2 files changed, 61 insertions, 5 deletions
diff --git a/tools/README.md b/tools/README.md
index df4c6ef7d2..cb6c22dd83 100644
--- a/tools/README.md
+++ b/tools/README.md
@@ -1,13 +1,16 @@
-buildgen: template renderer for our build system.
+buildgen: Template renderer for our build system.
 
-distrib: scripts to distribute language-specific packages.
+distrib: Scripts to distribute language-specific packages.
 
 dockerfile: Docker files to test gRPC.
 
 doxygen: gRPC C/C++ documentation generation via Doxygen.
 
-gce: scripts to help setup testing infrastructure on GCE.
+gce: Scripts to help setup testing infrastructure on GCE.
 
-jenkins: support for running tests on Jenkins.
+gcp: Helper scripts for interacting with various services on GCP (like Google
+container engine, BigQuery etc)
 
-run_tests: scripts to run gRPC tests in parallel.
+jenkins: Support for running tests on Jenkins.
+
+run_tests: Scripts to run gRPC tests in parallel.
diff --git a/tools/run_tests/stress_test/README.md b/tools/run_tests/stress_test/README.md
new file mode 100644
index 0000000000..80e4cd58f0
--- /dev/null
+++ b/tools/run_tests/stress_test/README.md
@@ -0,0 +1,53 @@
+Running Stress tests on Google Container Engine
+=======================================
+
+### **Glossary**:
+* GCP: Google Cloud Platform
+* GCE: Google Compute Engine
+* GKE: Google Container Engine
+* GCP console: https://console.cloud.google.com
+
+### **Setup Instructions**
+#### *On GCP:*
+1. Login to GCP with your Google account (for example, your @gmail account) at https://cloud.google.com. If do not have a Google account, you will have to create an account first.
+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).i.e Click on the project dropdown box on the top right (to the right of the search box) and click '*Create a project*' option.
+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). Alternatively, you can do the following:
+    - Click on the '*Products & Services*' icon on the top left (i.e the icon with three small horizontal bars) and select '*API Manager*'
+    - Select the '*Container Engine API*' under '*Google Cloud APIs*' on the main page. Note that you might have to click on '*More*' under '*Google Cloud APIs*' to see the '*Container Engine API*' link
+    - Click on the '*Enable*' button. If the API is already enabled, the button's label would be '*Disable*' instead (do NOT click the button if its label is '*Disable*')
+5. Create a Cluster from the GCP console.
+    - Go to the Container Engine section from GCP console i.e: Click on the '*Products & Services*' icon on the top left (i.e the icon with three small horizontal bars) and click on '*Container Engine*'
+    - Click '*Create Container Cluster*' and follow the instructions.
+    - 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)
+    - 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. For the machine type, something like '2 vCPUs 7.5 GB' (available in the drop down box) should be good enough.
+    - **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.
+    - 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 [here](https://github.com/grpc/grpc/blob/master/INSTALL.md)
+2. Install Docker. Instructions [here](https://docs.docker.com/engine/installation/)
+3. Install Google Cloud SDK. Instructions [here](https://cloud.google.com/sdk/). This installs the `gcloud` tool
+4. Install `kubectl`, Kubernetes command line tool using `gcloud`. i.e
+    - `$ gcloud components update kubectl`
+5. Install Google python client apis:
+    - `‘$ sudo pip install --upgrade google-api-python-client’`
+    -  **Note**: Do `$ sudo apt-get install python-pip` (or `$ easy_install -U pip`) if you do not have pip
+6. Install the `requests` Python package if you don’t have it already by doing `sudo pip install requests`. More details regarding `requests` package are [here](http://docs.python-requests.org/en/master/user/install/)
+7. Set the `gcloud` defaults: See the instructions [here](https://cloud.google.com/container-engine/docs/before-you-begin) under "*Set gcloud defaults*" section)
+    - 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) :
+`tools/run_tests/stress_test/run_stress_tests_on_gke.py`
+
+The script has several parameters and you can find out more details by using the `--help` flag.
+  - `<grpc_root_dir>$ tools/run_tests/stress_test/run_stress_tests_on_gke.py --help`
+
+> **Example**
+> `$ tools/run_tests/stress_test/run_stress_tests_on_gke.py --project_id=sree-gce --test_duration_secs=180 --num_clients=5`
+
+> 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