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lamya1baidouri 2025-02-03 20:14:13 +01:00
parent f5d2b0b0aa
commit 3e9be926fc
1 changed files with 115 additions and 69 deletions
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154
.github/workflows/pipeline.yml vendored
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@ -209,13 +209,13 @@ jobs:
# Collecter les métriques système finales # Collecter les métriques système finales
echo "=== Final System Resources ===" > metrics/system/final_metrics.txt echo "=== Final System Resources ===" > metrics/system/final_metrics.txt
top -b -n 1 >> metrics/system/final_metrics.txt top -b -n 1 >> metrics/system/final_metrics.txt || echo "Failed to collect top metrics"
echo "=== Final Memory Usage ===" > metrics/system/final_memory.txt echo "=== Final Memory Usage ===" > metrics/system/final_memory.txt
free -m >> metrics/system/final_memory.txt free -m >> metrics/system/final_memory.txt || echo "Failed to collect memory metrics"
echo "=== Final Disk Usage ===" > metrics/system/final_disk.txt echo "=== Final Disk Usage ===" > metrics/system/final_disk.txt
df -h >> metrics/system/final_disk.txt df -h >> metrics/system/final_disk.txt || echo "Failed to collect disk metrics"
# Marquer la fin du pipeline # Marquer la fin du pipeline
date +%s%N > metrics/pipeline_end_time.txt date +%s%N > metrics/pipeline_end_time.txt
@ -225,70 +225,116 @@ jobs:
import glob import glob
import os import os
def read_time_file(filename, default=0):
"""Lit un fichier de temps avec gestion d'erreur"""
try:
with open(filename) as f:
return float(f.read().strip())
except Exception as e:
print(f"Warning: Could not read {filename}: {e}")
return default
def analyze_power_metrics(): def analyze_power_metrics():
power_files = glob.glob('metrics/power/*.csv') """Analyse les données de PowerAPI avec gestion d'erreur"""
if not power_files: try:
print("No power metrics found") power_files = glob.glob('metrics/power/*.csv')
return if not power_files:
print("No power metrics found")
return {}
power_data = [] power_data = []
for file in power_files: for file in power_files:
stage = os.path.basename(file).replace('_power.csv', '') stage = os.path.basename(file).replace('_power.csv', '')
try: try:
df = pd.read_csv(file) df = pd.read_csv(file)
stats = { stats = {
'stage': stage, 'stage': stage,
'avg_power': df['power'].mean(), 'avg_power': df['power'].mean(),
'max_power': df['power'].max(), 'max_power': df['power'].max(),
'total_energy': df['power'].sum() * df['power'].count() * 0.1, 'total_energy': df['power'].sum() * df['power'].count() * 0.1,
'duration': len(df) * 0.1 'duration': len(df) * 0.1
} }
power_data.append(stats) power_data.append(stats)
except Exception as e: except Exception as e:
print(f"Error processing {file}: {e}") print(f"Error processing {file}: {e}")
if power_data: if power_data:
power_df = pd.DataFrame(power_data) power_df = pd.DataFrame(power_data)
power_df.to_csv('metrics/power/power_analysis.csv', index=False) power_df.to_csv('metrics/power/power_analysis.csv', index=False)
return power_df
return {}
except Exception as e:
print(f"Error in power analysis: {e}")
return {}
with open('metrics/power/power_summary.txt', 'w') as f: def analyze_times():
f.write("Energy Consumption Summary\n") """Analyse les temps d'exécution avec gestion d'erreur"""
f.write("=========================\n\n") try:
times = {
'build': read_time_file('metrics/performance/build_time.txt'),
'test': read_time_file('metrics/performance/test_time.txt'),
'docker': read_time_file('metrics/performance/docker_time.txt')
}
for _, row in power_df.iterrows(): total_time = sum(times.values())
f.write(f"Stage: {row['stage']}\n") if total_time > 0:
f.write(f"Average Power: {row['avg_power']:.2f} W\n") os.makedirs('metrics/performance', exist_ok=True)
f.write(f"Maximum Power: {row['max_power']:.2f} W\n")
f.write(f"Total Energy: {row['total_energy']:.2f} J\n")
f.write(f"Duration: {row['duration']:.2f} s\n\n")
def analyze_times(): with open('metrics/performance/summary.txt', 'w') as f:
times = { f.write("Pipeline Performance Summary\n")
'build': float(open('metrics/performance/build_time.txt').read().strip()), f.write("==========================\n\n")
'test': float(open('metrics/performance/test_time.txt').read().strip()),
'docker': float(open('metrics/performance/docker_time.txt').read().strip())
}
total_time = sum(times.values()) for stage, duration in times.items():
percentage = (duration / total_time * 100) if total_time > 0 else 0
f.write(f"{stage.capitalize()} Stage:\n")
f.write(f"Duration: {duration/1000:.2f} seconds\n")
f.write(f"Percentage of total time: {percentage:.1f}%\n\n")
with open('metrics/performance/summary.txt', 'w') as f: f.write(f"Total Pipeline Duration: {total_time/1000:.2f} seconds\n")
f.write("Pipeline Performance Summary\n")
f.write("==========================\n\n")
for stage, duration in times.items(): pd.DataFrame([times]).to_csv('metrics/performance/times.csv', index=False)
percentage = (duration / total_time * 100) return times
f.write(f"{stage.capitalize()} Stage:\n") except Exception as e:
f.write(f"Duration: {duration/1000:.2f} seconds\n") print(f"Error in time analysis: {e}")
f.write(f"Percentage of total time: {percentage:.1f}%\n\n") return {}
f.write(f"Total Pipeline Duration: {total_time/1000:.2f} seconds\n") # Créer les répertoires si nécessaire
os.makedirs('metrics/power', exist_ok=True)
os.makedirs('metrics/performance', exist_ok=True)
os.makedirs('metrics/system', exist_ok=True)
pd.DataFrame([times]).to_csv('metrics/performance/times.csv', index=False) # Analyser les données
power_metrics = analyze_power_metrics()
time_metrics = analyze_times()
# Créer un rapport final
try:
with open('metrics/summary_report.txt', 'w') as f:
f.write("Pipeline Analysis Report\n")
f.write("======================\n\n")
if time_metrics:
f.write("Performance Metrics:\n")
f.write("-----------------\n")
total_time = sum(time_metrics.values())
f.write(f"Total Duration: {total_time/1000:.2f} seconds\n")
for stage, duration in time_metrics.items():
f.write(f"{stage}: {duration/1000:.2f}s\n")
f.write("\n")
if power_metrics:
f.write("Energy Metrics:\n")
f.write("--------------\n")
for stage, metrics in power_metrics.items():
f.write(f"Stage: {stage}\n")
for metric, value in metrics.items():
if metric != 'stage':
f.write(f"{metric}: {value:.2f}\n")
f.write("\n")
except Exception as e:
print(f"Error creating final report: {e}")
analyze_power_metrics()
analyze_times()
EOF EOF
- name: Export metrics to Prometheus - name: Export metrics to Prometheus
if: always() if: always()
timeout-minutes: 5 timeout-minutes: 5