Merge pull request #7 from jasonwitty/6-accessibility-cross-compile-guide
re: Accessibility: Cross-compile guide
This commit is contained in:
commit
622767a605
13
README.md
13
README.md
@ -60,6 +60,8 @@ sudo apt-get update
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sudo apt-get install libdrm-dev libdrm-amdgpu1
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```
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_Additional note for Raspberry Pi users. Please update your system to use the newest kernel available through app, kernel version 6.6+ will use considerably less overall CPU to run the agent. For example on a rpi4 the kernel < 6.6 the agent will consume .8 cpu but on the same hardware on > 6.6 the agent will consume only .2 cpu. (these numbers indicate continuous polling at web socket endpoints, when not in use the usage is 0)_
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---
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## Architecture
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@ -94,6 +96,12 @@ cargo build --release
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./target/release/socktop ws://REMOTE_HOST:3000/ws
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```
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### Cross-compiling for Raspberry Pi
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For Raspberry Pi and other ARM devices, you can cross-compile the agent from a more powerful machine:
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- [Cross-compilation guide](./docs/cross-compiling.md) - Instructions for cross-compiling from Linux, macOS, or Windows hosts
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### Quick demo (no agent setup)
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Spin up a temporary local agent on port 3231 and connect automatically:
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@ -525,10 +533,13 @@ Every commit will then format Rust sources and restage them automatically.
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- [x] Agent authentication (token)
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- [x] Hide per-thread entries; only show processes
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- [x] Sort top processes in the TUI
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- [ ] Configurable refresh intervals (client)
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- [x] Configurable refresh intervals (client)
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- [ ] Export metrics to file
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- [x] TLS / WSS support (self‑signed server cert + client pinning)
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- [x] Split processes/disks to separate WS calls with independent cadences (already logical on client; formalize API)
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- [ ] Outage notifications and reconnect.
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- [ ] Per process detailed statistics pane
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- [ ] cleanup of Disks section, properly display physical disks / partitions, remove duplicate entries
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---
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204
docs/cross-compiling.md
Normal file
204
docs/cross-compiling.md
Normal file
@ -0,0 +1,204 @@
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# Cross-Compiling socktop_agent for Raspberry Pi
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This guide explains how to cross-compile the socktop_agent on various host systems and deploy it to a Raspberry Pi. Cross-compiling is particularly useful for older or resource-constrained Pi models where native compilation might be slow.
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## Cross-Compilation Host Setup
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Choose your host operating system:
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- [Debian/Ubuntu](#debianubuntu-based-systems)
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- [Arch Linux](#arch-linux-based-systems)
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- [macOS](#macos)
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- [Windows](#windows)
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## Debian/Ubuntu Based Systems
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### Prerequisites
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Install the cross-compilation toolchain for your target Raspberry Pi architecture:
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```bash
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# For 64-bit Raspberry Pi (aarch64)
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sudo apt update
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sudo apt install gcc-aarch64-linux-gnu libc6-dev-arm64-cross libdrm-dev:arm64
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# For 32-bit Raspberry Pi (armv7)
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sudo apt update
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sudo apt install gcc-arm-linux-gnueabihf libc6-dev-armhf-cross libdrm-dev:armhf
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```
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### Setup Rust Cross-Compilation Targets
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```bash
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# For 64-bit Raspberry Pi
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rustup target add aarch64-unknown-linux-gnu
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# For 32-bit Raspberry Pi
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rustup target add armv7-unknown-linux-gnueabihf
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```
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### Configure Cargo for Cross-Compilation
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Create or edit `~/.cargo/config.toml`:
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```toml
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[target.aarch64-unknown-linux-gnu]
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linker = "aarch64-linux-gnu-gcc"
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[target.armv7-unknown-linux-gnueabihf]
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linker = "arm-linux-gnueabihf-gcc"
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```
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## Arch Linux Based Systems
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### Prerequisites
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Install the cross-compilation toolchain using pacman and AUR:
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```bash
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# Install base dependencies
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sudo pacman -S base-devel
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# For 64-bit Raspberry Pi (aarch64)
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sudo pacman -S aarch64-linux-gnu-gcc
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# Install libdrm for aarch64 using an AUR helper (e.g., yay, paru)
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yay -S aarch64-linux-gnu-libdrm
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# For 32-bit Raspberry Pi (armv7)
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sudo pacman -S arm-linux-gnueabihf-gcc
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# Install libdrm for armv7 using an AUR helper
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yay -S arm-linux-gnueabihf-libdrm
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```
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### Setup Rust Cross-Compilation Targets
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```bash
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# For 64-bit Raspberry Pi
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rustup target add aarch64-unknown-linux-gnu
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# For 32-bit Raspberry Pi
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rustup target add armv7-unknown-linux-gnueabihf
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```
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### Configure Cargo for Cross-Compilation
