Perf-Bench

Continuous Benchmarking

The Benchmark action runs performance benchmarks on Constellation clusters. The benchmark suite records storage and network benchmarks.

After testing, the action compares the results of the benchmarks to previous results of Constellation on the same cloud provider. That way, it is possible to evaluate performance progression throughout the development.

The data of previous benchmarks is stored in the private S3 artifact store.

In order to support encrypted storage, the action deploys the Azure CSI and GCP CSI drivers.

For the network benchmark we utilize the knb tool of the k8s-bench-suite.

For the storage benchmark we utilize kubestr to run FIO tests.

Displaying Performance Progression

The action creates a summary of the action and attaches it the workflow execution log.

The table compares the current benchmark results of Constellation on the selected cloud provider to the previous records (of Constellation on the cloud provider).

The hashes of the two commits that are the base for the comparison are prepended to the table.

Example table:

Commit of current benchmark: 8eb0a6803bc431bcebc2f6766ab2c6376500e106
Commit of previous benchmark: 8f733daaf5c5509f024745260220d89ef8e6e440

Benchmark suite	Metric	Current	Previous	Ratio
read_iops	iops (IOPS)	213.6487	216.74684	0.986 ⬇️
write_iops	iops (IOPS)	24.412066	18.051243	1.352 ⬆️
read_bw	bw_kbytes (KiB/s)	28302.0	28530.0	0.992 ⬇️
write_bw	bw_kbytes (KiB/s)	4159.0	2584.0	1.61 ⬆️
pod2pod	tcp_bw_mbit (MiB/s)	20450.0	929.0	22.013 ⬆️
pod2pod	udp_bw_mbit (MiB/s)	1138.0	750.0	1.517 ⬆️
pod2svc	tcp_bw_mbit (MiB/s)	21188.0	905.0	23.412 ⬆️
pod2svc	udp_bw_mbit (MiB/s)	1137.0	746.0	1.524 ⬆️

Updating Stored Records

Managed Kubernetes

One must manually update the stored benchmark records of managed Kubernetes:

AKS

Follow the Azure documentation to create an AKS cluster of desired benchmarking settings (region, instance types). If comparing against Constellation clusters with CVM instances, make sure to select the instance type on AKS as well.

For example:

az aks create -g moritz-constellation -n benchmark --node-count 2
az aks get-credentials -g moritz-constellation -n benchmark

Once the cluster is ready, set up managing access via kubectl and take the benchmark:

# Setup knb
git clone https://github.com/InfraBuilder/k8s-bench-suite.git
cd k8s-bench-suite
install knb /usr/local/bin
cd ..

# Setup kubestr
case "$(go env GOOS)" in "darwin") HOSTOS="MacOS";; *) HOSTOS="$(go env GOOS)";; esac
HOSTARCH="$(go env GOARCH)"
KUBESTR_VER=0.4.37
curl -fsSLO https://github.com/kastenhq/kubestr/releases/download/v${KUBESTR_VER}/kubestr_${KUBESTR_VER}_${HOSTOS}_${HOSTARCH}.tar.gz
tar -xzf kubestr_${KUBESTR_VER}_${HOSTOS}_${HOSTARCH}.tar.gz
install kubestr /usr/local/bin


# Run kubestr
mkdir -p out
kubestr fio -e "out/fio-AKS.json" -o json -s default -z 400Gi

# Run knb
workers="$(kubectl get nodes | grep nodepool)"
server="$(echo $workers | head -1 | tail -1 |cut -d ' ' -f1|tr '\n' ' ')"
client="$(echo $workers | head -2 | tail -1 |cut -d ' ' -f1|tr '\n' ' ')"
knb -f "out/knb-AKS.json" -o json --server-node $server --client-node $client


# Benchmarks done, do processing.

# Parse
git clone https://github.com/edgelesssys/constellation.git
mkdir -p benchmarks
export BDIR=benchmarks
export CSP=azure
export EXT_NAME=AKS
export BENCH_RESULTS=out/

python constellation/.github/actions/e2e_benchmark/evaluate/parse.py

# Upload result to S3
S3_PATH=s3://edgeless-artifact-store/constellation/benchmarks
aws s3 cp benchmarks/AKS.json ${S3_PATH}/AKS.json

GKE

Create a GKE cluster of desired benchmarking settings (region, instance types). If comparing against Constellation clusters with CVM instances, make sure to select the matching instance type on GKE. For example:

gcloud container clusters create benchmark \
    --zone europe-west3-b \
    --node-locations europe-west3-b \
    --machine-type n2d-standard-4 \
    --num-nodes 2
gcloud container clusters get-credentials benchmark --region europe-west3-b
# create storage class for pd-standard
cat <<EOF | kubectl apply -f -
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: pd-standard
provisioner: pd.csi.storage.gke.io
volumeBindingMode: WaitForFirstConsumer
allowVolumeExpansion: true
parameters:
  type: pd-standard
EOF

Once the cluster is ready, set up managing access via kubectl and take the benchmark:

# Setup knb
git clone https://github.com/InfraBuilder/k8s-bench-suite.git
cd k8s-bench-suite
install knb /usr/local/bin
cd ..

# Setup kubestr
case "$(go env GOOS)" in "darwin") HOSTOS="MacOS";; *) HOSTOS="$(go env GOOS)";; esac
HOSTARCH="$(go env GOARCH)"
KUBESTR_VER=0.4.37
curl -fsSLO https://github.com/kastenhq/kubestr/releases/download/v${KUBESTR_VER}/kubestr_${KUBESTR_VER}_${HOSTOS}_${HOSTARCH}.tar.gz
tar -xzf kubestr_${KUBESTR_VER}_${HOSTOS}_${HOSTARCH}.tar.gz
install kubestr /usr/local/bin

# Run kubestr
mkdir -p out
kubestr fio -e "out/fio-GKE.json" -o json -s pd-standard -z 400Gi

# Run knb
workers="$(kubectl get nodes | grep default-pool)"
server="$(echo $workers | head -1 | tail -1 |cut -d ' ' -f1|tr '\n' ' ')"
client="$(echo $workers | head -2 | tail -1 |cut -d ' ' -f1|tr '\n' ' ')"
knb -f "out/knb-GKE.json" -o json --server-node "$server" --client-node "$client"


# Parse
git clone https://github.com/edgelesssys/constellation.git
mkdir -p benchmarks
export BDIR=benchmarks
export CSP=gcp
export EXT_NAME=GKE
export BENCH_RESULTS=out/

python constellation/.github/actions/e2e_benchmark/evaluate/parse.py

# Upload result to S3
S3_PATH=s3://edgeless-artifact-store/constellation/benchmarks
aws s3 cp benchmarks/GKE.json ${S3_PATH}/GKE.json

Constellation

The action updates the stored Constellation records for the selected cloud provider when running on the main branch.

Drawing Performance Charts

The action also contains the code to draw graphs as used in the Constellation docs. The graphs compare the performance of Constellation to the performance of managed Kubernetes clusters. It expects the results of [AKS.json, GKE.json, constellation-azure.json, constellation-gcp.json] to be present in the BDIR folder.

Graphs can thne be created from using the graphs.py script:

BDIR=benchmarks
python ./graph.py

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