Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.
# Kustomisasi gambar kontainer
Solusi ini menggunakan repositori image Amazon Elastic Container Registry (Amazon ECR) publik yang dikelola oleh AWS untuk menyimpan gambar yang digunakan untuk menjalankan pengujian yang dikonfigurasi. Jika Anda ingin menyesuaikan gambar kontainer, Anda dapat membangun kembali dan mendorong gambar ke dalam repositori gambar ECR di akun AWS Anda sendiri.
Jika Anda ingin menyesuaikan solusi ini, Anda dapat menggunakan gambar kontainer default atau, edit wadah ini agar sesuai dengan kebutuhan Anda. Jika Anda menyesuaikan solusinya, gunakan contoh kode berikut untuk mendeklarasikan variabel lingkungan sebelum membuat solusi khusus Anda.
```
#!/bin/bash
export REGION=aws-region-code # the AWS region to launch the solution (e.g. us-east-1)
export BUCKET_PREFIX=my-bucket-name # prefix of the bucket name without the region code
export BUCKET_NAME=$BUCKET_PREFIX-$REGION # full bucket name where the code will reside
export SOLUTION_NAME=my-solution-name
export VERSION=my-version # version number for the customized code
export PUBLIC_ECR_REGISTRY=public.ecr.aws/awssolutions/distributed-load-testing-on-aws-load-tester # replace with the container registry and image if you want to use a different container image export PUBLIC_ECR_TAG=v3.1.0 # replace with the container image tag if you want to use a different container image
```
Jika Anda memilih untuk menyesuaikan gambar kontainer, Anda dapat menghostingnya di repositori gambar pribadi, atau repositori gambar publik di akun AWS Anda. Sumber daya gambar ada di `deployment/ecr/distributed-load-testing-on-aws-load-tester` direktori, yang terletak di basis kode.
Anda dapat membangun dan mendorong gambar ke tujuan host.
+ *Untuk repositori dan gambar Amazon ECR pribadi, lihat [repositori pribadi Amazon ECR dan [gambar pribadi di](https://docs.aws.amazon.com/AmazonECR/latest/userguide/images.html) Panduan](https://docs.aws.amazon.com/AmazonECR/latest/userguide/Repositories.html) Pengguna Amazon ECR.*
+ *Untuk repositori dan gambar ECR Amazon publik, lihat repositori publik [Amazon ECR dan [gambar publik di](https://docs.aws.amazon.com/AmazonECR/latest/public/public-images.html) Panduan Pengguna](https://docs.aws.amazon.com/AmazonECR/latest/public/public-repositories.html) Publik Amazon ECR.*
Setelah Anda membuat gambar Anda sendiri, Anda dapat mendeklarasikan variabel lingkungan berikut sebelum membangun solusi khusus Anda.
```
#!/bin/bash
export PUBLIC_ECR_REGISTRY=YOUR_ECR_REGISTRY_URI # e.g. YOUR_ACCOUNT_ID.dkr.ecr.us-east-1.amazonaws.com/YOUR_IMAGE_NAME
export PUBLIC_ECR_TAG=YOUR_ECR_TAG # e.g. latest, v3.4.0
```
Contoh berikut menunjukkan file kontainer.
```
FROM public.ecr.aws/amazonlinux/amazonlinux:2023-minimal
RUN dnf update -y && \
dnf install -y python3.11 python3.11-pip java-21-amazon-corretto bc procps jq findutils unzip && \
dnf clean all
ENV PIP_INSTALL="pip3.11 install --no-cache-dir"
# install bzt
RUN $PIP_INSTALL --upgrade bzt awscli setuptools==78.1.1 h11 urllib3==2.2.2 && \
$PIP_INSTALL --upgrade bzt
COPY ./.bzt-rc /root/.bzt-rc
RUN chmod 755 /root/.bzt-rc
# install bzt tools
RUN bzt -install-tools -o modules.install-checker.exclude=selenium,gatling,tsung,siege,ab,k6,external-results-loader,locust,junit,testng,rspec,mocha,nunit,xunit,wdio,robot,newman
RUN rm -rf /root/.bzt/selenium-taurus
RUN mkdir /bzt-configs /tmp/artifacts
ADD ./load-test.sh /bzt-configs/
ADD ./*.jar /bzt-configs/
ADD ./*.py /bzt-configs/
RUN chmod 755 /bzt-configs/load-test.sh
RUN chmod 755 /bzt-configs/ecslistener.py
RUN chmod 755 /bzt-configs/ecscontroller.py
RUN chmod 755 /bzt-configs/jar_updater.py
RUN python3.11 /bzt-configs/jar_updater.py
# Remove jar files from /tmp
RUN rm -rf /tmp/jmeter-plugins-manager-1* && \
rm -rf /usr/local/lib/python3.11/site-packages/setuptools-65.5.0.dist-info && \
rm -rf /usr/local/lib/python3.11/site-packages/urllib3-1.26.17.dist-info
# Add settings file to capture the output logs from bzt cli
RUN mkdir -p /etc/bzt.d && echo '{"settings": {"artifacts-dir": "/tmp/artifacts"}}' > /etc/bzt.d/90-artifacts-dir.json
WORKDIR /bzt-configs
ENTRYPOINT ["./load-test.sh"]
```
Selain file kontainer, direktori berisi skrip bash berikut yang mengunduh konfigurasi pengujian dari Amazon S3 sebelum menjalankan Taurus/Blazemeter program.
