Before you can run the PerfKit Benchmarker, you need account(s) on the cloud provider(s) you want to benchmark:
This section describes the setup steps needed for each cloud system. Note that
you only need to perform setup steps on the clouds you wish to test. If you only
want to test Google Cloud, you only need to install and configure gcloud
.
- Google Cloud
- OpenStack
- Kubernetes
- Mesos
- Cloudstack
- AWS
- Azure
- IBMCloud
- AliCloud
- DigitalOcean
- RackSpace
- ProfitBricks
After configuring the clouds you intend to use, skip to Running a Single Benchmark, unless you are going to use an object storage benchmark, in which case you need to configure a boto file.
Follow the instructions at: https://developers.google.com/cloud/sdk/. When prompted, pick the local folder, then Python project, then the defaults for all the rest.
Restart your shell window (or logout/ssh again if running on a VM)
Next, create a project by visiting Google Cloud Console. After that, run:
$ gcloud init
which helps you authenticate, set your project, and set some defaults.
Alternatively, if that is already set up, and you just need to authenticate, you can use:
$ gcloud auth login
For help, see gcloud
docs.
Make sure you have installed pip (see the section above).
Install OpenStack CLI utilities via the following command:
$ pip install -r perfkitbenchmarker/providers/openstack/requirements.txt
To setup credentials and endpoint information simply set the environment
variables using an OpenStack RC file. For help, see
OpenStack
docs
Perfkit uses the kubectl
binary in order to communicate with a Kubernetes
cluster - you need to pass the path to the kubectl
binary using the
--kubectl
flag. It's recommended to use
version 1.0.1.
Authentication to a Kubernetes cluster is done via a
kubeconfig
file.
Its path is passed using the --kubeconfig
flag.
Image prerequisites Please refer to the Image prerequisites for Docker based clouds.
Kubernetes cluster configuration If your Kubernetes cluster is running on CoreOS:
-
Fix
$PATH
environment variable so that the appropriate binaries can be found:$ sudo mkdir /etc/systemd/system/kubelet.service.d $ sudo vim /etc/systemd/system/kubelet.service.d/10-env.conf
Add the following line to the
[Service]
section:Environment=PATH=/opt/bin:/usr/bin:/usr/sbin:$PATH
-
Reboot the node:
$ sudo reboot
Note that some benchmarks must be run within a privileged container. By default
Kubernetes doesn't allow containers to be scheduled in privileged mode - you
have to add the --allow-privileged=true
flag to kube-apiserver
and each
kubelet
startup command.
Ceph integration When you run benchmarks with the standard scratch disk type
(--scratch_disk_type=standard
- which is a default option), Ceph storage will
be used. There are some configuration steps you need to follow before you will
be able to spawn Kubernetes PODs with Ceph volume. On each Kubernetes node, and
on the machine which is running the Perfkit benchmarks, do the following:
-
Copy
/etc/ceph
directory from Ceph-host. -
Install
ceph-common
package so thatrbd
command is available:-
If your Kubernetes cluster is running on CoreOS, then you need to create a bash script called
rbd
which will run therbd
command inside a Docker container:#!/usr/bin/bash /usr/bin/docker run -v /etc/ceph:/etc/ceph -v /dev:/dev -v /sys:/sys --net=host --privileged=true --rm=true ceph/rbd $@
Save the file as
rbd
and run:$ chmod +x rbd $ sudo mkdir /opt/bin $ sudo cp rbd /opt/bin
Install
rbdmap
:$ git clone https://github.com/ceph/ceph-docker.git $ cd ceph-docker/examples/coreos/rbdmap/ $ sudo mkdir /opt/sbin $ sudo cp rbdmap /opt/sbin $ sudo cp ceph-rbdnamer /opt/bin $ sudo cp 50-rbd.rules /etc/udev/rules.d $ sudo reboot
-
You have two Ceph authentication options available:
-
Keyring - pass the path to the keyring file using
--ceph_keyring
flag -
Secret. In this case you have to create a secret first:
Retrieve base64-encoded Ceph admin key:
$ ceph auth get-key client.admin | base64 QVFEYnpPWlZWWnJLQVJBQXdtNDZrUDlJUFo3OXdSenBVTUdYNHc9PQ==
Create a file called
create_ceph_admin.yml
and replace thekey
value with the output from the previous command:apiVersion: v1 kind: Secret metadata: name: my-ceph-secret data: key: QVFEYnpPWlZWWnJLQVJBQXdtNDZrUDlJUFo3OXdSenBVTUdYNHc9PQ==
Add secret to Kubernetes:
$ kubectl create -f create_ceph_admin.yml
You will have to pass the Secret name (using
--ceph_secret
flag) when running the benchmakrs. In this case it should be:--ceph_secret=my-ceph-secret
.
