socktop/socktop_agent

socktop_agent (server)

Lightweight on‑demand metrics WebSocket server for the socktop TUI.

Highlights:

• Collects system metrics only when requested (keeps idle CPU <1%)
• Optional TLS (self‑signed cert auto‑generated & pinned by client)
• JSON for fast metrics / disks; protobuf (optionally gzipped) for processes
• Accurate per‑process CPU% on Linux via /proc jiffies delta
• Optional GPU & temperature metrics (disable via env vars)
• Simple token auth (?token=...) support

Run (no TLS):

cargo install socktop_agent
socktop_agent --port 3000

Enable TLS:

SOCKTOP_ENABLE_SSL=1 socktop_agent --port 8443
# cert/key stored under $XDG_DATA_HOME/socktop_agent/tls

Environment toggles:

• SOCKTOP_AGENT_GPU=0 (disable GPU collection)
• SOCKTOP_AGENT_TEMP=0 (disable temperature)
• SOCKTOP_TOKEN=secret (require token param from client)
• SOCKTOP_AGENT_METRICS_TTL_MS=250 (cache fast metrics window)
• SOCKTOP_AGENT_PROCESSES_TTL_MS=1000
• SOCKTOP_AGENT_DISKS_TTL_MS=1000

Systemd unit example & full docs: https://github.com/jasonwitty/socktop

WebSocket API Integration Guide

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.

WebSocket Endpoint

ws://HOST:PORT/ws         # Without TLS
wss://HOST:PORT/ws        # With TLS

With authentication token (if configured):

ws://HOST:PORT/ws?token=YOUR_TOKEN
wss://HOST:PORT/ws?token=YOUR_TOKEN

Communication Protocol

All communication uses JSON format for requests and responses, except for the process list which uses Protocol Buffers (protobuf) format with optional gzip compression.

Request Types

Send a JSON message with a type field to request specific metrics:

{"type": "metrics"}       // Request fast-changing metrics (CPU, memory, network)
{"type": "disks"}         // Request disk information
{"type": "processes"}     // Request process list (returns protobuf)

Response Formats

1. Fast Metrics (JSON):

{
  "cpu_total": 12.4,
  "cpu_per_core": [11.2, 15.7],
  "mem_total": 33554432,
  "mem_used": 18321408,
  "swap_total": 0,
  "swap_used": 0,
  "hostname": "myserver",
  "cpu_temp_c": 42.5,
  "networks": [{"name":"eth0","received":12345678,"transmitted":87654321}],
  "gpus": [{"name":"nvidia-0","usage":56.7,"memory_total":8589934592,"memory_used":1073741824,"temp_c":65.0}]
}

2. Disks (JSON):

[
  {"name":"nvme0n1p2","total":512000000000,"available":320000000000},
  {"name":"sda1","total":1000000000000,"available":750000000000}
]

3. Processes (Protocol Buffers):

Processes are returned in Protocol Buffers format, optionally gzip-compressed for large process lists. The protobuf schema is:

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;
}

Example Integration (JavaScript/Node.js)

const WebSocket = require('ws');

// Connect to the agent
const ws = new WebSocket('ws://localhost:3000/ws');

ws.on('open', function open() {
  console.log('Connected to socktop_agent');
  
  // Request metrics immediately on connection
  ws.send(JSON.stringify({type: 'metrics'}));
  
  // Set up regular polling
  setInterval(() => {
    ws.send(JSON.stringify({type: 'metrics'}));
  }, 1000);
  
  // Request processes every 3 seconds
  setInterval(() => {
    ws.send(JSON.stringify({type: 'processes'}));
  }, 3000);
});

ws.on('message', function incoming(data) {
  // Check if the response is JSON or binary (protobuf)
  try {
    const jsonData = JSON.parse(data);
    console.log('Received JSON data:', jsonData);
  } catch (e) {
    console.log('Received binary data (protobuf), length:', data.length);
    // Process binary protobuf data with a library like protobufjs
  }
});

ws.on('close', function close() {
  console.log('Disconnected from socktop_agent');
});

Example Integration (Python)

import json
import asyncio
import websockets

async def monitor_system():
    uri = "ws://localhost:3000/ws"
    async with websockets.connect(uri) as websocket:
        print("Connected to socktop_agent")
        
        # Request initial metrics
        await websocket.send(json.dumps({"type": "metrics"}))
        
        # Set up regular polling
        while True:
            # Request metrics
            await websocket.send(json.dumps({"type": "metrics"}))
            
            # Receive and process response
            response = await websocket.recv()
            
            # Check if response is JSON or binary (protobuf)
            try:
                data = json.loads(response)
                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

# 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)

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

// 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

// 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

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();