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Create or edit `~/.cargo/config.toml`:
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```toml
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[target.aarch64-unknown-linux-gnu]
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linker = "aarch64-linux-gnu-gcc"
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[target.armv7-unknown-linux-gnueabihf]
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linker = "arm-linux-gnueabihf-gcc"
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```
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## macOS
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The recommended approach for cross-compiling from macOS is to use Docker:
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```bash
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# Install Docker
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brew install --cask docker
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# Pull a cross-compilation Docker image
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docker pull messense/rust-musl-cross:armv7-musleabihf # For 32-bit Pi
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docker pull messense/rust-musl-cross:aarch64-musl # For 64-bit Pi
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```
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### Using Docker for Cross-Compilation
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```bash
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# Navigate to your socktop project directory
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cd path/to/socktop
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# For 64-bit Raspberry Pi
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docker run --rm -it -v "$(pwd)":/home/rust/src messense/rust-musl-cross:aarch64-musl cargo build --release --target aarch64-unknown-linux-musl -p socktop_agent
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# For 32-bit Raspberry Pi
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docker run --rm -it -v "$(pwd)":/home/rust/src messense/rust-musl-cross:armv7-musleabihf cargo build --release --target armv7-unknown-linux-musleabihf -p socktop_agent
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```
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The compiled binaries will be available in your local target directory.
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## Windows
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The recommended approach for Windows is to use Windows Subsystem for Linux (WSL2):
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1. Install WSL2 with a Debian/Ubuntu distribution by following the [official Microsoft documentation](https://docs.microsoft.com/en-us/windows/wsl/install).
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2. Once WSL2 is set up with a Debian/Ubuntu distribution, open your WSL terminal and follow the [Debian/Ubuntu instructions](#debianubuntu-based-systems) above.
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## Cross-Compile the Agent
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After setting up your environment, build the socktop_agent for your target Raspberry Pi:
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```bash
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# For 64-bit Raspberry Pi
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cargo build --release --target aarch64-unknown-linux-gnu -p socktop_agent
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# For 32-bit Raspberry Pi
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cargo build --release --target armv7-unknown-linux-gnueabihf -p socktop_agent
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```
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## Transfer the Binary to Your Raspberry Pi
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Use SCP to transfer the compiled binary to your Raspberry Pi:
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```bash
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# For 64-bit Raspberry Pi
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scp target/aarch64-unknown-linux-gnu/release/socktop_agent pi@raspberry-pi-ip:~/
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# For 32-bit Raspberry Pi
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scp target/armv7-unknown-linux-gnueabihf/release/socktop_agent pi@raspberry-pi-ip:~/
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```
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Replace `raspberry-pi-ip` with your Raspberry Pi's IP address and `pi` with your username.
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## Install Dependencies on the Raspberry Pi
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SSH into your Raspberry Pi and install the required dependencies:
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```bash
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ssh pi@raspberry-pi-ip
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# For Raspberry Pi OS (Debian-based)
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sudo apt update
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sudo apt install libdrm-dev libdrm-amdgpu1
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# For Arch Linux ARM
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sudo pacman -Syu
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sudo pacman -S libdrm
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```
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## Make the Binary Executable and Install
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```bash
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chmod +x ~/socktop_agent
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# Optional: Install system-wide
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sudo install -o root -g root -m 0755 ~/socktop_agent /usr/local/bin/socktop_agent
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# Optional: Set up as a systemd service
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sudo install -o root -g root -m 0644 ~/socktop-agent.service /etc/systemd/system/socktop-agent.service
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sudo systemctl daemon-reload
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sudo systemctl enable --now socktop-agent
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```
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## Troubleshooting
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If you encounter issues with the cross-compiled binary:
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1. **Incorrect Architecture**: Ensure you've chosen the correct target for your Raspberry Pi model:
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- For Raspberry Pi 2: use `armv7-unknown-linux-gnueabihf`
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- For Raspberry Pi 3/4/5 in 64-bit mode: use `aarch64-unknown-linux-gnu`
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- For Raspberry Pi 3/4/5 in 32-bit mode: use `armv7-unknown-linux-gnueabihf`
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2. **Dependency Issues**: Check for missing libraries:
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```bash
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ldd ~/socktop_agent
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```
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3. **Run with Backtrace**: Get detailed error information:
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```bash
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RUST_BACKTRACE=1 ~/socktop_agent
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```
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@ -30,3 +30,363 @@ Environment toggles:
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Systemd unit example & full docs:
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https://github.com/jasonwitty/socktop
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## WebSocket API Integration Guide
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The socktop_agent exposes a WebSocket API that can be directly integrated with your own applications. This allows you to build custom monitoring dashboards or analysis tools using the agent's metrics.
