# Deploy with AWS EC2

This document provides instructions to start an AWS EC2 virtual machine and run an [Insight Point](/4yItIzMvkpAvMVFAamTf/integrations/connectivity/insight-point.md) as a Docker image.

### Installation

Follow the instructions to launch a new AWS EC2 instance, install prerequisites, and download and run the Insight Point. You can opt to use an existing EC2 instance, provided that the docker version is `19.09` or later.

* [Start an EC2 instance](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/LaunchingAndUsingInstances.html)
  * Open the [AWS EC2 Console](https://console.aws.amazon.com/ec2/)
  * Ensure that the region where you want to initialize the instance is selected
  * Click *Launch Instance*
  * Add a name for the instance ("Veza Insight Point")
  * Choose `Amazon Linux 2023` OS image
  * Configure instance size to meet the [Insight Point system requirements](/4yItIzMvkpAvMVFAamTf/integrations/connectivity/insight-point.md#system-requirements) (minimum: `2 CPU cores`, `4 GB RAM`)
* Choose an existing key pair or create a new one
  * Verify time synchronization: AWS EC2 instances use Amazon Time Sync Service by default, which should maintain accurate time automatically
* [Install Insight Point](/4yItIzMvkpAvMVFAamTf/integrations/connectivity/insight-point/insight-point-install-script.md)
* To discover standalone RDS or Trino databases, ensure that [Security Group Inbound Rules](/4yItIzMvkpAvMVFAamTf/integrations/connectivity/insight-point.md#ports-and-connectivity) allow communication to and from the Insight Point's outbound IP address.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.veza.com/4yItIzMvkpAvMVFAamTf/integrations/connectivity/insight-point/insight-point-ec2.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.