[WIP] Create Kubeflow Ecosystem overview documentation

[Copilot]

Thanks for asking me to work on this. I will get started on it and keep this PR's description up to date as I form a plan and make progress.

Original prompt

Objective

Create a comprehensive, versatile, and flexible Kubeflow Ecosystem overview documentation that includes:

• Architecture diagrams (ASCII and image references)
• AI Lifecycle mapping
• Kubeflow projects breakdown
• Interface documentation

Requirements

Create a new Markdown file named KUBEFLOW_ECOSYSTEM_OVERVIEW.md with the following complete content:

# Kubeflow Ecosystem: A Versatile & Flexible AI Platform

The **Kubeflow Ecosystem** provides a modular, scalable, and extensible approach to building AI platforms on Kubernetes.

---

## 1. Kubeflow Ecosystem Diagram

**A. ASCII Overview**

```
+-------------------------------------------------------------------------------+
|                             Kubernetes Cluster                                |
|   +----------------------  Kubeflow Central Dashboard   -------------------+   |
|   |        +-----------------------------------------+                   |   |
|   |        |            Kubeflow Ecosystem           |                   |   |
|   |        | +------------+   +---------+   +------+ |                   |   |
|   |        | | Notebooks  |   | Pipelines|   |KServe| | ...               |   |
|   |        | +------------+   +---------+   +------+ |                   |   |
|   |        +-----------------------------------------+                   |   |
|   +--------------------------------------------------------------------+   |
+----------------------------------------------------------------------------+
```
**B. Image Reference**

![Kubeflow Ecosystem Diagram](https://www.kubeflow.org/docs/images/architecture.svg)

---

## 2. AI Lifecycle Stages

**A. ASCII Diagram**

```
[Raw Data]
     |
     v
[Data Preparation]
     |
     v
[Model Development]
     |
     v
[Model Training]
     |
     v
[Model Optimization]
     |
     v
[Model Registry]
     |
     v
[Model Serving & Monitoring]
```

**B. Phases**

```
|-- Development ---------------------||---- Production ---------|
       (preparation, dev, training)      (registry, serving)
```

**C. Image Reference**

![AI Lifecycle Stages](https://raw.githubusercontent.com/kubeflow/website/master/content/en/docs/images/ai-lifecycle-stages.png)

---

## 3. Kubeflow Projects Across the AI Lifecycle

**A. Mapping Table**

| Lifecycle Stage     | Kubeflow Project(s)                             |
|---------------------|-------------------------------------------------|
| Data Preparation    | Spark Operator, Feast                           |
| Model Development   | Notebooks                                       |
| Model Training      | Trainer                                         |
| Model Optimization  | Katib, Model Registry                           |
| Model Registry      | Model Registry                                  |
| Model Serving       | KServe, Feast                                   |
| Orchestration       | Pipelines                                       |

**B. ASCII Mapping**

```
          +------------------+
          |   Data Prep      |---[Spark, Feast]
          +------------------+
                    |
          +------------------+
          |  Development     |---[Notebooks]
          +------------------+
                    |
          +------------------+
          |    Training      |---[Trainer]
          +------------------+
                    |
          +------------------+
          |   Optimization   |---[Katib, Registry]
          +------------------+
                    |
          +------------------+
          |    Serving       |---[KServe, Feast]
          +------------------+
                    |
          +------------------+
          |  Orchestration   |---[Pipelines]
          +------------------+
```

**C. Image Reference**

![Kubeflow Projects in AI Lifecycle](https://raw.githubusercontent.com/kubeflow/website/master/content/en/docs/images/projects-in-lifecycle.png)

---

## 4. Kubeflow Dashboard Example

**A. Image Placeholder**

![Kubeflow Central Dashboard](https://www.kubeflow.org/docs/images/central-dashboard.png)
*Replace with actual screenshot from your installation as needed.*

---

## 5. Detailed AI Lifecycle Stages

### Data Preparation
- **Purpose:** Ingest raw data, perform feature engineering to extract ML features for the offline feature store, and prepare training data for model development.
- **Tools:** Spark, Dask, Flink, Ray, Kubeflow Spark Operator, Feast
- **Kubeflow Integration:** Spark Operator, Feast

### Model Development
- **Purpose:** Choose an ML framework, develop model architecture, and explore existing pre-trained models for fine-tuning (e.g., BERT, Llama).
- **Tools:** TensorFlow, PyTorch, JAX, HuggingFace
- **Kubeflow Integration:** Notebooks for interactive development and experimentation

### Model Training
- **Purpose:** Train or fine-tune models on large-scale compute environments. Use distributed training if single GPU can't handle model size.
- **Output:** Trained model artif...

</details>



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