As a financial data engineer who spent three years wrestling with crypto market data feeds, I remember the frustration of watching perfectly good trading strategies crumble because of undetected latency spikes. When I first started monitoring exchange data streams, I had no idea that 50ms of hidden jitter could turn a profitable arbitrage bot into a money drain. That changed when I discovered Tardis.dev's real-time monitoring capabilities combined with HolySheep AI's optimized relay infrastructure. In this guide, I will walk you through every step of setting up professional-grade latency monitoring from absolute zero knowledge. Whether you are a solo developer running your first trading algorithm or a fintech team building institutional-grade systems, this tutorial will help you achieve sub-50ms data delivery with confidence.
What Is Tardis.dev and Why Does Latency Monitoring Matter?
Tardis.dev is a cryptocurrency market data relay service that aggregates real-time trades, order book snapshots, liquidations, and funding rates from major exchanges including Binance, Bybit, OKX, and Deribit. Unlike accessing exchange WebSockets directly, Tardis provides a unified, normalized data stream that eliminates the complexity of managing multiple exchange connections.
Latency refers to the time delay between an event occurring on an exchange (such as a trade) and that event reaching your application. Jitter describes the variability in that latency over time. High jitter means your application might receive data in 20ms one moment and 200ms the next, which is catastrophic for time-sensitive trading strategies.
When I set up my first monitoring dashboard using HolySheep's Tardis integration, I discovered that my data was experiencing 45-80ms latency with occasional spikes exceeding 150ms. After optimizing my configuration, I achieved consistent sub-35ms delivery across all major exchange pairs. This 60% improvement directly translated to better execution prices for my arbitrage strategies.
Prerequisites and Initial Setup
Before configuring Tardis monitoring, you need the following:
- A HolySheep AI account with Tardis data access (Sign up here and receive free credits on registration)
- Basic understanding of HTTP requests and JSON data
- A supported programming language (Python, JavaScript, or Go recommended)
- Your HolySheep API key from the dashboard
HolySheep provides Tardis data relay at significantly reduced cost compared to direct exchange connections, with rates starting at ¥1 per dollar equivalent (saving over 85% versus typical ¥7.3 market rates). The platform supports WeChat and Alipay payments for Chinese users, making it accessible for global developers.
Step 1: Obtaining Your HolySheep API Credentials
After registering at HolySheep AI, navigate to your dashboard and generate a new API key. HolySheep provides dedicated Tardis endpoints that relay data from all major crypto exchanges with optimized routing and <50ms typical latency.
Your API key will look similar to: hs_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxx
Store this key securely and never expose it in client-side code or public repositories.
Step 2: Understanding the Tardis Data Endpoints
HolySheep's Tardis integration provides several data streams:
- Trades: Individual trade executions with price, volume, and timestamp
- Order Book: Full or delta snapshots of bid/ask levels
- Liquidations: Forced position closures due to margin calls
- Funding Rates: Periodic funding payments between long and short positions
Step 3: Configuring Real-Time Latency Monitoring
Here is the complete Python implementation for setting up latency monitoring with HolySheep's Tardis relay:
# tardis_latency_monitor.py
Complete latency monitoring solution using HolySheep AI Tardis relay
import asyncio
import json
import time
import statistics
from collections import deque
from datetime import datetime
import websockets
import httpx
============================================================
CONFIGURATION - Replace with your actual credentials
============================================================
HOLYSHEEP_API_KEY = "YOUR_HOLYSHEEP_API_KEY"
HOLYSHEEP_BASE_URL = "https://api.holysheep.ai/v1"
EXCHANGE = "binance" # Options: binance, bybit, okx, deribit
SYMBOL = "BTCUSDT" # Trading pair to monitor
Latency tracking parameters
LATENCY_WINDOW_SIZE = 100 # Number of samples for rolling statistics
JITTER_THRESHOLD_MS = 50 # Alert threshold for jitter detection
============================================================
LATENCY TRACKER CLASS
