> For the complete documentation index, see [llms.txt](https://docs.archera.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.archera.ai/partners/archera-overview/supported-services.md).

# Supported Services

### AWS

1. EC2
2. RDS
3. ElastiCache
4. OpenSearch
5. Redshift
6. Fargate
7. SageMaker
8. ECS
9. EKS
10. Lambda

### Azure

1. Azure Functions
2. Container Instances
3. Container Apps
4. Azure Spring Apps
5. Virtual Machines
6. Dedicated Host
7. Machine Learning
8. Azure Databricks
9. App Service
10. AKS (Azure Kubernetes Service)
11. SQL DB
12. DB for MySQL
13. DB for PostgreSQL
14. Cosmos DB
15. Cache for Redis
16. Azure VMware Solution
17. Azure OpenAI
18. Microsoft Fabric
19. Defender for Cloud
20. Microsoft Sentinel
21. Blob Storage
22. Disk Storage
23. Azure Files
24. Azure NetApp Files
25. Azure Backup

### GCP

1. Google Compute Engine


---

# 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.archera.ai/partners/archera-overview/supported-services.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.