µBench is a tool for benchmarking cloud/edge computing platforms that run microservice applications. The tool creates dummy microservice applications that can be customized by the user and run on Kubernetes.
µBench targets researchers and cloud platform developers who lack real microservice applications to benchmark their findings (e.g., new resource control mechanisms, AI-driven orchestration, etc.). Indeed, µBench can create these applications for them. At the same time, µBench can also be used for educational purposes to show advantages and problems of microservice applications to students.
µBench allows users control some properties of the microservice application it creates, such as: - the topology of the service mesh
- the behaviors of composing microservices using a portfolio of stress functions (e.g. for CPU, memory, I/O, network) or implementing new ones,
- the microservice-to-microservice API (HTTP or gRPC)
- the CPU and Memory resources assigned to microservices and their number of replicas
µBench provides a comprehensive monitoring framework consisting of Prometheus, Grafana, Istio, Kiali, and Jaeger through which to observe the performance of the produced benchmark applications.
You can learn how to use µBench to create and monitor your application by reading the µBench manual.
For a complete install guide, head over to the manual. Instead, for a quick hands-on with µBench the following commands will deploy a microservice application composed of 10 services with a star topology service mesh. Clients send requests to s0 and s0 sequentially calls all other services before sending the result to clients. Each service equally stresses the CPU.
We assume that on your host, you have Docker and have access to a Kubernetes cluster with kubectl tool. If you need to configure a Kubernetes cluster (e.g., with Minikube) or for other configurations read the manual.
We will use the Docker µBench container that contains all the necessary software.
Run the µBench container
docker run -d --name mubench msvcbench/mubenchCopy the .kube/config file you use in your host to access the Kubernetes cluster in the container
kubectl config view --flatten > config
docker cp config mubench:/root/.kube/configVerify that µBench container can access your cluster, e.g., by using next command from your host
docker exec mubench kubectl get nodesEnter the µBench container with:
docker exec -it mubench bashNow your terminal should be in the µBench container from which you will run next commands
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root@64ae03d1e5b8:~# Deploy the µBench demo app with
cd $HOME/muBench
python3 Deployers/K8sDeployer/RunK8sDeployer.py -c Configs/K8sParameters.jsonCheck the correct deployment of the application pods with
kubectl get pods You should see the following pods
root@64ae03d1e5b8:~/muBench# k get pods
NAME READY STATUS RESTARTS AGE
gw-nginx-5b66796c85-fpqvc 2/2 Running 0 11m
s0-7d7f8c875b-gk2pq 2/2 Running 0 11m
s1-8fcb67d75-pncwq 2/2 Running 0 11m
s2-558f544b94-kft64 2/2 Running 0 11m
s3-79485f9857-5j79h 2/2 Running 0 11m
s4-9b6f9f77b-dklvm 2/2 Running 0 11m
s5-6ccddd9b47-n5pz7 2/2 Running 0 11m
s6-7c87c79cd6-pt26s 2/2 Running 0 11m
s7-5fb7cbff7c-hkd6t 2/2 Running 0 11m
s8-5549949968-72q2z 2/2 Running 0 11m
s9-9576b784c-4npsj 2/2 Running 0 11mTest the correct execution of the application with
curl http://<MASTER_IP>:31113/s0where MASTER_IP is the IP address of the master-node of the Kubernetes cluster.
If you receive back a sequence of random letters, it means that your first µBench app is running :-).
Read the manual to create and monitor your benchmark apps.
NOTE:: edit Configs/K8sParameters.json if your Kubernetes dns-resolver service is different from
kube-dns. For instance, for some clusters it is namedcoredns. Otherwise, nginx pod gets error status.
The description of µBench and some use-cases has been published in IEEE Transactions on Parallel and Distributed Systems. If you use the µBench please cite the following publication:
A. Detti, L. Funari, L. Petrucci, "µBench: an open-source factory of benchmark microservice applications", IEEE Transactions on Parallel and Distributed Systems
To reproduce the tests of the paper read here
This software is supported by:
- Liquid_Edge project, funded by Italian Ministry of University and Research within the PRIN 2017 program.
- Italian PNRR Restart Program