Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Astronomer, the company behind Apache Airflow orchestration software, launched Astro Observe today, marking its expansion from a single-product company into the competitive data operations platform market. The move comes as enterprises struggle to operationalize their AI initiatives and maintain reliable data pipelines at scale.The new platform aims to help organizations monitor and troubleshoot their data workflows more effectively by combining orchestration and observability capabilities in a single solution. This consolidation could significantly reduce the complexity that many companies face when managing their data infrastructure.“Previously, our customers would have to come to us for orchestration data pipelines, and they’d have to go figure out a different data observability and Airflow observability vendor,” said Julian LaNeve, CTO of Astronomer, in an interview with VentureBeat. “We’re trying to make that a lot easier for our customers and give them everything in one platform.”AI-powered predictive analytics aims to prevent pipeline failuresA key differentiator of Astro Observe is its ability to predict potential pipeline failures before they impact business operations

This partnership allows organizations to effectively manage and scale their ML workflows by integrating Astronomer's workflow management capabilities with Anyscale's distributed computing power.

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Getting data from where it is created to where it can be used effectively for data analytics and AI isn’t always a straight line. It’s the job of data orchestration technology like the open-source Apache Airflow project to help enable a data pipeline that gets data where it needs to be.Today the Apache Airflow project is set to release its 2.10 update, marking the project’s first major update since the Airflow 2.9 release back in April. Airflow 2.10 introduces hybrid execution, allowing organizations to optimize resource allocation across diverse workloads, from simple SQL queries to compute-intensive machine learning (ML) tasks. Enhanced lineage capabilities provide better visibility into data flows, crucial for governance and compliance