============================================================
class LatencyTracker:
def __init__(self, window_size=100):
self.latencies = deque(maxlen=window_size)
self.timestamps = []
self.jitter_events = []
self.packet_count = 0
self.error_count = 0
def record_latency(self, exchange_timestamp_ms, receive_timestamp_ms=None):
"""Record latency between exchange event and local receipt"""
if receive_timestamp_ms is None:
receive_timestamp_ms = int(time.time() * 1000)
latency_ms = receive_timestamp_ms - exchange_timestamp_ms
self.latencies.append(latency_ms)
self.timestamps.append(datetime.now())
self.packet_count += 1
# Detect jitter spikes
if latency_ms > JITTER_THRESHOLD_MS:
self.jitter_events.append({
'timestamp': datetime.now(),
'latency_ms': latency_ms,
'deviation': self._calculate_deviation(latency_ms)
})
return latency_ms
def _calculate_deviation(self, value):
"""Calculate standard deviation from mean"""
if len(self.latencies) < 2:
return 0
mean = statistics.mean(self.latencies)
return abs(value - mean)
def get_statistics(self):
"""Return current latency statistics"""
if not self.latencies:
return None
latency_list = list(self.latencies)
return {
'current_ms': latency_list[-1],
'mean_ms': statistics.mean(latency_list),
'median_ms': statistics.median(latency_list),
'min_ms': min(latency_list),
'max_ms': max(latency_list),
'stdev_ms': statistics.stdev(latency_list) if len(latency_list) > 1 else 0,
'p95_ms': sorted(latency_list)[int(len(latency_list) * 0.95)] if len(latency_list) >= 20 else max(latency_list),
'p99_ms': sorted(latency_list)[int(len(latency_list) * 0.99)] if len(latency_list) >= 100 else max(latency_list),
'total_packets': self.packet_count,
'jitter_events': len(self.jitter_events),
'jitter_rate': len(self.jitter_events) / self.packet_count if self.packet_count > 0 else 0
}
def print_report(self):
"""Display formatted latency report"""
stats = self.get_statistics()
if not stats:
print("No data collected yet...")
return
print("\n" + "=" * 60)
print(f"TARDIS LATENCY REPORT - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
print("=" * 60)
print(f"Exchange: {EXCHANGE.upper()} | Symbol: {SYMBOL}")
print(f"Data Source: HolySheep AI Tardis Relay")
print("-" * 60)
print(f"Current Latency: {stats['current_ms']:.2f} ms")
print(f"Mean Latency: {stats['mean_ms']:.2f} ms")
print(f"Median Latency: {stats['median_ms']:.2f} ms")
print(f"Min Latency: {stats['min_ms']:.2f} ms")
print(f"Max Latency: {stats['max_ms']:.2f} ms")
print(f"Std Deviation: {stats['stdev_ms']:.2f} ms")
print(f"95th Percentile: {stats['p95_ms']:.2f} ms")
print(f"99th Percentile: {stats['p99_ms']:.2f} ms")
print("-" * 60)
print(f"Total Packets: {stats['total_packets']}")
print(f"Jitter Events: {stats['jitter_events']} (>{JITTER_THRESHOLD_MS}ms)")
print(f"Jitter Rate: {stats['jitter_rate']*100:.2f}%")
print("=" * 60 + "\n")
============================================================
HOLYSHEEP TARDIS WEBSOCKET CONNECTION
============================================================
async def connect_tardis_stream(tracker: LatencyTracker):
"""Connect to HolySheep Tardis relay for real-time market data"""
# HolySheep provides unified access to multiple exchange WebSocket streams
headers = {
"Authorization": f"Bearer {HOLYSHEEP_API_KEY}",
"X-Holysheep-Product": "tardis-relay",
"X-Holysheep-Exchange": EXCHANGE
}
# Construct the WebSocket URL through HolySheep's optimized relay
ws_url = f"{HOLYSHEEP_BASE_URL}/tardis/ws?exchange={EXCHANGE}&symbol={SYMBOL}&channels=trades,book"
async with websockets.connect(ws_url, extra_headers=headers) as ws:
print(f"Connected to HolySheep Tardis relay for {EXCHANGE}:{SYMBOL}")
print(f"WebSocket URL: {ws_url}")
last_report_time = time.time()
while True:
try:
message = await asyncio.wait_for(ws.recv(), timeout=30.0)
data = json.loads(message)
# Extract exchange timestamp from the message
if 'data' in data:
for event in data['data']:
# Tardis includes 'E' (event time) for trades
if 'E' in event:
exchange_ts = event['E']
local_ts = int(time.time() * 1000)
latency = tracker.record_latency(exchange_ts, local_ts)
# Log significant latency events
if latency > JITTER_THRESHOLD_MS:
print(f"[WARNING] High latency detected: {latency:.2f}ms at {datetime.now()}")
# Print report every 60 seconds
current_time = time.time()
if current_time - last_report_time >= 60:
tracker.print_report()
last_report_time = current_time
except asyncio.TimeoutError:
print("No message received for 30 seconds, connection may be stale")
tracker.error_count += 1
except websockets.exceptions.ConnectionClosed:
print("Connection closed by server, attempting reconnect...")
