Export and Import Al Model across CP4AIOps instances

Current Situation:

• CP4AIOps uses various AI models for tasks like anomaly detection, event grouping, and incident prediction.
• These models are typically trained and optimized within a single CP4AIOps instance.
• There's limited information about direct model portability between instances in the current documentation.

Benefits of implementing this feature:

Consistency Across Environments:

• Ability to use the same trained models across development, testing, and production instances.
• Ensures consistent AI behavior and performance across different environments.

Time and Resource Savings:

• Reduces the need to retrain models for each CP4AIOps instance.
• Saves computational resources and time required for model training.

Knowledge Transfer:

• Facilitates sharing of optimized models between different teams or organizations.
• Enables leveraging of models trained on larger or more diverse datasets.

Backup and Recovery:

• Allows for easier backup of trained models.
• Simplifies disaster recovery scenarios for AI components.

Version Control and Rollback:

• Enables versioning of AI models for better tracking and management.
• Facilitates easy rollback to previous model versions if needed.

Simplified Updates and Upgrades:

• Eases the process of updating CP4AIOps instances while preserving trained models.
• Supports smoother migration paths between different versions of CP4AIOps.

Benchmarking and Comparison:

• Allows for direct comparison of model performance across different environments or configurations.