Microsoft Fabric Updates Blog

Fabric Change the Game: Revolutionizing Fabric with REST API, Part 1

This post will explore Microsoft Fabric REST APIs for seamless automation. Following, let’s review through some of the options for API integration in Fabric, unravelling the threads of development, deployment, governance, and beyond in this comprehensive series, this is Part One. Some additional Material to review: Fabric API quickstart – Microsoft Fabric REST APIs | … Continue reading “Fabric Change the Game: Revolutionizing Fabric with REST API, Part 1”

Fabric Spark Autotune and Run Series Job Analysis

We are thrilled to announce the public preview of Run Series Analysis, in conjunction with our recent announcement of the Autotune feature at the Fab conference. These two features are designed to help you gain insights into Spark application executions across your recurring runs of your Notebook and Spark job definitions, facilitating performance tuning and … Continue reading “Fabric Spark Autotune and Run Series Job Analysis”

Environment is now generally available

Exciting news! The environment has officially become a generally available feature within Microsoft Fabric. What is the environment in Microsoft Fabric? The environment serves as a comprehensive container for both your hardware and software settings within Spark. Within this unified interface, you have the ability to select the desired Spark runtime, install libraries, and configure … Continue reading “Environment is now generally available”

Profiling Microsoft Fabric Spark Notebooks with Sparklens

Problem Statement: You are a data engineer developing Spark notebooks using Microsoft Fabric. You are having performance issues and you want to know if your spark code is running efficiently. You also want to know if increasing the resources would improve its performance. Discussion: In this blog, you will learn how to leverage Sparklens, an … Continue reading “Profiling Microsoft Fabric Spark Notebooks with Sparklens”

Introducing Code-First AutoML and Hyperparameter Tuning: Now in Public Preview for Fabric Data Science

At the recent Fabric Conference, we announced that both code-first automated machine learning (AutoML) and hyperparameter tuning are now in Public Preview, a key step in making machine learning more complete and widely accessible in the Fabric Data Science. Our system seamlessly integrates the open-source Fast Library for Automated Machine Learning & Tuning (FLAML), offering … Continue reading “Introducing Code-First AutoML and Hyperparameter Tuning: Now in Public Preview for Fabric Data Science”