improve the power consumption performance of the app.
1、 System native viewing method: Beginner's skills for ordinary users
Settings → Battery → Battery Usage
- Can display the percentage of battery usage for each app in the past 24 hours/10 days;
- You can view the battery ratio distinction between the front-end and back-end of the app;
- Can identify which apps consume the highest amount of power.
Settings → Battery → Battery Health
- Display the 'maximum capacity percentage';
- Display the 'Peak Performance Capacity' to determine if the device's performance may be affected by battery degradation;
- Provide battery health reference.
The native method of the system is suitable for users to quickly understand the battery condition, but lacks quantitative data and behavioral details.
2、 Developer perspective: Tools in-depth power consumption analysis
Xcode Instruments → Energy Log
- Real time analysis of energy consumption in various stages of the app (startup, interface sliding, background wake-up, etc.);
- Display energy consumption hotspots (such as frequent positioning, rendering, requests, etc.);
- Can be used in conjunction with Time Profiler to locate power consumption codes.
However, Instruments does not support long-term sampling of devices and is only used for short process debugging.
3、 Testing and collaboration layer: KeyMob real-time power consumption monitoring
Feature Highlights:
- Cross platform use across Windows/macOS/Linux platforms;
- Can record CPU, GPU, memory, FPS, and network behavior trends on the device;
- Can monitor the power consumption of the app during operation and in the background, and output a complete power curve;
- Support exporting trend reports for easy version comparison and team sharing.
Practical process:
- Use Kemo to run the app, simulate a typical user behavior, and run a background idle;
- View real-time battery curve, power consumption ratio, and backend active module records;
- Export reports to developers to locate power consumption behavior in conjunction with logs;
- After optimization, resample and compare again to confirm significant performance improvement.
4、 Process example: Optimizing backend power consumption issues
- User or QA feedback: Abnormal power consumption during app backend operation;
- Use Kemo sampling to record the backend status for several hours;
- The power curve shows that the overall power consumption in the background is as high as 15%/hour, and the network or positioning module has been activated multiple times;
- Develop and integrate Instruments to thoroughly investigate the accumulation of power consumption code, and if any backend tasks or location monitoring are missed, close them;
- After repair, resampling showed a significant decrease in battery level;
- Finally, archive the report to form an optimization record and enhance team experience.
5、 Comparison Table of Electricity Consumption for Different Roles
| role | View mode | Focus on the key points |
|---|
| regular user | System Settings → Battery Usage Interface | Which app consumes the most power |
| Testing Team | Kemo Sampling Record App Power Behavior and Results Report | Comparison results of different versions or devices |
| developer | Instruments energy consumption analysis+business code processing | The power consumption hotspot is located at the code implementation point |
| Product/Operations Team | Firebase Performance or Kemo Output Report for Continuous Monitoring | Electricity trend, inter version changes, warning response mechanism |
6、 Practical strategy suggestions for optimizing electricity consumption
- Restricting background wake-up: controlling positioning Socket、 Active frequency of push and other modules;
- Reasonably arrange the time slots for backend tasks to avoid resource consumption when users are not using them;
- Optimize animation logic: reduce frequent GPU usage;
- Reduce redundant network requests, merge or delay loading;
- Control log frequency: Avoid frequent logging before crashing, which may affect battery life.
7、 Why is Kemo the core bridge for performance monitoring?
- Real sampling behavior data to compensate for the deficiency of Instruments' inability to record offline;
- Support real-time and offline modes, suitable for developers and QA scenarios;
- Unified reporting standards facilitate multi role sharing and collaborative feedback;
- Combined with tools such as Instruments and Firebase, a closed-loop process for power consumption monitoring can be achieved.
- The battery level and energy consumption performance not only affect the user experience, but also are important indicators of the quality of an app.
summary
By setting up the system to view basic data, using Instruments to locate energy consumption functions, and using cross platform trend sampling and code repair by Kemo, you can establish a sustainable performance monitoring mechanism to achieve a robust and high-quality experience for the app.