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Instruments is a performance-analysis and testing tool for iOS, iPadOS, watchOS, tvOS, and macOS apps.

Instruments Documentation

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How to export Allocations report in XML (Call Tree format) with xctrace?
Hello Apple team, I am using xctrace to record an Allocations trace on iOS. For example: xctrace record --template "Allocations" --launch com.example.myapp --time-limit 30s --output alloc.trace After recording, I can export the results in Allocations List format (flat list of allocations) using: xcrun xctrace export --input ./alloc.trace --xpath '/trace-toc/run/tracks/track[@name="Allocations"]/details/detail[@name="Allocations List"]' --output ./alloc.xml This works fine and produces an XML output. However, what I really need is to export the data in Call Tree format (as shown in Instruments GUI). I checked xctrace export --help, but it seems that the Allocations template only supports the List view for export, not the Call Tree breakdown. My question is: 👉 Is there a way to export an Allocations trace in XML with Call Tree details using xctrace? 👉 If not, is there an API or recommended workflow to automate this instead of exporting manually from Instruments GUI? Thanks in advance for your help!
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Sep ’25
Battery Consumption Analysis Using Xcode Instruments
I have been working on battery consumption analysis for my application, and as part of this effort, I wanted to understand how competitor apps behave under similar usage conditions. To do this, I downloaded competitor apps from the App Store and attached them to Instruments via Xcode. I then executed a defined set of manual test scenarios to simulate real user behavior. During these tests, the iPhone was connected to a Mac and charging continuously, which meant that System Power Usage logs were not generated in Instruments. However, I was able to capture detailed metrics such as: Network usage CPU load GPU activity Display and brightness impact Other runtime performance characteristics Since direct battery drain data was unavailable, I used derived analysis (with AI assistance) to estimate approximate power consumption based on the above metrics, assuming real-device (battery-powered) conditions. According to Apple documentation, System Power Usage in Instruments is not directly tied to the device’s battery percentage. Instead, it appears to be computed using contributing factors such as CPU, network, display, and other subsystem activity. This raises a few important questions about data reliability and methodology. Key questions: How reliable are Instruments-based metrics (CPU, network, display, GPU) for estimating real-world battery consumption when the device is charging? Can these metrics be safely used as a comparative baseline between competitor applications, even if absolute battery drain values are unavailable? Is the System Power Usage instrument essentially a derived model based on subsystem activity, and if so, does it remain accurate when the device is not discharging? From Apple’s perspective, is this a valid approach for relative power comparison, provided that: The same device is used OS version is identical Test scenarios are consistent and repeatable Based on these findings, would it be reasonable to proceed with instrumenting our own application, run the same scenarios, and draw conclusions using relative comparisons rather than absolute battery percentages? The intent is not to claim exact battery drain numbers, but to establish a directionally correct and repeatable comparison that can guide performance optimizations in our own application. I would like to understand whether this methodology aligns with Apple’s recommended practices, or if there are limitations or inaccuracies I should be aware of before relying on these results for decision-making.
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Jan ’26
The best way to build, test and upload an iOS app without owning a Mac
Hi everyone, I’m developing a cross-platform mobile app (React Native) but I don’t currently own a Mac. What is the most reliable and professional way to: Build the iOS version Test it properly (real device / TestFlight) Upload it to the App Store Are cloud Mac services (like MacinCloud, AWS Mac, etc.) considered stable for production release workflows? Is there any fully supported workflow without direct access to a physical Mac? Would appreciate real-world experience from developers who faced the same situation. Thanks in advance.
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Is dtrace & dtruss supported on current macOS?
When I try to run dtruss on a command line program (freshclam) I see: $ sudo dtruss -a /usr/local/bin/freshclam 2>&1 | tee ~/tmp/dtruss.out dtrace: system integrity protection is on, some features will not be available dtrace: failed to execute /usr/local/bin/freshclam: DTrace cannot instrument translated processes I did some research and found advice on how to enable dtrace use via running: csrutil enable --without dtrace in a terminal running in macOS recovery mode. When I do that I see a warning saying this is an unsupported configuration and that it will allow unsigned kernel modules to be loaded. This is not what I want, I just want to run dtruss on a program while keeping all the other SIP protections in place. Why can't I just use sudo to grant the privileges for dtrace to work? All of this has me wondering if Apple intends for developers to use dtruss/dtrace in the current macOS?
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How to programmatically determine fixed CPU frequency for memory latency benchmarking on Apple Silicon?
Hi everyone, I am developing a benchmarking tool to measure memory latency (L1/L2/DRAM) on Apple Silicon. I am currently using Xcode Instruments (CPU Counters) to validate my results. In my latest run for a 128 MB buffer with random access, Instruments shows: Latency (cycles): ~259 cycles (derived from LDST_UNIT_OLD_L1D_CACHE_MISS / L1D_CACHE_MISS_LD). Manual Timer Result: ~80 ns. To correlate these two values, I need the exact CPU Frequency (GHz) at the time of the sample. My Questions: Is there a recommended way to programmatically fetch the current frequency of the Performance cores (p-cores) during a benchmark run? Does Apple provide a "nominal" frequency value for M-series chips that we should use for cycle-to-nanosecond conversions? In Instruments, is there a hidden counter or "Average Frequency" metric that I can enable to avoid manual math? Hardware/Software Environment: Tool: Instruments 26.3+ (CPU Counters Template). Chip: A19, iPhone 17 pro. OS: 26.3.
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