Fabric Espresso – Episodes about Performance Optimization & Compute Management in Microsoft Fabric
For the past 1.5 years, the Microsoft Fabric Product Group Product Managers have been publishing a YouTube series featuring deep dives into Microsoft Fabric’s features. These episodes cover both technical functionalities and real-world scenarios, providing insights into the product roadmap and the people driving innovation. With over 80+ episodes, the series serves as a valuable resource for anyone looking to understand and optimize their use of Microsoft Fabric.
All episodes are available at https://aka.ms/fabric-espresso making it easy to explore the entire catalog. However, to enhance the learning experience, we are launching a short series of blog posts that will categorize the episodes into thematic groups, providing explanations and key takeaways for each.
Fabric Espresso & Performance Optimization & Compute Management
This week, we focus on Performance Optimization & Compute Management in Microsoft Fabric. Below is a curated list of episodes that explore various techniques for optimizing compute resources, tuning queries, and improving efficiency within Microsoft Fabric.
Key Episodes on Performance Optimization & Compute Management:
- High Concurrency Mode for Notebooks in Pipelines for Fabric Spark
- Learn how shared, high-performance sessions cut down job runtimes dramatically.
- ML based Autotune for Apache Spark Jobs in MS Fabric performance optimization for recurrent jobs
- Discover how predictive autotuning refines Spark configurations for optimized performance.
- Native execution engine for Apache Spark in Fabric
- Explore the vectorized execution engine designed to boost query speed and efficiency.
- Spark Compute in Fabric Data Engineering and Data Science – Starter Pools vs Custom Pools Unveiled!
- Compare resource provisioning options and understand the trade-offs between quick-start and tailored compute pools.
- Fabric Apache Spark Autotune and Run Series Job Analysis in Monitoring Hub
- Gain insights into automated tuning techniques and job performance diagnostics.
- Fabric Apache Spark Jobs monitoring capabilities – Resource Usage
- Understand how detailed monitoring helps identify performance bottlenecks and resource inefficiencies.
- Fabric Spark Compute Capabilities – