Cloud gaming on macOS has improved a lot over the last few years, but I kept running into the same issues: random ping spikes, micro-stutters, Bluetooth latency, and network interruptions caused by background system services.

Instead of tweaking settings manually every time I launched a gaming session, I decided to build a small native macOS utility to automate the process.

The result is CloudBoost.

The Problem

When troubleshooting cloud gaming performance on macOS, I noticed that many issues weren't caused by internet speed.

Even with a fast fiber connection, there were occasional interruptions caused by:

Background wireless discovery services
Network interface transitions
Power management behaviors
Input device acceleration
Memory pressure during long gaming sessions

These issues were small individually, but together they created a noticeably less consistent experience.

The Approach

Rather than creating another "system cleaner" application, I wanted something that would:

Apply temporary optimizations only during gaming sessions
Avoid permanent system modifications
Use native macOS technologies
Restore original settings when disabled

The application focuses on automation instead of aggressive tuning.

Building It

CloudBoost was developed using:

Swift
SwiftUI
Native macOS APIs
UNIX system utilities already available on macOS

The biggest challenge wasn't writing code.

It was understanding which system behaviors actually affected cloud gaming and identifying changes that could safely improve consistency without creating side effects.

Features

Current functionality includes:

Network optimization routines
Temporary wireless service management
Mouse acceleration controls
Session-based optimization profiles
Automatic restoration of original settings
Native menu bar integration
Automatic update checking through GitHub releases
What I Learned

One interesting lesson from this project is that performance optimization is often more about engineering decisions than programming complexity.

Modern AI tools can generate code quickly.

The difficult part is:

Defining requirements
Understanding operating system behavior
Evaluating trade-offs
Testing real-world scenarios
Ensuring user safety

The code is only one piece of the solution.