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Description
Background
We have a batch of Mac Studio devices that we would like to use for network traffic monitoring and packet capture using DeepFlow.
Current Situation
From our investigation and PR #11449, we understand that:
- DeepFlow agent primarily targets Linux with eBPF-based observability
- Windows and Android have basic support
- macOS support is limited/incomplete
Our Use Case
We have multiple Mac Studio devices (Apple Silicon M1/M2 Max/Ultra) that we want to use for:
- Local network traffic capture on macOS
- Development and testing of network applications
- Traffic analysis in macOS environments
Proposed Solution
We notice that PR #11449 adds basic macOS support using libpcap for packet capture. This is exactly what we need:
- libpcap is mature and well-supported on macOS
- It works well on Apple Silicon
- It provides sufficient performance for our monitoring needs
Feature Requests
- Complete macOS libpcap support - Ensure the agent can properly capture packets on macOS interfaces
- Apple Silicon optimization - Native ARM64 support for M1/M2 chips
- Interface selection - Ability to specify which macOS network interfaces to monitor
- BPF filter support - Allow custom BPF filters for packet capture
- Performance tuning - Optimize libpcap buffer sizes for high-throughput scenarios
Environment
- Hardware: Mac Studio (M1 Max, M2 Ultra)
- OS: macOS Ventura / Sonoma
- Network: Multiple interfaces (Ethernet, Thunderbolt, Wi-Fi)
- Traffic volume: Moderate to high (1-10 Gbps in some scenarios)
Questions
- Is there a timeline for official macOS support?
- Are there any known limitations with libpcap on macOS that we should be aware of?
- Would you be interested in accepting more contributions for macOS-specific features?
Related
- PR feat(agent): add basic macOS platform support #11449 - Basic macOS platform support
Willingness to Contribute
We are willing to contribute code, testing, and documentation for macOS support. Our team has experience with:
- libpcap/pcap development
- macOS network stack
- Apple Silicon optimization
Thank you for considering this feature request!
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