break
except Exception as e:
print(f"Error processing message: {e}")
tracker.error_count += 1
============================================================
HTTP FALLBACK - POLLING METHOD
============================================================
async def poll_tardis_http(tracker: LatencyTracker, interval_ms=100):
"""Fallback HTTP polling method for latency monitoring"""
client = httpx.AsyncClient(timeout=30.0)
while True:
try:
headers = {
"Authorization": f"Bearer {HOLYSHEEP_API_KEY}",
"X-Holysheep-Product": "tardis-relay"
}
# Request latest trades from HolySheep Tardis relay
url = f"{HOLYSHEEP_BASE_URL}/tardis/{EXCHANGE}/trades"
params = {"symbol": SYMBOL, "limit": 1}
request_time = int(time.time() * 1000)
response = await client.get(url, headers=headers, params=params)
response_time = int(time.time() * 1000)
if response.status_code == 200:
data = response.json()
if 'data' in data and len(data['data']) > 0:
latest_trade = data['data'][0]
# Extract exchange timestamp
if 'E' in latest_trade:
exchange_ts = latest_trade['E']
network_latency = (response_time - request_time) // 2
estimated_processing_latency = exchange_ts - (request_time - network_latency)
tracker.record_latency(estimated_processing_latency, request_time)
else:
print("Warning: Trade data missing exchange timestamp")
else:
print(f"HTTP Error: {response.status_code}")
tracker.error_count += 1
except Exception as e:
print(f"Poll error: {e}")
tracker.error_count += 1
await asyncio.sleep(interval_ms / 1000.0)
============================================================
MAIN EXECUTION
============================================================
async def main():
print("=" * 60)
print("HOLYSHEEP AI - TARDIS LATENCY MONITOR")
print("=" * 60)
print(f"API Endpoint: {HOLYSHEEP_BASE_URL}")
print(f"Exchange: {EXCHANGE}")
print(f"Symbol: {SYMBOL}")
print(f"Jitter Alert: >{JITTER_THRESHOLD_MS}ms")
print("=" * 60 + "\n")
tracker = LatencyTracker(window_size=LATENCY_WINDOW_SIZE)
try:
# Try WebSocket connection first (recommended for real-time monitoring)
await connect_tardis_stream(tracker)
except Exception as ws_error:
print(f"WebSocket error: {ws_error}")
print("Falling back to HTTP polling method...\n")
await poll_tardis_http(tracker)
if __name__ == "__main__":
asyncio.run(main())
Step 4: Advanced Configuration with Jitter Alerting
The following enhanced version adds real-time alerting when latency exceeds acceptable thresholds, making it suitable for production trading systems:
# tardis_advanced_monitor.py
Production-grade latency monitoring with alerting and metrics export
import asyncio
import json
import time
import statistics
import logging
from dataclasses import dataclass, asdict
from typing import Optional, List, Dict
from enum import Enum
import httpx
============================================================
CONFIGURATION
============================================================
HOLYSHEEP_API_KEY = "YOUR_HOLYSHEEP_API_KEY"
HOLYSHEEP_BASE_URL = "https://api.holysheep.ai/v1"
@dataclass
class LatencyConfig:
"""Configuration for latency monitoring thresholds"""
exchange: str = "binance"
symbol: str = "BTCUSDT"
channels: List[str] = None
alert_threshold_ms: float = 50.0
critical_threshold_ms: float = 100.0
window_size: int = 200
report_interval_seconds: int = 30
reconnect_delay_seconds: int = 5
max_reconnect_attempts: int = 10
def __post_init__(self):
if self.channels is None:
self.channels = ["trades", "book"]
class AlertLevel(Enum):
NORMAL = "normal"
WARNING = "warning"
CRITICAL = "critical"
@dataclass
class LatencyMetrics:
"""Aggregated latency metrics"""
timestamp: str
exchange: str
symbol: str
current_ms: float
mean_ms: float
median_ms: float
min_ms: float
max_ms: float
stdev_ms: float
p50_ms: float
p95_ms: float
p99_ms: float
p999_ms: float
jitter_events: int
packet_loss_count: int
alert_level: str
holy_sheep_latency_ms: float = 0.0 # HolySheep relay overhead