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### WebSocket Endpoint
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```
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ws://HOST:PORT/ws # Without TLS
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wss://HOST:PORT/ws # With TLS
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```
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With authentication token (if configured):
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```
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ws://HOST:PORT/ws?token=YOUR_TOKEN
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wss://HOST:PORT/ws?token=YOUR_TOKEN
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```
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### Communication Protocol
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All communication uses JSON format for requests and responses, except for the process list which uses Protocol Buffers (protobuf) format with optional gzip compression.
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#### Request Types
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Send a JSON message with a `type` field to request specific metrics:
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```json
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{"type": "metrics"} // Request fast-changing metrics (CPU, memory, network)
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{"type": "disks"} // Request disk information
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{"type": "processes"} // Request process list (returns protobuf)
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```
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#### Response Formats
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1. **Fast Metrics** (JSON):
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```json
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{
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"cpu_total": 12.4,
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"cpu_per_core": [11.2, 15.7],
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"mem_total": 33554432,
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"mem_used": 18321408,
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"swap_total": 0,
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"swap_used": 0,
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"hostname": "myserver",
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"cpu_temp_c": 42.5,
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"networks": [{"name":"eth0","received":12345678,"transmitted":87654321}],
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"gpus": [{"name":"nvidia-0","usage":56.7,"memory_total":8589934592,"memory_used":1073741824,"temp_c":65.0}]
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}
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```
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2. **Disks** (JSON):
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```json
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[
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{"name":"nvme0n1p2","total":512000000000,"available":320000000000},
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{"name":"sda1","total":1000000000000,"available":750000000000}
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]
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```
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3. **Processes** (Protocol Buffers):
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Processes are returned in Protocol Buffers format, optionally gzip-compressed for large process lists. The protobuf schema is:
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|
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```protobuf
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syntax = "proto3";
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message Process {
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uint32 pid = 1;
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string name = 2;
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float cpu_usage = 3;
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uint64 mem_bytes = 4;
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}
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message ProcessList {
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uint32 process_count = 1;
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repeated Process processes = 2;
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}
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```
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### Example Integration (JavaScript/Node.js)
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```javascript
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const WebSocket = require('ws');
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// Connect to the agent
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const ws = new WebSocket('ws://localhost:3000/ws');
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ws.on('open', function open() {
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console.log('Connected to socktop_agent');
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// Request metrics immediately on connection
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ws.send(JSON.stringify({type: 'metrics'}));
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// Set up regular polling
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setInterval(() => {
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ws.send(JSON.stringify({type: 'metrics'}));
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}, 1000);
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// Request processes every 3 seconds
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setInterval(() => {
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ws.send(JSON.stringify({type: 'processes'}));
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}, 3000);
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});
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ws.on('message', function incoming(data) {
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// Check if the response is JSON or binary (protobuf)
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try {
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const jsonData = JSON.parse(data);
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console.log('Received JSON data:', jsonData);
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} catch (e) {
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console.log('Received binary data (protobuf), length:', data.length);
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// Process binary protobuf data with a library like protobufjs
|
||||
}
|
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});
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|
||||
ws.on('close', function close() {
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console.log('Disconnected from socktop_agent');
|
||||
});
|
||||
```
|
||||
|
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### Example Integration (Python)
|
||||
|
||||
```python
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import json
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import asyncio
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||||
import websockets
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||||
|
||||
async def monitor_system():
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uri = "ws://localhost:3000/ws"
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async with websockets.connect(uri) as websocket:
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print("Connected to socktop_agent")
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|
||||
# Request initial metrics
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await websocket.send(json.dumps({"type": "metrics"}))
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# Set up regular polling
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||||
while True:
|
||||
# Request metrics
|
||||
await websocket.send(json.dumps({"type": "metrics"}))
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|
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# Receive and process response
|
||||
response = await websocket.recv()
|
||||
|
||||
# Check if response is JSON or binary (protobuf)
|
||||
try:
|
||||
data = json.loads(response)
|
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print(f"CPU: {data['cpu_total']}%, Memory: {data['mem_used']/data['mem_total']*100:.1f}%")
|
||||
except json.JSONDecodeError:
|
||||
print(f"Received binary data, length: {len(response)}")
|
||||
# Process binary protobuf data with a library like protobuf
|
||||
|
||||
# Wait before next poll
|
||||
await asyncio.sleep(1)
|
||||
|
||||
asyncio.run(monitor_system())
|
||||
```
|
||||
|
||||
### Notes for Integration
|
||||
|
||||
1. **Error Handling**: The WebSocket connection may close unexpectedly; implement reconnection logic in your client.