```
#!/bin/bash
# set a uuid for the results xml file name in S3
UUID=$(cat /proc/sys/kernel/random/uuid)
pypid=0
echo "S3_BUCKET:: ${S3_BUCKET}"
echo "TEST_ID:: ${TEST_ID}"
echo "TEST_TYPE:: ${TEST_TYPE}"
echo "FILE_TYPE:: ${FILE_TYPE}"
echo "PREFIX:: ${PREFIX}"
echo "UUID:: ${UUID}"
echo "LIVE_DATA_ENABLED:: ${LIVE_DATA_ENABLED}"
echo "MAIN_STACK_REGION:: ${MAIN_STACK_REGION}"
cat /proc/self/cgroup
TASK_ID=$(grep -oE '[a-f0-9]{32}' /proc/self/cgroup | head -n 1)
echo $TASK_ID
sigterm_handler() {
if [ $pypid -ne 0 ]; then
echo "container received SIGTERM."
kill -15 $pypid
wait $pypid
exit 143 #128 + 15
fi
}
trap 'sigterm_handler' SIGTERM
echo "Download test scenario"
aws s3 cp s3://$S3_BUCKET/test-scenarios/$TEST_ID-$AWS_REGION.json test.json --region $MAIN_STACK_REGION
# Set the default log file values to jmeter
LOG_FILE="jmeter.log"
OUT_FILE="jmeter.out"
ERR_FILE="jmeter.err"
KPI_EXT="jtl"
# download JMeter jmx file
if [ "$TEST_TYPE" != "simple" ]; then
# setting the log file values to the test type
LOG_FILE="${TEST_TYPE}.log"
OUT_FILE="${TEST_TYPE}.out"
ERR_FILE="${TEST_TYPE}.err"
# set variables based on TEST_TYPE
if [ "$TEST_TYPE" == "jmeter" ]; then
EXT="jmx"
TYPE_NAME="JMeter"
# Copy *.jar to JMeter library path. See the Taurus JMeter path: https://gettaurus.org/docs/JMeter/
JMETER_LIB_PATH=`find ~/.bzt/jmeter-taurus -type d -name "lib"`
echo "cp $PWD/*.jar $JMETER_LIB_PATH"
cp $PWD/*.jar $JMETER_LIB_PATH
elif [ "$TEST_TYPE" == "k6" ]; then
curl --output /tmp/artifacts/k6.rpm https://dl.k6.io/rpm/x86_64/k6-v0.58.0-amd64.rpm
rpm -ivh /tmp/artifacts/k6.rpm
dnf install -y k6
rm -rf /tmp/artifacts/k6.rpm
EXT="js"
KPI_EXT="csv"
TYPE_NAME="K6"
elif [ "$TEST_TYPE" == "locust" ]; then
EXT="py"
TYPE_NAME="Locust"
fi
if [ "$FILE_TYPE" != "zip" ]; then
aws s3 cp s3://$S3_BUCKET/public/test-scenarios/$TEST_TYPE/$TEST_ID.$EXT ./ --region $MAIN_STACK_REGION
else
aws s3 cp s3://$S3_BUCKET/public/test-scenarios/$TEST_TYPE/$TEST_ID.zip ./ --region $MAIN_STACK_REGION
unzip $TEST_ID.zip
echo "UNZIPPED"
ls -l
# If zip and locust, make sure to pick locustfile
if [ "$TEST_TYPE" != "locust" ]; then
TEST_SCRIPT=$(find . -name "*.${EXT}" | head -n 1)
else
TEST_SCRIPT=$(find . -name "locustfile.py" | head -n 1)
fi
# only looks for the first test script file.
TEST_SCRIPT=`find . -name "*.${EXT}" | head -n 1`
echo $TEST_SCRIPT
if [ -z "$TEST_SCRIPT" ]; then
echo "There is no test script (.${EXT}) in the zip file."