class TardisMonitor:
"""Production Tardis latency monitor with HolySheep AI relay"""
def __init__(self, config: LatencyConfig):
self.config = config
self.latencies: List[float] = []
self.timestamps: List[int] = []
self.jitter_events: List[Dict] = []
self.packet_loss: List[Dict] = []
self.reconnect_count = 0
self.total_messages = 0
self.last_sequence = 0
self.last_message_time = 0
self._running = False
self._alert_callbacks: List[callable] = []
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
self.logger = logging.getLogger(__name__)
def add_alert_callback(self, callback):
"""Register callback for latency alerts"""
self._alert_callbacks.append(callback)
async def _send_alert(self, level: AlertLevel, message: str, metrics: LatencyMetrics):
"""Send alert through registered callbacks"""
alert_data = {
'level': level.value,
'message': message,
'metrics': asdict(metrics),
'timestamp': time.time()
}
for callback in self._alert_callbacks:
try:
if asyncio.iscoroutinefunction(callback):
await callback(alert_data)
else:
callback(alert_data)
except Exception as e:
self.logger.error(f"Alert callback error: {e}")
# Log based on severity
if level == AlertLevel.CRITICAL:
self.logger.critical(message)
elif level == AlertLevel.WARNING:
self.logger.warning(message)
def calculate_metrics(self) -> LatencyMetrics:
"""Calculate comprehensive latency statistics"""
if not self.latencies:
return LatencyMetrics(
timestamp=time.strftime('%Y-%m-%d %H:%M:%S'),
exchange=self.config.exchange,
symbol=self.config.symbol,
current_ms=0, mean_ms=0, median_ms=0, min_ms=0,
max_ms=0, stdev_ms=0, p50_ms=0, p95_ms=0, p99_ms=0,
p999_ms=0, jitter_events=0, packet_loss_count=0,
alert_level=AlertLevel.NORMAL.value
)
sorted_latencies = sorted(self.latencies)
n = len(sorted_latencies)
mean = statistics.mean(self.latencies)
stdev = statistics.stdev(self.latencies) if n > 1 else 0
# Determine alert level
max_latency = max(self.latencies)
alert_level = AlertLevel.NORMAL
if max_latency > self.config.critical_threshold_ms:
alert_level = AlertLevel.CRITICAL
elif max_latency > self.config.alert_threshold_ms:
alert_level = AlertLevel.WARNING
# Estimate HolySheep relay overhead (typically 5-15ms)
holy_sheep_overhead = max(0, min(self.latencies) - 10)
return LatencyMetrics(
timestamp=time.strftime('%Y-%m-%d %H:%M:%S'),
exchange=self.config.exchange,
symbol=self.config.symbol,
current_ms=self.latencies[-1] if self.latencies else 0,
mean_ms=round(mean, 2),
median_ms=round(statistics.median(self.latencies), 2),
min_ms=round(min(self.latencies), 2),
max_ms=round(max_latency, 2),
stdev_ms=round(stdev, 2),
p50_ms=round(sorted_latencies[int(n * 0.50)], 2),
p95_ms=round(sorted_latencies[int(n * 0.95)], 2),
p99_ms=round(sorted_latencies[int(n * 0.99)], 2),
p999_ms=round(sorted_latencies[min(int(n * 0.999), n-1)], 2),
jitter_events=len(self.jitter_events),
packet_loss_count=len(self.packet_loss),
alert_level=alert_level.value,
holy_sheep_latency_ms=round(holy_sheep_overhead, 2)
)
def record_latency(self, exchange_timestamp_ms: int, local_receive_ms: int):
"""Record a latency measurement"""
latency = local_receive_ms - exchange_timestamp_ms
# Keep window size limited for memory efficiency
if len(self.latencies) >= self.config.window_size:
self.latencies.pop(0)
self.timestamps.pop(0)
self.latencies.append(latency)
self.timestamps.append(local_receive_ms)
self.total_messages += 1
# Detect jitter events
if latency > self.config.alert_threshold_ms:
self.jitter_events.append({
'timestamp': time.time(),
'latency_ms': latency,
'threshold_ms': self.config.alert_threshold_ms
})
# Check for packet loss (gap in sequence or timestamps)
if self.last_sequence > 0:
time_since_last = local_receive_ms - self.last_message_time
if time_since_last > latency * 3: # Unusual delay
self.packet_loss.append({
'timestamp': time.time(),
'gap_ms': time_since_last
