Optimizing AI-Orchestrated Data Processing for Real-Time Efficiency

Overview of the Project

BeamNG required an advanced workflow orchestration system to manage tasks across Windows and Linux environments. Datavise initially implemented Apache Airflow before pivoting to Prefect, ensuring seamless task automation and cross-platform functionality.

Key Numbers & Infographics

34%

reduction in task execution time after switching to Prefect, optimizing the workflow for both Linux and Windows platforms

100%

success rate in orchestrating tasks across Windows and Linux machines using Prefect, overcoming the initial limitations of Airflow

57%

deployment time reduced using Docker-compose for seamless replication and scaling of orchestration systems

Introduction

Background of the Project

BeamNG needed a robust orchestration tool to automate workflows and manage tasks on both Linux and Windows machines.

Client Overview

BeamNG, a leader in simulation and software, needed a reliable, scalable solution for cross-platform task automation.

Beam NG Case Study, cross-platform task automation, Workflow orchestration

Objectives

Purpose of the Case Study

Highlight how Datavise implemented a comprehensive workflow orchestration system for BeamNG, transitioning from Apache Airflow to Prefect.

Key Objectives and Goals

Deliver a cross-platform orchestration system supporting Windows task automation.

Improve task execution efficiency and reduce manual interventions.

The Challenge

Initial Challenges Faced by the Company

BeamNG needed to automate tasks across both Linux and Windows, which presented issues with Apache Airflow’s compatibility on Windows environments.

Impact of the Challenges

Without a reliable workflow orchestration tool, BeamNG faced delayed testing and inefficiencies in managing their software test automation.

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Solutions

AI Solutions Implemented

Apache Airflow POC

Datavise initially built a POC using Apache Airflow with a master node running on Linux and a Windows-based Celery worker. However, limitations in Windows integration led to exploring alternatives.

Prefect POC

Datavise pivoted to Prefect orchestration, which handled Windows tasks natively, using PostgreSQL for backend support and a Docker-compose setup for seamless deployment.

Beam NG Implementation Scheme completed by Datavise, Apache Airflow solution, Docker for orchestration

Technologies and Tools Used

Prefect

Docker

PostgreSQL

Python

Results and Benefits

Outcomes Achieved

30% faster task execution: Switching to Prefect significantly improved task execution times, optimizing BeamNG's workflow.

Enhanced test automation: Test coverage increased by 40%, allowing for more efficient and automated processes.

Comprehensive documentation: Delivered thorough documentation, reducing team onboarding time by 30%.

Quantitative and Qualitative Results

68%

reduction in AI-powered document retrieval time

39%

increase in document processing efficiency

+450%

Positive feedback from users on the improved regulatory compliance tools

Lessons Learned

Key Takeaways

Choosing the right orchestration tool is essential for cross-platform automation. Switching to a Windows-native solution like Prefect improved performance and solved compatibility issues.

Best Practices

Early testing in Windows and Linux environments to ensure full compatibility before full implementation.

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Client Feedback

Client Testimonial

Datavise’s flexibility and quick pivot to Prefect orchestration helped us achieve seamless automation across Windows and Linux systems. The results were outstanding, significantly improving our task execution and testing processes.

BeamNG Engineering Team

Conclusion

Summary of the Case Study

Datavise’s implementation of a cross-platform workflow orchestration system helped BeamNG optimize their task automation. By transitioning from Apache Airflow to Prefect, Datavise ensured compatibility and efficiency for their software testing workflows.

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