exit 1
fi
sed -i -e "s|$TEST_ID.$EXT|$TEST_SCRIPT|g" test.json
# copy bundled plugin jars to jmeter extension folder to make them available to jmeter
BUNDLED_PLUGIN_DIR=`find $PWD -type d -name "plugins" | head -n 1`
# attempt to copy only if a /plugins folder is present in upload
if [ -z "$BUNDLED_PLUGIN_DIR" ]; then
echo "skipping plugin installation (no /plugins folder in upload)"
else
# ensure the jmeter extensions folder exists
JMETER_EXT_PATH=`find ~/.bzt/jmeter-taurus -type d -name "ext"`
if [ -z "$JMETER_EXT_PATH" ]; then
# fail fast - if plugins bundled they will be needed for the tests
echo "jmeter extension path (~/.bzt/jmeter-taurus/**/ext) not found - cannot install bundled plugins"
exit 1
fi
cp -v $BUNDLED_PLUGIN_DIR/*.jar $JMETER_EXT_PATH
fi
fi
fi
#Download python script
if [ -z "$IPNETWORK" ]; then
python3.11 -u $SCRIPT $TIMEOUT &
pypid=$!
wait $pypid
pypid=0
else
aws s3 cp s3://$S3_BUCKET/Container_IPs/${TEST_ID}_IPHOSTS_${AWS_REGION}.txt ./ --region $MAIN_STACK_REGION
export IPHOSTS=$(cat ${TEST_ID}_IPHOSTS_${AWS_REGION}.txt)
python3.11 -u $SCRIPT $IPNETWORK $IPHOSTS
fi
echo "Running test"
stdbuf -i0 -o0 -e0 bzt test.json -o modules.console.disable=true | stdbuf -i0 -o0 -e0 tee -a result.tmp | sed -u -e "s|^|$TEST_ID $LIVE_DATA_ENABLED |"
CALCULATED_DURATION=`cat result.tmp | grep -m1 "Test duration" | awk -F ' ' '{ print $5 }' | awk -F ':' '{ print ($1 * 3600) + ($2 * 60) + $3 }'`
# upload custom results to S3 if any
# every file goes under $TEST_ID/$PREFIX/$UUID to distinguish the result correctly
if [ "$TEST_TYPE" != "simple" ]; then
if [ "$FILE_TYPE" != "zip" ]; then
cat $TEST_ID.$EXT | grep filename > results.txt
else
cat $TEST_SCRIPT | grep filename > results.txt
fi
if [ -f results.txt ]; then
sed -i -e 's///g' results.txt
sed -i -e 's/<\/stringProp>//g' results.txt
sed -i -e 's/ //g' results.txt
echo "Files to upload as results"
cat results.txt
files=(`cat results.txt`)
extensions=()
for f in "${files[@]}"; do
ext="${f##*.}"
if [[ ! " ${extensions[@]} " =~ " ${ext} " ]]; then
extensions+=("$ext")
fi
done
# Find all files in the current folder with the same extensions
all_files=()
for ext in "${extensions[@]}"; do
for f in *."$ext"; do
all_files+=("$f")
done
done
for f in "${all_files[@]}"; do
p="s3://$S3_BUCKET/results/$TEST_ID/${TYPE_NAME}_Result/$PREFIX/$UUID/$f"
if [[ $f = /* ]]; then
p="s3://$S3_BUCKET/results/$TEST_ID/${TYPE_NAME}_Result/$PREFIX/$UUID$f"
fi
echo "Uploading $p"
aws s3 cp $f $p --region $MAIN_STACK_REGION
done
fi
fi
if [ -f /tmp/artifacts/results.xml ]; then
# Insert the Task ID at the same level as
curl -s $ECS_CONTAINER_METADATA_URI_V4/task
Task_CPU=$(curl -s $ECS_CONTAINER_METADATA_URI_V4/task | jq '.Limits.CPU')