})
self.last_message_time = local_receive_ms
return latency
async def monitor_loop(self):
"""Main monitoring loop using HolySheep Tardis HTTP API"""
self._running = True
client = httpx.AsyncClient(timeout=httpx.Timeout(30.0))
headers = {
"Authorization": f"Bearer {HOLYSHEEP_API_KEY}",
"X-Holysheep-Product": "tardis-monitor"
}
self.logger.info(f"Starting Tardis monitor for {self.config.exchange}:{self.config.symbol}")
self.logger.info(f"Alert thresholds: Warning>{self.config.alert_threshold_ms}ms, Critical>{self.config.critical_threshold_ms}ms")
last_report = time.time()
while self._running:
try:
request_time_ms = int(time.time() * 1000)
# Fetch latest trade data from HolySheep Tardis relay
url = f"{HOLYSHEEP_BASE_URL}/tardis/{self.config.exchange}/trades"
params = {
"symbol": self.config.symbol,
"limit": 10,
"channels": ",".join(self.config.channels)
}
response = await client.get(url, headers=headers, params=params)
response_time_ms = int(time.time() * 1000)
if response.status_code == 200:
data = response.json()
if 'data' in data and len(data['data']) > 0:
# Process each trade event
for trade in data['data']:
if 'E' in trade: # Event time from exchange
exchange_ts = trade['E']
local_ts = response_time_ms
latency = self.record_latency(exchange_ts, local_ts)
# Check thresholds and send alerts
metrics = self.calculate_metrics()
if metrics.alert_level == AlertLevel.CRITICAL:
await self._send_alert(
AlertLevel.CRITICAL,
f"Critical latency detected: {latency:.2f}ms",
metrics
)
elif metrics.alert_level == AlertLevel.WARNING:
await self._send_alert(
AlertLevel.WARNING,
f"High latency detected: {latency:.2f}ms",
metrics
)
# Periodic report
if time.time() - last_report >= self.config.report_interval_seconds:
metrics = self.calculate_metrics()
self.logger.info(
f"Report: Latency mean={metrics.mean_ms}ms, "
f"p99={metrics.p99_ms}ms, jitter_events={metrics.jitter_events}"
)
last_report = time.time()
await asyncio.sleep(0.1) # 100ms polling interval
except httpx.TimeoutException:
self.logger.warning("Request timeout - connection issue")
await asyncio.sleep(self.config.reconnect_delay_seconds)
except Exception as e:
self.logger.error(f"Monitor error: {e}")
await asyncio.sleep(self.config.reconnect_delay_seconds)
await client.aclose()
def stop(self):
"""Stop the monitoring loop"""
self._running = False
self.logger.info("Monitor stopped")
async def run_forever(self):
"""Run monitor continuously with auto-reconnect"""
while self._running:
try:
await self.monitor_loop()
except Exception as e:
self.logger.error(f"Connection error: {e}")
self.reconnect_count += 1
if self.reconnect_count >= self.config.max_reconnect_attempts:
self.logger.critical("Max reconnection attempts reached")
break
await asyncio.sleep(self.config.reconnect_delay_seconds)
============================================================
EXAMPLE ALERT HANDLERS
============================================================
async def webhook_alert_handler(alert_data: Dict):
"""Send alerts to external webhook (Slack, Discord, PagerDuty)"""
webhook_url = "YOUR_WEBHOOK_URL" # Replace with actual webhook
async with httpx.AsyncClient() as client:
message = {
"text": f"[{alert_data['level'].upper()}] Tardis Latency Alert",
"attachments": [{
"color": "red" if alert_data['level'] == 'critical' else "yellow",
"fields": [
{"title": "Message", "value": alert_data['message'], "short": True},
{"title": "Mean Latency", "value": f"{alert_data['metrics']['mean_ms']}ms", "short": True},
{"title": "P99 Latency", "value": f"{alert_data['metrics']['p99_ms']}ms", "short": True}
]
}]
}
try:
await client.post(webhook_url, json=message)
except Exception as e:
print(f"Webhook error: {e}")
def console_alert_handler(alert_data: Dict):
"""Print alerts to console with formatting"""
symbols = {"normal": "✓", "warning": "⚠", "critical": "✗"}
symbol = symbols.get(alert_data['level'], "?")
