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lamya1baidouri 2025-02-03 20:19:41 +01:00
parent 3e9be926fc
commit b8055c3c2b
1 changed files with 4 additions and 173 deletions
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177
.github/workflows/pipeline.yml vendored
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@ -1,4 +1,4 @@
name: Enhanced Java Application Pipeline with Metrics and Energy Monitoring
name: Enhanced Java Application Pipeline with Metrics Collection
on:
push:
@ -11,31 +11,10 @@ jobs:
runs-on: ubuntu-latest
timeout-minutes: 60
services:
prometheus:
image: prom/prometheus:latest
ports:
- 9090:9090
options: >-
--health-cmd "wget -q -O- http://localhost:9090/-/healthy || exit 1"
--health-interval 10s
--health-timeout 5s
--health-retries 3
pushgateway:
image: prom/pushgateway:latest
ports:
- 9091:9091
options: >-
--health-cmd "wget -q -O- http://localhost:9091/-/healthy || exit 1"
--health-interval 10s
--health-timeout 5s
--health-retries 3
steps:
- uses: actions/checkout@v4
- name: Setup directories and tools
- name: Setup directories for metrics
run: |
set -eo pipefail
@ -66,8 +45,7 @@ jobs:
sudo powerapi daemon start --formula rapl
echo "POWERAPI_PID=$(pgrep -f powerapi)" >> $GITHUB_ENV
- name: Start monitoring
id: start-monitoring
- name: Collect initial system metrics
run: |
set -eo pipefail
@ -124,7 +102,6 @@ jobs:
free -m > metrics/system/post_build_memory.txt
# Enregistrer le temps de build
echo "BUILD_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
echo "$((($end_time - $start_time)/1000000))" > metrics/performance/build_time.txt
exit $build_status
@ -158,7 +135,6 @@ jobs:
free -m > metrics/system/post_test_memory.txt
# Enregistrer le temps des tests
echo "TEST_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
echo "$((($end_time - $start_time)/1000000))" > metrics/performance/test_time.txt
exit $test_status
@ -194,7 +170,6 @@ jobs:
df -h > metrics/system/post_docker_disk.txt
# Enregistrer le temps de build Docker
echo "DOCKER_BUILD_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
echo "$((($end_time - $start_time)/1000000))" > metrics/performance/docker_time.txt
# Collecter la taille de l'image
@ -202,7 +177,7 @@ jobs:
exit $build_status
- name: Collect and analyze metrics
- name: Collect final system metrics
if: always()
run: |
set -eo pipefail
@ -220,149 +195,6 @@ jobs:
# Marquer la fin du pipeline
date +%s%N > metrics/pipeline_end_time.txt
python3 << EOF
import pandas as pd
import glob
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():
"""Analyse les données de PowerAPI avec gestion d'erreur"""
try:
power_files = glob.glob('metrics/power/*.csv')
if not power_files:
print("No power metrics found")
return {}
power_data = []
for file in power_files:
stage = os.path.basename(file).replace('_power.csv', '')
try:
df = pd.read_csv(file)
stats = {
'stage': stage,
'avg_power': df['power'].mean(),
'max_power': df['power'].max(),
'total_energy': df['power'].sum() * df['power'].count() * 0.1,
'duration': len(df) * 0.1
}
power_data.append(stats)
except Exception as e:
print(f"Error processing {file}: {e}")
if power_data:
power_df = pd.DataFrame(power_data)
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 {}
def analyze_times():
"""Analyse les temps d'exécution avec gestion d'erreur"""
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')
}
total_time = sum(times.values())
if total_time > 0:
os.makedirs('metrics/performance', exist_ok=True)
with open('metrics/performance/summary.txt', 'w') as f:
f.write("Pipeline Performance Summary\n")
f.write("==========================\n\n")
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")
f.write(f"Total Pipeline Duration: {total_time/1000:.2f} seconds\n")
pd.DataFrame([times]).to_csv('metrics/performance/times.csv', index=False)
return times
except Exception as e:
print(f"Error in time analysis: {e}")
return {}
# 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)
# 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}")
EOF
- name: Export metrics to Prometheus
if: always()
timeout-minutes: 5
run: |
set -eo pipefail
function export_metric() {
local metric_name=$1
local metric_value=$2
local stage=$3
if [ -n "$metric_value" ]; then
echo "${metric_name}{stage=\"${stage}\",project=\"java-app\"} ${metric_value}" | \
curl --retry 3 --max-time 10 --silent --show-error \
--data-binary @- http://localhost:9091/metrics/job/pipeline-metrics || \
echo "Failed to export metric ${metric_name}"
fi
}
# Exporter les temps d'exécution
export_metric "pipeline_duration_ms" "${BUILD_TIME}" "build"
export_metric "pipeline_duration_ms" "${TEST_TIME}" "test"
export_metric "pipeline_duration_ms" "${DOCKER_BUILD_TIME}" "docker"
# Exporter l'utilisation mémoire finale
mem_usage=$(free -b | grep Mem: | awk '{print $3}')
export_metric "memory_usage_bytes" "$mem_usage" "final"
- name: Save metrics
if: always()
uses: actions/upload-artifact@v4
@ -381,4 +213,3 @@ jobs:
fi
docker system prune -af
rm -rf node_exporter*