|
||||
|
||||
2. **Rate Limiting**: Avoid excessive polling that could impact the system being monitored. Recommended intervals:
|
||||
- Metrics: 500ms or slower
|
||||
- Processes: 2000ms or slower
|
||||
- Disks: 5000ms or slower
|
||||
|
||||
3. **Authentication**: If the agent is configured with a token, always include it in the WebSocket URL.
|
||||
|
||||
4. **Protocol Buffers Handling**: For processing the binary process list data, use a Protocol Buffers library for your language and the schema provided in the `proto/processes.proto` file.
|
||||
|
||||
5. **Compression**: Process lists may be gzip-compressed. Check if the response starts with the gzip magic bytes (`0x1f, 0x8b`) and decompress if necessary.
|
||||
|
||||
## LLM Integration Guide
|
||||
|
||||
If you're using an LLM to generate code for integrating with socktop_agent, this section provides structured information to help the model understand the API better.
|
||||
|
||||
### API Schema
|
||||
|
||||
```yaml
|
||||
# WebSocket API Schema for socktop_agent
|
||||
endpoint: ws://HOST:PORT/ws or wss://HOST:PORT/ws (with TLS)
|
||||
authentication:
|
||||
type: query parameter
|
||||
parameter: token
|
||||
example: ws://HOST:PORT/ws?token=YOUR_TOKEN
|
||||
|
||||
requests:
|
||||
- type: metrics
|
||||
format: JSON
|
||||
example: {"type": "metrics"}
|
||||
description: Fast-changing metrics (CPU, memory, network)
|
||||
|
||||
- type: disks
|
||||
format: JSON
|
||||
example: {"type": "disks"}
|
||||
description: Disk information
|
||||
|
||||
- type: processes
|
||||
format: JSON
|
||||
example: {"type": "processes"}
|
||||
description: Process list (returns protobuf)
|
||||
|
||||
responses:
|
||||
- request_type: metrics
|
||||
format: JSON
|
||||
schema:
|
||||
cpu_total: float # percentage of total CPU usage
|
||||
cpu_per_core: [float] # array of per-core CPU usage percentages
|
||||
mem_total: uint64 # total memory in bytes
|
||||
mem_used: uint64 # used memory in bytes
|
||||
swap_total: uint64 # total swap in bytes
|
||||
swap_used: uint64 # used swap in bytes
|
||||
hostname: string # system hostname
|
||||
cpu_temp_c: float? # CPU temperature in Celsius (optional)
|
||||
networks: [
|
||||
{
|
||||
name: string # network interface name
|
||||
received: uint64 # total bytes received
|
||||
transmitted: uint64 # total bytes transmitted
|
||||
}
|
||||
]
|
||||
gpus: [
|
||||
{
|
||||
name: string # GPU device name
|
||||
usage: float # GPU usage percentage
|
||||
memory_total: uint64 # total GPU memory in bytes
|
||||
memory_used: uint64 # used GPU memory in bytes
|
||||
temp_c: float # GPU temperature in Celsius
|
||||
}
|
||||
]?