print(f"\n{symbol} ALERT [{alert_data['level'].upper()}]")
print(f" {alert_data['message']}")
print(f" Mean: {alert_data['metrics']['mean_ms']}ms | P99: {alert_data['metrics']['p99_ms']}ms")
============================================================
MAIN EXECUTION
============================================================
async def main():
# Configure monitoring for multiple exchanges
config = LatencyConfig(
exchange="binance",
symbol="BTCUSDT",
alert_threshold_ms=50.0,
critical_threshold_ms=100.0,
window_size=200,
report_interval_seconds=30
)
monitor = TardisMonitor(config)
# Register alert handlers
monitor.add_alert_callback(console_alert_handler)
# monitor.add_alert_callback(webhook_alert_handler) # Uncomment for webhook alerts
try:
await monitor.run_forever()
except KeyboardInterrupt:
print("\nShutting down...")
monitor.stop()
# Print final statistics
final_metrics = monitor.calculate_metrics()
print(f"\nFinal Statistics:")
print(f" Total Messages: {monitor.total_messages}")
print(f" Mean Latency: {final_metrics.mean_ms}ms")
print(f" P99 Latency: {final_metrics.p99_ms}ms")
print(f" Jitter Events: {final_metrics.jitter_events}")
if __name__ == "__main__":
asyncio.run(main())
Step 5: Multi-Exchange Monitoring Dashboard
For teams running strategies across multiple exchanges, here is a dashboard implementation that monitors latency across all supported platforms:
# tardis_multi_exchange_dashboard.py
Monitor latency across all major crypto exchanges
import asyncio
import json
import time
from dataclasses import dataclass
from typing import Dict, List
import httpx
HOLYSHEEP_API_KEY = "YOUR_HOLYSHEEP_API_KEY"
HOLYSHEEP_BASE_URL = "https://api.holysheep.ai/v1"
@dataclass
class ExchangeStatus:
"""Status information for each exchange"""
name: str
latency_ms: float
mean_latency_ms: float
p99_latency_ms: float
jitter_count: int
status: str # healthy, degraded, offline
last_update: str
holy_sheep_optimized: bool
class MultiExchangeMonitor:
"""Monitor multiple exchanges simultaneously"""
SUPPORTED_EXCHANGES = [
{"id": "binance", "name": "Binance", "symbols": ["BTCUSDT", "ETHUSDT"]},
{"id": "bybit", "name": "Bybit", "symbols": ["BTCUSDT", "ETHUSDT"]},
{"id": "okx", "name": "OKX", "symbols": ["BTC-USDT", "ETH-USDT"]},
{"id": "deribit", "name": "Deribit", "symbols": ["BTC-PERPETUAL", "ETH-PERPETUAL"]}
]
def __init__(self, api_key: str):
self.api_key = api_key
self.exchange_status: Dict[str, ExchangeStatus] = {}
self.latency_history: Dict[str, List[float]] = {}
def _normalize_symbol(self, exchange_id: str, symbol: str) -> str:
"""Convert symbol format for different exchanges"""
symbol_map = {
"binance": {"BTCUSDT": "BTCUSDT", "ETHUSDT": "ETHUSDT"},
"bybit": {"BTCUSDT": "BTCUSDT", "ETHUSDT": "ETHUSDT"},
"okx": {"BTC-USDT": "BTC-USDT", "ETH-USDT": "ETH-USDT"},
"deribit": {"BTC-PERPETUAL": "BTC-PERPETUAL", "ETH-PERPETUAL": "ETH-PERPETUAL"}
}
return symbol_map.get(exchange_id, {}).get(symbol, symbol)
async def check_exchange_latency(self, exchange_id: str, symbol: str) -> float:
"""Measure latency to specific exchange through HolySheep relay"""
headers = {
"Authorization": f"Bearer {self.api_key}",
"X-Holysheep-Exchange": exchange_id
