# DevOps Q&A Dataset Summary

**Generated on:** 2026-01-17
**Version:** 2.1 Final

## 📊 Overview
Based on user requirements, we have collected, validated, and deduplicated a high-quality dataset of DevOps Questions & Answers.

| Metric | Value |
|:--- |:--- |
| **Total Unique Items** | **7,219** |
| **Primary Source** | GitHub Repositories (Advanced Search) |
| **Secondary Source** | Official Documentation (Docker, K8s, etc.) |
| **Average Quality Score** | ~0.81 |
| **Deduplication** | Exact (MD5) + Semantic (BGE-Small) |

## 📁 File Manifest
All files are located in `/opt/Data set/output/`:

*   `devops_dataset.jsonl` - Main dataset (JSON Lines).
*   `devops_dataset.parquet` - Optimized Parquet format for pandas/polars.
*   `dataset_metadata.json` - Technical metadata (last run stats).

## 🧩 Data Composition
The dataset covers a wide range of DevOps topics, including but not limited to:
*   **Kubernetes:** Troubleshooting, Configs, Best Practices.
*   **Docker:** Composition, Optimization, Security.
*   **IaC:** Terraform, Ansible, Pulumi.
*   **CI/CD:** GitHub Actions, GitLab CI, Jenkins.
*   **Monitoring:** Prometheus, Grafana, ELK.

## 🚀 Usage Example (Python)
```python
import pandas as pd

# Load the dataset
df = pd.read_parquet('/opt/Data set/output/devops_dataset.parquet')

# Inspect
print(df.head())
print(df['source'].value_counts())

# Filter high quality
high_quality = df[df['quality_score'] > 0.85]
```

## 🛠 Collection Details
*   **Tools:** `devops_collector.py` (Custom Python Collector)
*   **Validation:** Strict quality rules (length, spam, content safety).
*   **Dedup:** Semantic embedding filtering enabled for new data.