38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
import json
|
|
import os
|
|
from datetime import datetime, timedelta
|
|
|
|
DATA_FILE = 'monitoring_data.json'
|
|
|
|
def load_data():
|
|
if os.path.exists(DATA_FILE):
|
|
with open(DATA_FILE, 'r') as f:
|
|
return json.load(f)
|
|
return []
|
|
|
|
def store_data(new_data):
|
|
data = load_data()
|
|
data.append(new_data)
|
|
with open(DATA_FILE, 'w') as f:
|
|
json.dump(data, f, indent=4)
|
|
|
|
def calculate_baselines():
|
|
data = load_data()
|
|
if not data:
|
|
return {}
|
|
|
|
# For simplicity, we'll average the last 24 hours of data
|
|
# More complex logic can be added here
|
|
recent_data = [d for d in data if datetime.fromisoformat(d['system_logs']['timestamp'].replace('Z', '')) > datetime.now() - timedelta(hours=24)]
|
|
|
|
if not recent_data:
|
|
return {}
|
|
|
|
baseline_metrics = {
|
|
'avg_rtt': sum(d['network_metrics']['round_trip_ms_avg'] for d in recent_data) / len(recent_data),
|
|
'packet_loss': sum(d['network_metrics']['packet_loss_percent'] for d in recent_data) / len(recent_data),
|
|
'avg_cpu_temp': sum(d['cpu_temperature']['cpu_temperature'] for d in recent_data) / len(recent_data),
|
|
'avg_gpu_temp': sum(d['gpu_temperature']['gpu_temperature'] for d in recent_data) / len(recent_data),
|
|
}
|
|
|
|
return baseline_metrics |