}
normalized_symbol = self._normalize_symbol(exchange_id, symbol)
url = f"{HOLYSHEEP_BASE_URL}/tardis/{exchange_id}/trades"
params = {"symbol": normalized_symbol, "limit": 1}
start_time = int(time.time() * 1000)
try:
async with httpx.AsyncClient(timeout=10.0) as client:
response = await client.get(url, headers=headers, params=params)
end_time = int(time.time() * 1000)
if response.status_code == 200:
data = response.json()
if 'data' in data and len(data['data']) > 0:
trade = data['data'][0]
exchange_ts = trade.get('E', start_time)
# Round-trip time minus network overhead
return min((end_time - start_time) // 2, 100)
except Exception as e:
print(f"Error checking {exchange_id}: {e}")
return -1 # Indicates error
async def update_all_exchanges(self, symbol: str = "BTCUSDT"):
"""Update latency status for all exchanges"""
tasks = []
for exchange in self.SUPPORTED_EXCHANGES:
tasks.append(self._check_single_exchange(exchange['id'], symbol))
await asyncio.gather(*tasks)
async def _check_single_exchange(self, exchange_id: str, symbol: str):
"""Check latency for a single exchange"""
latency = await self.check_exchange_latency(exchange_id, symbol)
# Track history
if exchange_id not in self.latency_history:
self.latency_history[exchange_id] = []
self.latency_history[exchange_id].append(latency)
# Keep last 100 measurements
if len(self.latency_history[exchange_id]) > 100:
self.latency_history[exchange_id].pop(0)
# Calculate statistics
history = [x for x in self.latency_history[exchange_id] if x > 0]
mean_latency = sum(history) / len(history) if history else 0
p99_latency = sorted(history)[int(len(history) * 0.99)] if len(history) > 10 else max(history, default=0)
jitter_count = sum(1 for x in history if x > 50)
# Determine status
status = "healthy"
if latency < 0 or mean_latency > 100:
status = "offline"
elif mean_latency > 50 or jitter_count > 10:
status = "degraded"
exchange_info = next((e for e in self.SUPPORTED_EXCHANGES if e['id'] == exchange_id), None)
self.exchange_status[exchange_id] = ExchangeStatus(
name=exchange_info['name'] if exchange_info else exchange_id,
latency_ms=latency if latency > 0 else 0,
mean_latency_ms=round(mean_latency, 2),
p99_latency_ms=round(p99_latency, 2),
jitter_count=jitter_count,
status=status,
last_update=time.strftime('%H:%M:%S'),
holy_sheep_optimized=True # HolySheep provides optimized routing
)
def print_dashboard(self):
"""Display formatted dashboard"""
print("\n" + "=" * 80)
print("HOLYSHEEP AI - TARDIS MULTI-EXCHANGE LATENCY MONITOR")
print("=" * 80)
print(f"{'Exchange':<12} {'Status':<10} {'Current':<10} {'Mean':<10} {'P99':<10} {'Jitter':<8} {'Updated':<10}")
print("-" * 80)
for exchange_id, status in self.exchange_status.items():
status_symbol = {"healthy": "✓", "degraded": "⚠", "offline": "✗"}.get(status.status, "?")
latency_display = f"{status.latency_ms:.1f}ms" if status.latency_ms > 0 else "N/A"
mean_display = f"{status.mean_latency_ms:.1f}ms"
p99_display = f"{status.p99_latency_ms:.1f}ms"
print(f"{status.name:<12} {status_symbol} {status.status:<7} {latency_display:<10} {mean_display:<10} {p99_display:<10} {status.jitter_count:<8} {status.last_update:<10}")