spring-petclinic/.github/workflows/pipeline.yml
lamya1baidouri da5cb7e45d debbug 4
2025-02-03 20:25:14 +01:00

275 lines
8.3 KiB
YAML

name: Enhanced Java Application Pipeline with Metrics Collection
on:
push:
branches: [ pipeline-optimization ]
pull_request:
branches: [ pipeline-optimization ]
jobs:
build-with-metrics:
runs-on: ubuntu-latest
timeout-minutes: 60
steps:
- uses: actions/checkout@v4
- name: Setup directories and install dependencies
run: |
set -eo pipefail
# Créer la structure des répertoires
mkdir -p metrics/system
mkdir -p metrics/power
mkdir -p metrics/performance
# Installation des packages nécessaires
sudo apt-get update
sudo apt-get install -y \
linux-tools-common \
linux-tools-generic \
python3-pip \
python3-psutil
# Installer PowerAPI globalement
sudo pip3 install powerapi pandas numpy
- name: Cache Maven packages
uses: actions/cache@v3
with:
path: ~/.m2
key: ${{ runner.os }}-m2-${{ hashFiles('**/pom.xml') }}
restore-keys: ${{ runner.os }}-m2
- name: Collect initial system metrics
run: |
set -eo pipefail
# Enregistrer le temps de début
date +%s%N > metrics/pipeline_start_time.txt
# Collecter les métriques initiales
echo "=== Initial System Resources ===" > metrics/system/initial_metrics.txt
top -b -n 1 >> metrics/system/initial_metrics.txt
echo "=== Initial Memory Usage ===" > metrics/system/initial_memory.txt
free -m >> metrics/system/initial_memory.txt
echo "=== Initial Disk Usage ===" > metrics/system/initial_disk.txt
df -h >> metrics/system/initial_disk.txt
- name: Set up JDK 17
uses: actions/setup-java@v4
with:
java-version: '17'
distribution: 'adopt'
cache: maven
- name: Build with Maven and measure energy
id: build
timeout-minutes: 15
env:
MAVEN_OPTS: "-Xmx2048m -XX:+TieredCompilation -XX:TieredStopAtLevel=1"
run: |
set -eo pipefail
start_time=$(date +%s%N)
# Collecter les métriques avant build
free -m > metrics/system/pre_build_memory.txt
# Mesure de la consommation d'énergie avec PowerAPI
python3 -c "
import powerapi
from powerapi import database
# Configuration de la base de données
db = database.InfluxDatabase(
host='localhost',
port=8086,
database='powerapi'
)
# Configuration du monitoring
monitor = powerapi.monitor.PowerMonitor(
'rapl', # Utilisation de l'interface RAPL
db,
1 # Période de mesure en secondes
)
# Démarrer le monitoring
monitor.start()
# Enregistrer le début du monitoring
print('Monitoring started')
" &
POWERAPI_PID=$!
# Build optimisé
./mvnw -B verify \
-Dmaven.test.skip=true \
-Dcheckstyle.skip=true \
-T 1C
build_status=$?
end_time=$(date +%s%N)
# Arrêter PowerAPI
kill $POWERAPI_PID
# Collecter les métriques post-build
free -m > metrics/system/post_build_memory.txt
# Enregistrer le temps de build
echo "$((($end_time - $start_time)/1000000))" > metrics/performance/build_time.txt
exit $build_status
- name: Run tests with energy monitoring
id: test
if: success()
timeout-minutes: 20
run: |
set -eo pipefail
start_time=$(date +%s%N)
# Collecter les métriques pré-tests
free -m > metrics/system/pre_test_memory.txt
# Mesure de la consommation d'énergie avec PowerAPI
python3 -c "
import powerapi
from powerapi import database
# Configuration de la base de données
db = database.InfluxDatabase(
host='localhost',
port=8086,
database='powerapi'
)
# Configuration du monitoring
monitor = powerapi.monitor.PowerMonitor(
'rapl', # Utilisation de l'interface RAPL
db,
1 # Période de mesure en secondes
)
# Démarrer le monitoring
monitor.start()
# Enregistrer le début du monitoring
print('Monitoring started')
" &
POWERAPI_PID=$!
# Tests optimisés
./mvnw test -T 1C
test_status=$?
end_time=$(date +%s%N)
# Arrêter PowerAPI
kill $POWERAPI_PID
# Collecter les métriques post-tests
free -m > metrics/system/post_test_memory.txt
# Enregistrer le temps des tests
echo "$((($end_time - $start_time)/1000000))" > metrics/performance/test_time.txt
exit $test_status
- name: Build Docker image with energy monitoring
id: docker-build
if: success()
timeout-minutes: 10
run: |
set -eo pipefail
start_time=$(date +%s%N)
# Collecter les métriques pré-docker
free -m > metrics/system/pre_docker_memory.txt
df -h > metrics/system/pre_docker_disk.txt
# Mesure de la consommation d'énergie avec PowerAPI
python3 -c "
import powerapi
from powerapi import database
# Configuration de la base de données
db = database.InfluxDatabase(
host='localhost',
port=8086,
database='powerapi'
)
# Configuration du monitoring
monitor = powerapi.monitor.PowerMonitor(
'rapl', # Utilisation de l'interface RAPL
db,
1 # Période de mesure en secondes
)
# Démarrer le monitoring
monitor.start()
# Enregistrer le début du monitoring
print('Monitoring started')
" &
POWERAPI_PID=$!
# Build Docker optimisé
docker build -t app:latest -f .devcontainer/Dockerfile . --no-cache
build_status=$?
end_time=$(date +%s%N)
# Arrêter PowerAPI
kill $POWERAPI_PID
# Collecter les métriques post-docker
free -m > metrics/system/post_docker_memory.txt
df -h > metrics/system/post_docker_disk.txt
# Enregistrer le temps de build Docker
echo "$((($end_time - $start_time)/1000000))" > metrics/performance/docker_time.txt
# Collecter la taille de l'image
docker images app:latest --format "{{.Size}}" > metrics/performance/docker_image_size.txt
exit $build_status
- name: Collect final system metrics
if: always()
run: |
set -eo pipefail
# Collecter les métriques système finales
echo "=== Final System Resources ===" > 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
free -m >> metrics/system/final_memory.txt || echo "Failed to collect memory metrics"
echo "=== Final Disk Usage ===" > metrics/system/final_disk.txt
df -h >> metrics/system/final_disk.txt || echo "Failed to collect disk metrics"
# Marquer la fin du pipeline
date +%s%N > metrics/pipeline_end_time.txt
- name: Save metrics
if: always()
uses: actions/upload-artifact@v4
with:
name: pipeline-metrics
path: metrics/
retention-days: 90
if-no-files-found: warn
- name: Cleanup
if: always()
run: |
docker system prune -af