diff --git a/HOSTING.md b/HOSTING.md
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+## Hosting vectara-answer
+
+This guide provides specific instructions to help you host your `vectara-answer` application on one of the popular hosting providers.
+We keep adding new hosting providers regularly - please let us know if you need instructions for a hosting provider that is not yet included.
+
+### Overview
+
+To run a hosted version of `vectara-answer` you would need to have two files: `.env` and `queries.json`.
+
+To prepare the `.env` file, which combines the information from `config.yaml` and `secrets.toml`, run the following command:
+
+`python3 prepare_config.py /path/to/<YOUR-CONFIG.yaml> <profile>`
+
+At the end of this process you should have two files ready to go:
+1. `.env` generated by the above python3 command
+2. `queries.json` that specifies the queries for your application.
+
+### Deploy vectara-answer on Render
+
+To deploy on Render, please follow these steps:
+
+1. Sign Up/Log In: If you don't have a Render account, you'll need to create one. If you already have one, just log in.
+2. Create New Service: Once you're logged in, click on the "New" button usually found on the dashboard and select "Web Service".
+3. Choose "Deploy an existing image from a registry" and click "Next"
+4. Specify Docker Image: In the "Image URL" fill in "vectara/vectara-answer" and click "Next"
+5. Choose a name for your deployment (e.g. "vectara-answer"), and if you need to pick a region or leave the default. Then pick you instance type.
+6. Click "Create Web Service"
+7. Click "Environment", then "Add Secret File": name the file `.env`, and copy the contents of your local `.env` file
+8. Now click "Add Secret File" again and this time name the file `queries.json`, and copy the contents of your local `queries.json` file
+9. Click "Settings" and go to "Docker Command" and click "Edit", the put in the following command: 
+
+`/bin/bash -c cp /etc/secrets/queries.json ./build/ && cp /etc/secrets/.env ./ && node server/index.js`
+
+Then click "Save Changes", and your application should now be deployed.
+
+### Deploy vectara-answer on Heroku
+
+To be added soon
+
+### Deploy vectara-answer on AWS with CloudFormation
+
+To be added soon
+
+### Deploy vectara-answer on GCP
+
+To be added soon
+
+
+
diff --git a/README.md b/README.md
index 022587f4..e7fb1ba4 100644
--- a/README.md
+++ b/README.md
@@ -333,15 +333,8 @@ The container generated is called `vanswer`, and after it is started, you can:
 
 ### Cloud deployment
 
-You can deploy `vectara-answer` on cloud platforms such as AWS, Azure, or GCP.
-
-1. Create your configuration file for the project under the `config/` directory.
-2. Run `python3 prepare_config.py <config_file_name>` to generate the `.env` file
-3. Push the docker to the cloud specific docker container registry:
-   - [AWS instructions](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/docker-basics.html).
-   - [Azure instructions](https://learn.microsoft.com/en-us/azure/container-apps/get-started-existing-container-image-portal?pivots=container-apps-private-registry).
-   - [GCP instructions](https://cloud.google.com/run/docs/quickstarts/build-and-deploy).
-4. Launch the container on a VM instance based on the Docker image now hosted in your cloud environment. Make sure to load the `.env` and the `config/` directory as volumes that the Docker recognizes as shown in `run.sh`.
+You can deploy `vectara-answer` on cloud platforms such as AWS, Azure, or GCP as well as on specialized cloud services like Render or Heroku.
+See [detailed instructions](HOSTING.MD)
 
 ## FAQs