spring-petclinic/.github/workflows/pipeline.yml
2025-02-03 19:40:00 +01:00

351 lines
11 KiB
YAML

name: Enhanced Java Application Pipeline with Metrics and Energy Monitoring
on:
push:
branches: [ pipeline-optimization ]
pull_request:
branches: [ pipeline-optimization ]
jobs:
build-with-metrics:
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
grafana:
image: grafana/grafana:latest
ports:
- 3000:3000
steps:
- uses: actions/checkout@v4
- name: Cache Maven packages
uses: actions/cache@v3
with:
path: ~/.m2
key: ${{ runner.os }}-m2-${{ hashFiles('**/pom.xml') }}
restore-keys: ${{ runner.os }}-m2
- name: Setup monitoring tools
id: setup-monitoring
timeout-minutes: 5
run: |
set -eo pipefail
echo "::group::Installing system packages"
sudo apt-get update
sudo apt-get install -y powerstat linux-tools-common linux-tools-generic python3-pip stress-ng
echo "::endgroup::"
echo "::group::Installing PowerAPI"
pip3 install powerapi pandas
sudo powerapi --formula rapl
echo "::endgroup::"
echo "::group::Setting up node exporter"
curl -L --retry 3 https://github.com/prometheus/node_exporter/releases/download/v1.3.1/node_exporter-1.3.1.linux-amd64.tar.gz -o node_exporter.tar.gz
tar xvfz node_exporter.tar.gz
echo "::endgroup::"
- name: Start monitoring services
id: start-monitoring
timeout-minutes: 2
run: |
set -eo pipefail
# Démarrer node exporter
./node_exporter-*/node_exporter --web.listen-address=":9100" &
echo "NODE_EXPORTER_PID=$!" >> $GITHUB_ENV
# Démarrer PowerAPI
sudo powerapi daemon start --formula rapl
echo "POWERAPI_PID=$(pgrep -f powerapi)" >> $GITHUB_ENV
# Créer les répertoires pour les métriques
mkdir -p metrics/{power,system,performance}
# Marquer le début du pipeline
date +%s%N > metrics/pipeline_start_time.txt
- name: Set up JDK 17
uses: actions/setup-java@v4
with:
java-version: '17'
distribution: 'adopt'
cache: maven
- name: Build with Maven
id: build
timeout-minutes: 15
env:
MAVEN_OPTS: "-Xmx2048m -XX:+TieredCompilation -XX:TieredStopAtLevel=1"
run: |
set -eo pipefail
# Démarrer la mesure PowerAPI pour le build
sudo powerapi monitor record --formula rapl --pid $$ --output metrics/power/build_power.csv &
POWER_MONITOR_PID=$!
start_time=$(date +%s%N)
# Build optimisé
./mvnw -B verify \
-Dmaven.test.skip=true \
-Dcheckstyle.skip=true \
-T 1C \
-Dmaven.parallel.threads=4
build_status=$?
end_time=$(date +%s%N)
# Arrêter la mesure PowerAPI
kill $POWER_MONITOR_PID
# Exporter les métriques de build
echo "BUILD_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
exit $build_status
- name: Run tests
id: test
if: success()
timeout-minutes: 20
run: |
set -eo pipefail
# Démarrer la mesure PowerAPI pour les tests
sudo powerapi monitor record --formula rapl --pid $$ --output metrics/power/test_power.csv &
POWER_MONITOR_PID=$!
start_time=$(date +%s%N)
# Tests optimisés
./mvnw test \
-T 1C \
-Dmaven.parallel.threads=4 \
-Dsurefire.useFile=false
test_status=$?
end_time=$(date +%s%N)
# Arrêter la mesure PowerAPI
kill $POWER_MONITOR_PID
echo "TEST_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
exit $test_status
- name: Build Docker image
id: docker-build
if: success()
timeout-minutes: 10
run: |
set -eo pipefail
# Démarrer la mesure PowerAPI pour le build Docker
sudo powerapi monitor record --formula rapl --pid $$ --output metrics/power/docker_power.csv &
POWER_MONITOR_PID=$!
start_time=$(date +%s%N)
# Build Docker optimisé
DOCKER_BUILDKIT=1 docker build \
--no-cache \
--build-arg JAVA_VERSION=17 \
--build-arg JAVA_DISTRIBUTION=adoptopenjdk \
-t app:latest \
-f Dockerfile .
build_status=$?
