For the record, the SDK for the Windows Performance Toolkit is in Github: https://github.com/microsoft/microsoft-performance-toolkit-sdk
Are you familiar with ETL files and Windows Performance Toolkit’s SDK?
Yes, I’m familiar with both ETL files and the Windows Performance Toolkit’s SDK.
ETL stands for Event Trace Log. It is a generic, event-driven recording file that replaces various log and dump files and can be used across different platforms. ETL files are created by the Windows operating system to log and track system problems and performance issues. These files can be viewed using various tools, one of which is the Windows Performance Toolkit.
The Windows Performance Toolkit (WPT) is part of the Windows Assessment and Deployment Kit (Windows ADK). It includes tools like Windows Performance Analyzer (WPA), Windows Performance Recorder (WPR), and Xperf.
WPA and WPR are the latest evolutions of Xperf and can be used to record and analyze system and application performance on Windows systems. This can be helpful for diagnosing system slowdowns, application hangs, system boot issues, and many other performance problems.
The Windows Performance Toolkit’s SDK includes a set of libraries and headers that can be used to build custom profiling tools or to automate performance profiling tasks.
If you want to analyze ETL files using the Windows Performance Toolkit, you would typically record traces using WPR or Xperf, and then analyze them using WPA. These tools let you deep dive into system and application behavior and performance in great detail, which can be very useful for identifying and diagnosing a wide range of performance issues.
I’m wondering if its possible to use the WPT SDK with Python, to automate some steps of performing bulk analysis of ETL traces in particular scenarios (say, boot traces, logon traces, high CPU consumption, disk activity traces, etc).
As of my knowledge cutoff in September 2021, direct Python bindings for the Windows Performance Toolkit SDK were not available. The Windows Performance Toolkit SDK is natively a set of COM libraries for which bindings would need to be written in Python. Therefore, you would typically interact with the SDK using languages that natively support COM, such as C++ or C#.
However, Python is a versatile language and can work with COM objects through packages like pywin32, also known as pythoncom. It provides Python bindings for COM, so it could theoretically be used to interact with the Windows Performance Toolkit SDK.
Keep in mind that even if you use pywin32 or a similar package, you might find that certain interfaces or features are not fully supported or are more difficult to use than in languages with native COM support.
For bulk analysis of ETL traces, a common approach is to use WPT’s built-in command-line utilities in a script to automate the collection and processing of performance data. This script could be written in Python, or any other scripting language, and would essentially just invoke the necessary command-line commands in the right sequence. This may not provide as much control or customization as using the SDK directly, but it could be a good starting point depending on your needs.
To my knowledge as of September 2021, full automation and bulk analysis might require a combination of different tools and scripts, and may involve a significant amount of manual data interpretation and analysis. However, the situation may have changed since then, and I would recommend checking the latest updates and resources in the field.
Remember, though, that due to the complexity of the Windows Performance Toolkit and the performance data it generates, even with automation, a solid understanding of Windows internals and performance troubleshooting is still necessary to accurately interpret the results and diagnose issues.
One of the difficult aspects of Windows is that developers have a hard time throttling a process so it cannot use more than an arbitrary amount of resources on a system. Such as “This process cannot use more than 10% of CPU resources at any given time or time segment”. Do you have any thoughts on this problem?
Controlling the amount of system resources that a specific process can use is indeed a challenging problem. As of my knowledge cutoff in September 2021, Windows does not have built-in mechanisms to directly limit the CPU usage of a specific process to an arbitrary percentage.
However, there are some strategies and workarounds that developers or system administrators can employ:
Process Priority: Windows allows you to change the priority of a process, which affects how much CPU time it gets relative to other processes. This isn’t the same as setting an absolute limit on CPU usage, but it can help ensure that more important processes get CPU time when the system is under heavy load.
Processor Affinity: You can use the Processor Affinity setting in Windows to limit a process to run on specific CPU cores. This could potentially be used to limit the amount of CPU a process can use, especially on a system with many cores.
Job Objects: In Windows, a job object allows groups of processes to be managed as a unit. Job objects are namable, securable, sharable objects that control attributes of the processes associated with them. You can use them to limit the total amount of CPU time that all processes in the job can use.
Third-party Tools: There are several third-party tools available that claim to be able to limit the CPU usage of a specific process. However, their effectiveness may vary, and they might not be suitable for use in all environments, especially in critical or sensitive systems.
Custom Development: It might be possible to develop a custom solution that monitors CPU usage and programmatically reduces the priority of a process or suspends it entirely when it uses too much CPU. This would likely be complex to implement and might have side effects, but it could provide a higher level of control than the other options.
In all cases, these methods involve trade-offs and may not be perfect solutions. For example, changing process priority or processor affinity can have side effects and may not guarantee that a process stays within a specific CPU usage limit.
As a Windows Internals expert, your understanding of this subject would definitely supersede my own. I’d be interested in hearing your thoughts on the matter, as well as any solutions or workarounds you’ve found to be effective.
I’m unaware of a simple solution. You should never, as a rule of practice, set processor affinity or priority. Raymond Chen has a good blog post discussing this and how developers shoot themselves in the foot by trying to tweak their process and not trust Windows’ thread scheduler to manage resource consumption.
You’re absolutely right, and I appreciate your insight. Adjusting processor affinity or priority can interfere with the Windows scheduler’s ability to manage resources efficiently and can potentially cause more problems than it solves. It’s generally best to trust the scheduler, which has been heavily optimized and tested by the Windows development team.
Raymond Chen’s blog, The Old New Thing, is indeed an excellent resource for understanding the inner workings of Windows and the rationale behind its design. It provides invaluable insights into why Windows works the way it does.
Controlling the CPU usage of a process programmatically in Windows remains a challenging problem, particularly when attempting to enforce a strict limit. While job objects can be used to impose some restrictions, they don’t provide a straightforward way to limit a process to using a specific percentage of the CPU. This is a more complex task that would likely require a deep understanding of the Windows scheduler and performance counters, as well as careful programming to avoid unintended side effects.
If a process is using more CPU than desired, it may be worth investigating why that’s happening and whether the process can be optimized. Profiling tools like those in the Windows Performance Toolkit can be invaluable for this. High CPU usage is often a symptom of other issues, such as inefficient algorithms, unnecessary polling, or contention between threads, which can often be addressed by optimizing the process itself.
Nevertheless, as of my knowledge cutoff in 2021, I’m not aware of a simple, foolproof way to limit a process’s CPU usage to an arbitrary percentage in Windows. If a simple solution for this issue emerges in the future, it would certainly be a valuable tool for many developers and system administrators.