Feature request : Integration with Harshicop Nomad

### The required feature described as a wish

As a User I would like to be able to setup and manage/deploy VM or container through [HArshicop Nomad](https://github.com/hashicorp/nomad).

For brief description

Nomad is a simple and flexible workload orchestrator to deploy and manage containers ([docker](https://developer.hashicorp.com/nomad/docs/deploy/task-driver/docker), [podman](https://developer.hashicorp.com/nomad/plugins/drivers/podman)), non-containerized applications ([executable](https://developer.hashicorp.com/nomad/docs/deploy/task-driver/exec), [Java](https://developer.hashicorp.com/nomad/docs/deploy/task-driver/java)), and virtual machines ([qemu](https://developer.hashicorp.com/nomad/docs/deploy/task-driver/qemu)) across on-prem and clouds at scale.

Nomad is supported on Linux, Windows, and macOS. A commercial version of Nomad, [Nomad Enterprise](https://developer.hashicorp.com/nomad/docs/enterprise), is also available.

- **Deploy Containers and Legacy Applications**: Nomad’s flexibility as an orchestrator enables an organization to run containers, legacy, and batch applications together on the same infrastructure. Nomad brings core orchestration benefits to legacy applications without needing to containerize via pluggable task drivers.

- **Simple & Reliable**: Nomad runs as a single binary and is entirely self contained - combining resource management and scheduling into a single system. Nomad does not require any external services for storage or coordination. Nomad automatically handles application, node, and driver failures. Nomad is distributed and resilient, using leader election and state replication to provide high availability in the event of failures.

- **Device Plugins & GPU Support**: Nomad offers built-in support for GPU workloads such as machine learning (ML) and artificial intelligence (AI). Nomad uses device plugins to automatically detect and utilize resources from hardware devices such as GPU, FPGAs, and TPUs.

- **Federation for Multi-Region, Multi-Cloud**: Nomad was designed to support infrastructure at a global scale. Nomad supports federation out-of-the-box and can deploy applications across multiple regions and clouds.

- Proven Scalability: Nomad is optimistically concurrent, which increases throughput and reduces latency for workloads. Nomad has been proven to scale to clusters of 10K+ nodes in real-world production environments.

此 issue 一開始沒有指出任何 CloudStack 檔案、測試或進入點。首先確認現有的部署邊界與整合邊界，然後定義透過 HashiCorp Nomad 管理 VM 與容器應如何運作；完成的標準是實作完整且經過測試的 Nomad 整合。

由索引模型根據 Issue 內容生成。