end_time=$(date +%s%N)
# Arrêter la mesure PowerAPI
kill $POWER_MONITOR_PID
echo "DOCKER_BUILD_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
exit $build_status
- name: Setup Kubernetes
id: k8s-setup
if: success()
uses: helm/kind-action@v1
with:
wait: 120s
config: |
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane
kubeadmConfigPatches:
- |
kind: InitConfiguration
nodeRegistration:
kubeletExtraArgs:
system-reserved: memory=1Gi
eviction-hard: memory.available<500Mi
- name: Deploy to Kubernetes
id: deploy
if: success()
timeout-minutes: 10
run: |
set -eo pipefail
# Démarrer la mesure PowerAPI pour le déploiement
sudo powerapi monitor record --formula rapl --pid $$ --output metrics/power/deploy_power.csv &
POWER_MONITOR_PID=$!
start_time=$(date +%s%N)
# Déploiement optimisé
kubectl apply -f k8s/
# Attendre que les pods soient prêts
kubectl wait --for=condition=ready pod -l app=petclinic --timeout=180s
end_time=$(date +%s%N)
# Arrêter la mesure PowerAPI
kill $POWER_MONITOR_PID
echo "DEPLOY_TIME=$((($end_time - $start_time)/1000000))" >> $GITHUB_ENV
- name: Collect and analyze metrics
if: always()
run: |
set -eo pipefail
# Collecter les métriques système finales
echo "=== System Resources ===" > metrics/system/system_metrics.txt
top -b -n 1 >> metrics/system/system_metrics.txt
echo "=== Memory Usage ===" > metrics/system/memory_metrics.txt
free -m >> metrics/system/memory_metrics.txt
echo "=== Disk Usage ===" > metrics/system/disk_metrics.txt
df -h >> metrics/system/disk_metrics.txt
# Marquer la fin du pipeline
date +%s%N > metrics/pipeline_end_time.txt
# Analyser les métriques de puissance
python3 << EOF
import pandas as pd
import glob
import os
def analyze_power_metrics():
power_files = glob.glob('metrics/power/*.csv')
metrics = []
for file in power_files:
stage = os.path.basename(file).replace('_power.csv', '')
df = pd.read_csv(file)
stats = {
'stage': stage,
'avg_power': df['power'].mean(),
'max_power': df['power'].max(),
'total_energy': df['energy'].sum(),
'duration': len(df) * df['power'].iloc[0] # Assuming fixed sampling rate
}
metrics.append(stats)
results = pd.DataFrame(metrics)
results.to_csv('metrics/power/power_analysis.csv', index=False)
# Créer un rapport sommaire
with open('metrics/performance/summary.txt', 'w') as f:
f.write("Pipeline Performance Summary\n")
f.write("==========================\n\n")
for _, row in results.iterrows():
f.write(f"Stage: {row['stage']}\n")
f.write(f"Average Power: {row['avg_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")
analyze_power_metrics()
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=\"petclinic\"} ${metric_value}" | \
curl --retry 3 --retry-delay 2 --max-time 10 --silent --show-error \
--data-binary @- http://localhost:9091/metrics/job/petclinic-pipeline
fi
}
# Exporter les durées
export_metric "pipeline_build_duration_ms" "${BUILD_TIME}" "build"
export_metric "pipeline_test_duration_ms" "${TEST_TIME}" "test"
export_metric "pipeline_docker_build_duration_ms" "${DOCKER_BUILD_TIME}" "docker-build"
export_metric "pipeline_deploy_duration_ms" "${DEPLOY_TIME}" "deploy"
# Exporter les métriques de ressources
mem_usage=$(free -b | grep Mem: | awk '{print $3}')
export_metric "pipeline_memory_usage_bytes" "$mem_usage" "memory"
cpu_usage=$(top -bn1 | grep "Cpu(s)" | awk '{print $2}')
export_metric "pipeline_cpu_usage_percent" "$cpu_usage" "cpu"
# Exporter les métriques de puissance
while IFS=, read -r stage avg_power total_energy; do
export_metric "pipeline_power_usage_watts" "$avg_power" "$stage"
export_metric "pipeline_energy_consumption_joules" "$total_energy" "$stage"
done < <(tail -n +2 metrics/power/power_analysis.csv)
- name: Stop monitoring services
if: always()
run: |
# Arrêter PowerAPI
sudo powerapi daemon stop
# Arrêter node exporter
if [ -n "$NODE_EXPORTER_PID" ]; then
kill $NODE_EXPORTER_PID
fi
- 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
rm -rf node_exporter*