Mesos provider communicates with Marathon framework in order to manage Docker
instances. Thus it is required to setup Marathon framework along with the Mesos
cluster. In order to connect to Mesos you need to provide IP address and port to
Marathon framework using --marathon_address
flag.
Provider has been tested with Mesos v0.24.1 and Marathon v0.11.1.
Overlay network Mesos on its own doesn't provide any solution for overlay networking. You need to configure your cluster so that the instances will live in the same network. For this purpose you may use Flannel, Calico, Weave, etc.
Mesos cluster configuration Make sure your Mesos-slave nodes are reachable
(by hostname) from the machine which is used to run the benchmarks. In case they
are not, edit the /etc/hosts
file appropriately.
Image prerequisites Please refer to the Image prerequisites for Docker based clouds.
$ pip install -r perfkitbenchmarker/providers/cloudstack/requirements.txt
Get the API key and SECRET from Cloudstack. Set the following environement variables.
export CS_API_URL=<insert API endpoint>
export CS_API_KEY=<insert API key>
export CS_API_SECRET=<insert API secret>
Specify the network offering when running the benchmark. If using VPC
(--cs_use_vpc
), also specify the VPC offering (--cs_vpc_offering
).
$ ./pkb.py --cloud=CloudStack --benchmarks=ping --cs_network_offering=DefaultNetworkOffering
Make sure you have installed pip (see the section above).
Follow instructions at http://aws.amazon.com/cli/ or run the following command (omit the 'sudo' on Windows)
$ pip install -r perfkitbenchmarker/providers/aws/requirements.txt
Navigate to the AWS console to create access credentials: https://console.aws.amazon.com/ec2/
- On the console click on your name (top left)
- Click on "Security Credentials"
- Click on "Access Keys", the create New Access Key. Download the file, it contains the Access key and Secret keys to access services. Note the values and delete the file.
Configure the CLI using the keys from the previous step:
$ aws configure
This version of Perfkit Benchmarker is known to be compatible with Azure CLI version 2.0.75, and will likely work with any version newer than that.
Follow the instructions at https://docs.microsoft.com/en-us/cli/azure/install-azure-cli or on Linux, run the following commands:
$ curl -L https://aka.ms/InstallAzureCli | bash
$ az login
Test that azure
is installed correctly:
$ az vm list
Finally, make sure that your account is authorized to allocate VMs and networks from Azure:
$ az provider register -n Microsoft.Compute
$ az provider register -n Microsoft.Network
Get the API key and API endpoints from IBM Cloud. Set the following environment variables.
export IBMCLOUD_AUTH_ENDPOINT=https://iam.cloud.ibm.com/identity/token
export IBMCLOUD_ENDPOINT=<API Endpoint, e.g. https://us-south.iaas.cloud.ibm.com>
export IBMCLOUD_ACCOUNT_ID=<account id>
export IBMCLOUD_APIKEY=<API key>
To change default region and zone, point IBMCLOUD_ENDPOINT to the correct endpoint and set these parameters.
--ibmcloud_region=<region e.g. us-east>
--zones=<zone e.g. us-east-2>
Use os_type to change OS image.
