diff --git a/README.md b/README.md
index 9553cd8..ccfb647 100644
--- a/README.md
+++ b/README.md
@@ -3,6 +3,7 @@
 ##  Auto-Magical Experiment Manager & Version Control for AI
 
 [![GitHub license](https://img.shields.io/badge/license-SSPL-green.svg)](https://img.shields.io/badge/license-SSPL-green.svg)
+[![Python versions](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)
 [![GitHub version](https://img.shields.io/github/release-pre/allegroai/trains-server.svg)](https://img.shields.io/github/release-pre/allegroai/trains-server.svg)
 [![PyPI status](https://img.shields.io/badge/status-beta-yellow.svg)](https://img.shields.io/badge/status-beta-yellow.svg)
 
@@ -33,7 +34,13 @@ The **trains-server's** code is freely available [here](https://github.com/alleg
 ![Alt Text](https://github.com/allegroai/trains/blob/master/docs/system_diagram.png?raw=true)
 
 
-## Installation
+## Installation - AWS
+
+Use our pre-installed Amazon Machine Image for easy deployment in AWS. 
+
+Details and instructions can be found  [here](docs/install_aws.md).
+
+## Installation - Docker
 
 This section contains the instructions to setup and launch a pre-built Docker image for the **trains-server**.
 This is the quickest way to get started with your own server. 
@@ -47,13 +54,13 @@ on a Linux virtual machine.
 
 ### Prerequisites
 
-You must be logged in as a user with sudo privileges.
+Make sure you are logged in as a user with sudo privileges.
 
 ### Setup
 
 #### Step 1: Install Docker CE
 
-You must install Docker to run the pre-packaged **trains-server**.
+In order to run the pre-packaged **trains-server**, install Docker.
 
 * See [Supported platforms](https://docs.docker.com/install//#support) in the Docker documentation for instructions
 
@@ -70,10 +77,10 @@ You must install Docker to run the pre-packaged **trains-server**.
 
 #### Step 2: Setup the Docker daemon
 
-To run the ElasticSearch Docker container, you must setup the Docker daemon by modifying the default
+To run the ElasticSearch Docker container, setup the Docker daemon by modifying the default
 values required by Elastic in your Docker configuration file (see [Notes for production use and defaults](https://www.elastic.co/guide/en/elasticsearch/reference/master/docker.html#_notes_for_production_use_and_defaults)). We provide instructions for the most common Docker configuration files.
 
-You must edit or create a Docker configuration file:
+Edit or create the Docker configuration file:
 
 * If your system contains a `/etc/sysconfig/docker` Docker configuration file, edit it.
 
@@ -111,7 +118,7 @@ You must edit or create a Docker configuration file:
 
 #### Step 3: Restart the Docker daemon
 
-You must restart the Docker daemon after modifying the configuration file:
+After modifying the configuration file, restart the Docker daemon:
 
 ```bash
 sudo service docker stop
@@ -138,8 +145,8 @@ Elastic requires that `vm.max_map_count` is at least 262144 (see [Production mod
 
 #### Step 5: Choose a Data Directory
 
-You must choose a directory on your system in which all data maintained by the **trains-server** is stored,
-Create a directory, and set its permissions. The data stored in this directory will include the database, uploaded files and logs.
+Choose a directory on your system in which all data maintained by the **trains-server** is stored.
+Create this directory, and set its owner and group to `uid` 1000. The data stored in this directory will include the database, uploaded files and logs.
 
 For example, if your data directory is `/opt/trains`, then use the following command:
 
diff --git a/docs/install_aws.md b/docs/install_aws.md
new file mode 100644
index 0000000..a813887
--- /dev/null
+++ b/docs/install_aws.md
@@ -0,0 +1,36 @@
+# **TRAINS-server**: AWS pre-installed images
+
+In order to easily deploy **trains-server** on AWS, we created the following Amazon Machine Images (AMIs).
+
+Service port numbers on these AMIs are: 
+ - Web: 8080
+ - API: 8008
+ - File Server: 8081
+
+Instructions on launching a custom AMI from the EC2 console can be found [here](https://aws.amazon.com/premiumsupport/knowledge-center/launch-instance-custom-ami/)
+and a detailed version [here](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/launching-instance.html).
+
+The minimum recommended instance type is **t3a.large**
+
+##Released versions
+
+The following sections provide a list containing AMI Image ID per region for each released **trains-server** version.
+
+### v0.9.0
+
+* **us-east-1** : ami-0991ad536ecbacdac
+* **eu-north-1** : ami-07cbcdff501b14afe
+* **ap-south-1** : ami-014cf398b00d4db83
+* **eu-west-3** : ami-0396ba51e9b733581
+* **eu-west-2** : ami-09134f4c7a20bad09
+* **eu-west-1** : ami-00427ed0a1bbfa7b0
+* **ap-northeast-2** : ami-041756675ca1be954
+* **ap-northeast-1** : ami-0c09ebad05c9128ff
+* **sa-east-1** : ami-017a8de4e8d1e8c8e
+* **ca-central-1** : ami-049ec444470f852be
+* **ap-southeast-1** : ami-0c919b8f821a6c635
+* **ap-southeast-2** : ami-04844a0594712d27b
+* **eu-central-1** : ami-0b4e756e0f7c0617d
+* **us-east-2** : ami-03b01914b07428488
+* **us-west-1** : ami-0cf4768e9d47ed076
+* **us-west-2** : ami-0b145f37da31eb9fb