It’s hard to deny that PerfDog is indeed useful, especially for mobile performance testing, as it integrates many things together:
- View CPU / Memory / FPS together
- Real-time monitoring on real devices
- Cross-platform support
But the issue is very real: the price isn’t friendly. For small teams or individual developers, the cost of several thousand per year can be a burden.
So, is there a way to replace it? I’ve tried several combinations in actual projects and finally compiled a split solution. It’s not a replacement for PerfDog, but it’s sufficient for most scenarios.
What Does PerfDog Actually Solve?
If you directly look for alternative tools, it’s easy to fall into the trap of which one is more similar.
A more effective approach is to first break down its functions:
- Real-time performance monitoring (CPU / Memory / FPS)
- Specified App monitoring
- Usable in testing environments (not dependent on Mac)
- Simple to operate, testers can also use it
As long as most of these capabilities can be covered, an alternative solution can be formed.
Using Device Monitoring Tools to Replace Real-Time Performance Charts
In my practical use, what I use PerfDog for most is actually real-time performance curves.
This part can be replaced with lightweight tools.
Using Keymob Assistant for Real-Time Performance Monitoring
In Windows environments, I often use Keymob Assistant (Keymob) primarily to observe resource changes at the device level.
Operation Process
1 Connect Device
- Connect iPhone via USB
- Open Keymob Assistant
- Wait for device recognition
2 Enter Performance Charts
Select on the left:
Performance Charts
3 Check Metrics
Choose based on testing goals:
- CPU
- Memory
- FPS
For lag issues, prioritize CPU and FPS.
4 Select App
Click “Select App,” check only the target application, and optionally check system CPU for reference.
5 Start Monitoring
After clicking start, perform operations on the phone:
- Open a page
- Scroll a list
- Play a video
Observe curve changes.
What Problems Can It Solve?
Mainly addresses:
- Which operation triggers performance issues
- Whether there is sustained high load
- Whether it’s an issue with the App itself
Using Official Tools for In-Depth Analysis
When anomalies are found, I usually return to the Mac.
The Role of Instruments
Instruments is more suitable for:
- Function-level CPU analysis
- Memory allocation tracking
- Rendering performance analysis
The process is typically:
- Use device monitoring to find abnormal operations
- Reproduce operations with Instruments
- Locate specific code
This avoids “blind analysis.”
Using Logs to Supplement Context
Performance data itself is the result; logs are more like the process.
In actual troubleshooting, I open simultaneously:
- Performance charts
- Real-time logs
Using Keymob Assistant to View Real-Time Logs
Operation method:
- Select Real-Time Logs on the left
- Click start
- Set keyword filters
When CPU or FPS shows anomalies, you can cross-reference logs to see:
- Whether network requests are triggered
- Whether a specific task is executed
This step is very crucial.
Real Alternative Case
Once, while testing a version, we found:
Page scrolling would lag
The handling process was as follows:
Step 1 Use Keymob Assistant to monitor performance:
- CPU significantly increased
- FPS decreased
Step 2 Open real-time logs and find frequent data requests triggered during scrolling.
Step 3 Use Instruments to analyze and confirm that the main thread executed a large amount of JSON parsing.
Ultimately, the optimization was to move parsing logic to a background thread. Throughout this process, PerfDog wasn’t used, but the issue was still located.
Trade-Off Between Cost and Effectiveness
PerfDog’s advantage lies in its integration.
But the split solution’s advantages are:
- Low cost
- Tools are replaceable
- Higher flexibility
For small teams, this approach is more sustainable.
Performance testing is essentially not a tool problem, but a methodology problem.
PerfDog packages the process, while the alternative requires you to split and recombine the process yourself.
Once you get used to this way, you’ll find that even without expensive tools, you can complete most performance analysis work.