1. Create a GCP account (if you haven’t already) at https://cloud.google.com
2. Enable billing on Google cloud platform. Instructions [here](https://cloud.google.com/container-engine/docs/before-you-begin)(see the '*Enable billing*' section).
3. Create a Project from the [GCP console](https://console.cloud.google.com)
4. Enable the Container Engine API. Instructions [here](https://cloud.google.com/container-engine/docs/before-you-begin)(See the '*Enable the Container Engine API*’ section).
5. Create a Cluster from the GCP console. i.e Go to the Container Engine section from GCP console and click ‘Create Container Cluster’ and follow the instructions.
5.1. The instructions for Name/Zone/MachineType etc are [here](https://cloud.google.com/container-engine/docs/clusters/operations)(**NOTE**: The page also has instructions to setting up default clusters and configuring `kubectl`. We will be doing that later)
5.2. For the cluster size, a smaller size of < 10 GCE instances is good enough for our use cases - assuming that we are planning to run a reasonably small number of stress client instances.
5.3. **IMPORTANT**: Before hitting the "Create" button, click on “More” link just above the "Create" button and Select "Enabled" for BigQuery , "Enabled" for Cloud Platform and "Read/Write" for Cloud User Accounts.
5.4. Create the cluster by clicking "Create" button.
#### *On your machine* (or the machine from which stress tests on GKE are launched):
1. You need a working gRPC repository on your machine. If you do not have it, clone the grpc repository from github (https://github.com/grpc/grpc) and follow the instructions at https://github.com/grpc/grpc/blob/master/INSTALL.md
**Note**: Do `$ easy_install -U pip` if you do not have pip
6. Install the `requests` Python package if you don’t have it already. Instructions are [here](http://docs.python-requests.org/en/master/user/install/)
7. Set the `gcloud` defaults: See the instructions at https://cloud.google.com/container-engine/docs/before-you-begin under "*Set gcloud defaults*" section)
7.1. Make sure you also fetch the cluster credentials for `kubectl` command to use. I.e `$ gcloud container clusters get-credentials CLUSTER_NAME`
### **Launching Stress tests**
The stress tests are launched by the following script (path is relative to GRPC root directory) :
>Launches the 5 instances of stress test clients, 1 instance of stress test server and runs the test for 180 seconds. The test would be run on the default container cluster (that you have set in `gcloud`) in the project `sree-gce`.
> Note: we currently do not have the ability to launch multiple instances of the server. This can be added very easily in future
all `kubectl`, Kubernetes command line tool using `gcloud`
**Note**: Do `$ easy_install -U pip` if you do not have pip
6. Install the `requests` Python package if you don’t have it already. Instructions are [here](http://docs.python-requests.org/en/master/user/install/)
7. Set the `gcloud` defaults: See the instructions at https://cloud.google.com/container-engine/docs/before-you-begin under "*Set gcloud defaults*" section)
7.1. Make sure you also fetch the cluster credentials for `kubectl` command to use. I.e `$ gcloud container clusters get-credentials CLUSTER_NAME`
### **Launching Stress tests**
The stress tests are launched by the following script (path is relative to GRPC root directory) :
>Launches the 5 instances of stress test clients, 1 instance of stress test server and runs the test for 180 seconds. The test would be run on the default container cluster (that you have set in `gcloud`) in the project `sree-gce`.
> Note: we currently do not have the ability to launch multiple instances of the server. This can be added very easily in future
