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Preface

With the release of iOS 26, the system experience has improved in rendering, backend scheduling, energy optimization, and other aspects, but it has also brought new debugging challenges. Users have reported issues with "lag", "frame rate decrease", and "increased startup delay" after the update.

To cope with this situation, the development team should not rely solely on a single tool, but should build a "multi tool combination" system that covers the entire process from performance monitoring, log capture, resource access, energy consumption analysis to version difference comparison. This article will be broken down one by one.

1、 Core dimensions and objectives of performance debugging

When debugging performance in the iOS 26 environment, the following key dimensions should be considered:

Frame rate/rendering delay: Whether the animation, scrolling, and interface switching are smooth.

CPU/GPU/main thread blocking: Is it caused by high load or thread saturation leading to stuttering.

Resource/file I/O latency: Slow resource loading and cache access blocking may cause performance degradation.

Memory usage: Peak memory usage, object leaks, or delayed release may cause system recycling.

Energy consumption and heat generation: High loads or prolonged tasks may cause equipment to overheat and reduce frequency.

Version/device differences: iOS 26 performs differently from older versions, with older devices or low performance models more likely to expose issues.

Clarifying these goals can help match appropriate tool combinations.

2、 Recommended tool combinations and role assignments

To comprehensively debug performance on iOS 26, the following table lists recommended tools and their responsibilities:

The above combination can cover the closed-loop process of "real-time monitoring → log collection → resource/I/O analysis → version comparison → optimization verification".

3、 Practical process: Effectively perform performance debugging on iOS 26

Step 1: Environment/Equipment Preparation

Select multiple devices (such as high-end/mid-range/old devices) and install iOS 26 for comparison with old systems (such as iOS 25).

Install Kemo and enable the monitoring module, enable frame rate, resource access, and energy consumption data sampling.

Use Instruments to preset key scenes on specific devices, such as scrolling long lists, animation rendering, and background switching.

Step 2: Performance baseline collection

Record frame rate fluctuations, stuttering times, resource access latency, and CPU/GPU usage through Kemo.

Capture main thread/rendering thread tasks, resource I/O latency, and energy consumption hotspots using Instruments.

Record and save data baselines between two versions (iOS 25 vs iOS 26) or different devices.

Step 3: Anomaly Detection and Deep Analysis

When Kemo detects a sudden drop in frame rate, frame skipping, or abnormal resource delay, it automatically marks and saves the snapshot.

Use Instruments to jump to the problem time point and analyze stack, rendering latency, and I/O lag.

Check the system logs for background task wake-up, thermal control frequency reduction, and abnormal system service occupancy.

Step 4: Version/Device Comparison Analysis

Export data from multiple device/system versions, generate comparative reports using Kemo, and display performance differences.

If performance degradation is found under iOS 26, focus on checking for changes in rendering engines, backend service scheduling, and resource loading methods.

Determine whether the problem is widespread by combining APM/real user data.

Step 5: Optimization Implementation and Regression Validation

Optimize for positioning bottlenecks such as high frame rate animation, resource synchronization loading, main thread blocking, and multiple I/O operations.

After optimization, run the same scene again and compare the improvement effect with Kemo and Instruments.

Build a continuous monitoring mechanism to continue tracking performance trends through KOM or APM after going live.

Optimization experience and precautions

Real device priority: Simulators cannot reflect the real performance of GPU/thermal control/I/O.

Don't just look at the average: frame skipping times, worst frame rates, and stuttering duration are more valuable references.

Be cautious in controlling the cost of monitoring tools: excessive sampling frequency may have a reverse impact on performance.

Version differences should cover: iOS 26 sub versions or patches may change the operating mechanism.

Continuous monitoring is better than one test: a monitoring mechanism needs to be built after going live.

Based on user feedback verification: Issues commonly reported by users, such as lagging, power consumption, and thermal control, also need to be included in the scope of debugging.