We are excited to announce a new feature which has been a long ask from Synapse Spark customers, Optimistic Job Admission for Spark in Microsoft Fabric.This feature brings in more flexibility to optimize for concurrency usage (in some cases ~12X increase) and prevents job starvation. This job admission approach aims to reduce the frequency of … Continue reading “Introducing Optimistic Job Admission for Fabric Spark”
Users orchestrate their data engineering or data science processes using notebooks and in most of the enterprise scenarios pipelines and job schedulers are used as a primary option to schedule and trigger these Spark jobs. We are thrilled to announce a new feature Job Queueing for Notebook Jobs in Microsoft Fabric. This feature aims to … Continue reading “Introducing Job Queueing for Notebook in Microsoft Fabric”
In the era of AI, data has become the cornerstone of analytics platforms. With the ever-increasing volume of data being collected across various applications, data lakes, databases, and data warehouses within an enterprise data estate, the need for secure access to enterprise data sources has become critical. This is particularly important given the growth of … Continue reading “Introducing Managed Private Endpoints for Microsoft Fabric in Public Preview”
We are excited to announce a new high concurrency mode in Fabric for Data Engineering and Data Science. This allows users to share Spark compute across multiple notebooks within a workspace which means that you can run multiple Spark notebooks simultaneously on the same Spark session without compromising performance or security when paying for a … Continue reading “Introducing High Concurrency Mode in Notebooks for Data Engineering and Data Science workloads in Microsoft Fabric”