Task_Memory=$(curl -s $ECS_CONTAINER_METADATA_URI_V4/task | jq '.Limits.Memory')
START_TIME=$(curl -s "$ECS_CONTAINER_METADATA_URI_V4/task" | jq -r '.Containers[0].StartedAt')
# Convert start time to seconds since epoch
START_TIME_EPOCH=$(date -d "$START_TIME" +%s)
# Calculate elapsed time in seconds
CURRENT_TIME_EPOCH=$(date +%s)
ECS_DURATION=$((CURRENT_TIME_EPOCH - START_TIME_EPOCH))
sed -i.bak 's/<\/FinalStatus>/'"$TASK_ID"'<\/TaskId><\/FinalStatus>/' /tmp/artifacts/results.xml
sed -i 's/<\/FinalStatus>/'"$Task_CPU"'<\/TaskCPU><\/FinalStatus>/' /tmp/artifacts/results.xml
sed -i 's/<\/FinalStatus>/'"$Task_Memory"'<\/TaskMemory><\/FinalStatus>/' /tmp/artifacts/results.xml
sed -i 's/<\/FinalStatus>/'"$ECS_DURATION"'<\/ECSDuration><\/FinalStatus>/' /tmp/artifacts/results.xml
echo "Validating Test Duration"
TEST_DURATION=$(grep -E '[0-9]+.[0-9]+' /tmp/artifacts/results.xml | sed -e 's///' | sed -e 's/<\/TestDuration>//')
if (( $(echo "$TEST_DURATION > $CALCULATED_DURATION" | bc -l) )); then
echo "Updating test duration: $CALCULATED_DURATION s"
sed -i.bak.td 's/[0-9]*\.[0-9]*<\/TestDuration>/'"$CALCULATED_DURATION"'<\/TestDuration>/' /tmp/artifacts/results.xml
fi
if [ "$TEST_TYPE" == "simple" ]; then
TEST_TYPE="jmeter"
fi
echo "Uploading results, bzt log, and JMeter log, out, and err files"
aws s3 cp /tmp/artifacts/results.xml s3://$S3_BUCKET/results/${TEST_ID}/${PREFIX}-${UUID}-${AWS_REGION}.xml --region $MAIN_STACK_REGION
aws s3 cp /tmp/artifacts/bzt.log s3://$S3_BUCKET/results/${TEST_ID}/bzt-${PREFIX}-${UUID}-${AWS_REGION}.log --region $MAIN_STACK_REGION
aws s3 cp /tmp/artifacts/$LOG_FILE s3://$S3_BUCKET/results/${TEST_ID}/${TEST_TYPE}-${PREFIX}-${UUID}-${AWS_REGION}.log --region $MAIN_STACK_REGION
aws s3 cp /tmp/artifacts/$OUT_FILE s3://$S3_BUCKET/results/${TEST_ID}/${TEST_TYPE}-${PREFIX}-${UUID}-${AWS_REGION}.out --region $MAIN_STACK_REGION
aws s3 cp /tmp/artifacts/$ERR_FILE s3://$S3_BUCKET/results/${TEST_ID}/${TEST_TYPE}-${PREFIX}-${UUID}-${AWS_REGION}.err --region $MAIN_STACK_REGION
aws s3 cp /tmp/artifacts/kpi.${KPI_EXT} s3://$S3_BUCKET/results/${TEST_ID}/kpi-${PREFIX}-${UUID}-${AWS_REGION}.${KPI_EXT} --region $MAIN_STACK_REGION
else
echo "An error occurred while the test was running."
fi
```
Selain [Dockerfile](https://docs.docker.com/engine/reference/builder/) dan skrip bash, dua skrip Python juga disertakan dalam direktori. Setiap tugas menjalankan skrip Python dari dalam skrip bash. Tugas pekerja menjalankan `ecslistener.py` skrip, sedangkan tugas pemimpin akan menjalankan `ecscontroller.py` skrip. `ecslistener.py`Skrip membuat soket pada port 50000 dan menunggu pesan. `ecscontroller.py`Skrip terhubung ke soket dan mengirimkan pesan uji awal ke tugas pekerja, yang memungkinkan mereka untuk memulai secara bersamaan.