> For the complete documentation index, see [llms.txt](https://docs.vectra.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.vectra.ai/deployment/deprecated-retired/ndr-for-cloud-gigamon/aws.md).

# AWS

Legacy NDR for Cloud (Gigamon) guidance for AWS.

Please see [NDR for Cloud Gigamon Reference Architectures](/deployment/deprecated-retired/ndr-for-cloud-gigamon/reference-architectures.md) for overview's and advice for various deployment scenarios in supported public clouds.

**Contains**

* Introduction
* Architecture Introduction
  * Gigamon Components and Terminology
* Resources
* Information Gathering / Scoping (Pre-Deployment)
* Licensing
* Prerequisites
  * GigaVUE-FM Version Compatibility
  * Vectra Sensor Support
  * Supported Operating Systems for UCT-V Agents
  * Subscribe to Gigamon GigaVUE Cloud Suite for Azure
  * Resource Group / Virtual Network / Subnet
  * Key Pair
  * Default Login Credentials
  * Network Security Group (Firewall Rules)
  * Azure Security Credentials
  * Sourcing Required Software Components
  * Recommended Instance Types for Azure Deployments
* Deployment
  * High Level Overview of Deployment Process
  * Deploying the Fabric Manger in Azure
  * Creating a Monitoring Domain
  * Deploying the Fabric
  * Deploying UCT-V Agents
    * Special Notes for v6.10 and higher
    * Creating token and adding it to your client machines
    * Linux installation using .deb or .rpm package
    * Windows installation
  * Configure a Monitoring Session and Map
* Post Deployment Guidance
  * Installing a Custom Certificate
* Worldwide Support Contact Information

**Attachments**

{% file src="/files/Z4528R87U8Ec46tHCirD" %}

{% file src="/files/t2i6r8wmZDc7Lf7hQKtv" %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.vectra.ai/deployment/deprecated-retired/ndr-for-cloud-gigamon/aws.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.