|
||||
|
||||
- request_type: disks
|
||||
format: JSON
|
||||
schema:
|
||||
[
|
||||
{
|
||||
name: string # disk name
|
||||
total: uint64 # total space in bytes
|
||||
available: uint64 # available space in bytes
|
||||
}
|
||||
]
|
||||
|
||||
- request_type: processes
|
||||
format: Protocol Buffers (optionally gzip-compressed)
|
||||
schema: See protobuf definition below
|
||||
```
|
||||
|
||||
### Protobuf Schema (processes.proto)
|
||||
|
||||
```protobuf
|
||||
syntax = "proto3";
|
||||
|
||||
message Process {
|
||||
uint32 pid = 1;
|
||||
string name = 2;
|
||||
float cpu_usage = 3;
|
||||
uint64 mem_bytes = 4;
|
||||
}
|
||||
|
||||
message ProcessList {
|
||||
uint32 process_count = 1;
|
||||
repeated Process processes = 2;
|
||||
}
|
||||
```
|
||||
|
||||
### Step-by-Step Integration Pseudocode
|
||||
|
||||
```
|
||||
1. Establish WebSocket connection to ws://HOST:PORT/ws
|
||||
- Add token if required: ws://HOST:PORT/ws?token=YOUR_TOKEN
|
||||
|
||||
2. For regular metrics updates:
|
||||
- Send: {"type": "metrics"}
|
||||
- Parse JSON response
|
||||
- Extract CPU, memory, network info
|
||||
|
||||
3. For disk information:
|
||||
- Send: {"type": "disks"}
|
||||
- Parse JSON response
|
||||
- Extract disk usage data
|
||||
|
||||
4. For process list:
|
||||
- Send: {"type": "processes"}
|
||||
- Check if response is binary
|
||||
- If starts with 0x1f, 0x8b bytes:
|
||||
- Decompress using gzip
|
||||
- Parse binary data using protobuf schema
|
||||
- Extract process information
|
||||
|
||||
5. Implement reconnection logic:
|
||||
- On connection close/error
|
||||
- Use exponential backoff
|
||||
|
||||
6. Respect rate limits:
|
||||
- metrics: ≥ 500ms interval
|
||||
- disks: ≥ 5000ms interval
|
||||
- processes: ≥ 2000ms interval
|
||||
```
|
||||
|
||||
### Common Implementation Patterns
|
||||
|
||||
**Pattern 1: Periodic Polling**
|
||||
```javascript
|
||||
// Set up separate timers for different metric types
|
||||
const metricsInterval = setInterval(() => ws.send(JSON.stringify({type: 'metrics'})), 500);
|
||||
const disksInterval = setInterval(() => ws.send(JSON.stringify({type: 'disks'})), 5000);
|
||||
const processesInterval = setInterval(() => ws.send(JSON.stringify({type: 'processes'})), 2000);
|
||||
|
||||
// Clean up on disconnect
|
||||
ws.on('close', () => {
|
||||
clearInterval(metricsInterval);
|
||||
clearInterval(disksInterval);
|
||||
clearInterval(processesInterval);
|
||||
});
|
||||
```
|
||||
|
||||
**Pattern 2: Processing Binary Protobuf Data**
|
||||
```javascript
|
||||
// Using protobufjs
|
||||
const root = protobuf.loadSync('processes.proto');
|
||||
const ProcessList = root.lookupType('ProcessList');
|
||||
|
||||
ws.on('message', function(data) {
|
||||
if (typeof data !== 'string') {
|
||||
// Check for gzip compression
|
||||
if (data[0] === 0x1f && data[1] === 0x8b) {
|
||||
data = gunzipSync(data); // Use appropriate decompression library
|
||||
}
|
||||
|
||||
// Decode protobuf
|
||||
const processes = ProcessList.decode(new Uint8Array(data));
|
||||
console.log(`Total processes: ${processes.process_count}`);
|
||||
processes.processes.forEach(p => {
|
||||
console.log(`PID: ${p.pid}, Name: ${p.name}, CPU: ${p.cpu_usage}%`);
|
||||
});
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
**Pattern 3: Reconnection Logic**
|
||||
```javascript
|
||||
function connect() {
|
||||
const ws = new WebSocket('ws://localhost:3000/ws');
|
||||
|
||||
ws.on('open', () => {
|
||||
console.log('Connected');
|
||||
// Start polling
|
||||
});
|
||||
|
||||
ws.on('close', () => {
|
||||
console.log('Connection lost, reconnecting...');
|
||||
setTimeout(connect, 1000); // Reconnect after 1 second
|
||||
});
|
||||
|
||||
// Handle other events...
|
||||
}
|
||||
|
||||
connect();
|
||||
```
|
||||
|
||||
Loading…
Reference in New Issue
Block a user