> 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/azure.md).

# Azure

**Reference Architectures**

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 GigaVUE Cloud Suite BYOL Version
  * AWS Security Credentials
  * VPC and Subnet
  * Key Pair
  * Default Login Credentials
  * Security Group (Firewall Rules)
  * Sourcing Required Software Components
  * Other Points to Note
  * Recommended Instance Types for AWS Deployments
* Deployment
  * High Level Overview of Deployment Process
  * Deploying the Fabric Manger in AWS
  * 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 installatin 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/X2C0eB2wCPHkiIyYl4Rr" %}

{% file src="/files/BN8DyIyCCObGb3qh3MVa" %}


---

# 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 dynamically by asking a question.

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

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

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.