ExtremeXP Framework Components

The ExtremeXP framework is built as a modular and interoperable ecosystem designed to support the full lifecycle of continuous adaptive experimentation, integrating human-in-the-loop processes and advanced data-driven decision making.

Framework Architecture Overview

Core Components

ExtremeXP Portal

The ExtremeXP Portal serves as the primary entry point for all ExtremeXP users. Registered users can design and specify workflows and experiments using both :

  • A Graphical Editor (Experiments tab)

  • A Textual Editor (Tasks tab, also referred to as the DSL Editor)

The portal centralizes experiment design and provides seamless access to both visual and textual specification tools.

Experiment DSL Language Server

The Experiment DSL Language Server provides syntax and grammar validation for the ExtremeXP DSL directly within the user’s preferred development environment.

Architecture

  • Server side

    • Implemented using XText

    • Runs in Java

  • Client side

    • Editor integrations for Visual Studio Code and IntelliJ IDEA

This component ensures reliable, consistent, and error-free experiment definitions.

ExtremeXP Experimentation Engine

The ExtremeXP Experimentation Engine is the core component responsible for implementing continuous adaptive experiment planning. It enables researchers and data scientists to :

  • Define experiments using a simple Domain-Specific Language (DSL)

  • Execute workflows across multiple backends :

    • ProActive Scheduler

    • Kubeflow Pipelines

    • Local execution

  • Manage datasets via :

    • Local storage

    • Decentralized Data Management (DDM)

  • Track experiment metadata and results through the Data Abstraction Layer (DAL)

  • Support human-in-the-loop interaction workflows

DDM – Decentralized Data Management

The Decentralized Data Management (DDM) component provides a distributed data management system tailored for ExtremeXP, ensuring robust data transport, validation, and insight generation.

Key technologies

  • Zenoh nodes for decentralized data transport and querying

  • React frontend

  • Flask backend

  • Celery task management

  • PostgreSQL storage

  • Ollama integration for dataset-driven insights

  • Great Expectations for dataset validation

  • YData Profiling for automated data profiling and reporting

ProActive Scheduler

The operation of the ExtremeXP framework requires access to an instance of the ProActive Scheduler, which enables distributed execution of experimental workflows.

Licensing

  • A separate license from Activeeon is required

  • An official request must be sent explaining:

    • Why the license is needed

    • Who will use it

    • For what purpose

Technical requirements

  • Minimum hardware: 4 CPU cores, 8 GB RAM

  • Minimum RAM usage: 4 GB

  • Public IP required

  • TCP ports: 8880 and 33647

ExperimentLens

ExperimentLens is a lightweight yet powerful visual dashboard for interactive exploration, monitoring, and explainability of complex AI pipelines.

Developed within the ExtremeXP project, ExperimentLens enables researchers, data scientists, and engineers to :

  • Monitor pipeline lifecycles

  • Explore results across multiple experimental runs

  • Inspect configurations and outputs

  • Gain insights into pipeline behavior and sensitivity

The tool is strongly centered on human-in-the-loop experimentation.

Intents2Workflows

Intents2Workflows translates high-level user-defined analytical intents into actionable and executable workflows.

Process

  1. The user defines an analytical task at a high level

  2. Key features are extracted from the description

  3. The intent is mapped to a rich knowledge base

  4. Ontology-based dependency tracing generates workflows

  5. Workflows are initially encoded in RDF

  6. RDF workflows can be translated into other representations, such as the DSL required by the execution engine

This component provides high flexibility and automation in workflow generation.

By combining experiment design, execution, data management, monitoring, and explainability, ExtremeXP delivers a comprehensive and modular framework for next-generation continuous adaptive experimentation.

The ExtremeXP project is co-funded by the European Union Horizon Program HORIZON CL4-2022-DATA-01-01, under Grant Agreement No. 101093164

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