--os_type=debian10
For cross zones network test, set zones to a comma separated string like us-east-1,us-east-2
$ ./pkb.py --cloud=IBMCloud --benchmarks=iperf --machine_type=cx2-4x8 \
--ibmcloud_region=us-east --zones=us-east-1,us-east-2 --os_type=debian10
-
Download Linux installer from Aliyun Github. Follow instructions from Readme to install for your OS.
-
Verify that aliyun CLI is working as expected:
$ aliyun ecs help
-
Navigate to the AliCloud console to create access credentials:
- Login first
- Click on "AccessKeys" (top right)
- Click on "Create Access Key", copy and store the "Access Key ID" and "Access Key Secret" to a safe place.
- Configure the CLI using the Access Key ID and Access Key Secret from the previous step
$ aliyun configure
-
Install
doctl
, the DigitalOcean CLI, following the instructions athttps://github.com/digitalocean/doctl
. -
Authenticate with
doctl
. The easiest way is runningdoctl auth login
and following the instructions, but any of the options at thedoctl
site will work.
In order to interact with the Rackspace Public Cloud, PerfKitBenchmarker makes use of RackCLI. You can find the instructions to install and configure RackCLI here: https://developer.rackspace.com/docs/rack-cli/
To run PerfKit Benchmarker against Rackspace is very easy. Simply make sure Rack
CLI is installed and available in your PATH, optionally use the flag
--rack_path
to indicate the path to the binary.
For a Rackspace UK Public Cloud account, unless it's your default RackCLI
profile then it's recommended that you create a profile for your UK account.
Once configured, use flag --profile
to specify which RackCLI profile to use.
You can find more details here:
https://developer.rackspace.com/docs/rack-cli/configuration/#config-file
Note: Not all flavors are supported on every region. Always check first if the flavor is supported in the region.
Get started by running:
$ pip install -r
perfkitbenchmarker/providers/profitbricks/requirements.txt
PerfKit Benchmarker uses the Requests module to interact with ProfitBricks' REST API. HTTP Basic authentication is used to authorize access to the API. Please set this up as follows:
Create a configuration file containing the email address and password associated with your ProfitBricks account, separated by a colon. Example:
$ less ~/.config/profitbricks-auth.cfg
email:password
The PerfKit Benchmarker will automatically base64 encode your credentials before making any calls to the REST API.
PerfKit Benchmarker uses the file location ~/.config/profitbricks-auth.cfg
by
default. You can use the --profitbricks_config
flag to override the path.
Docker instances by default don't allow to SSH into them. Thus it is important
to configure your Docker image so that it has SSH server installed. You can use
your own image or build a new one based on a Dockerfile placed in
tools/docker_images
directory - in this case please refer to
Docker images document.
In order to run object storage benchmark tests, you need to have a properly
configured ~/.boto
file. The directions require that you have installed
google-cloud-sdk
. The directions for doing that are in the
gcloud installation section.
Here is how:
- Create the
~/.boto
file (If you already have ~/.boto, you can skip this step. Consider making a backup copy of your existing .boto file.)
To create a new ~/.boto
file, issue the following command and follow the
instructions given by this command:
$ gsutil config
As a result, a .boto
file is created under your home directory.
Open the .boto
file and edit the following fields:
-
In the [Credentials] section:
gs_oauth2_refresh_token
: set it to be the same as therefresh_token
field in your gcloud credential file (~/.config/gcloud/credentials.db), which was setup as part of thegcloud auth login
step. To see the refresh token, run$ strings ~/.config/gcloud/credentials.db.
aws_access_key_id
,aws_secret_access_key
: set these to be the AWS access keys you intend to use for these tests, or you can use the same keys as those in your existing AWS credentials file (~/.aws/credentials
). -
In the
[GSUtil]
section:default_project_id
: if it is not already set, set it to be the google cloud storage project ID you intend to use for this test. (If you usedgsutil config
to generate the.boto
file, you should have been prompted to supply this information at this step). -
In the
[OAuth2]
section:client_id
,client_secret
: set these to be the same as those in your gcloud credentials file (~/.config/gcloud/credentials.db
), which was setup as part of thegcloud auth login
step.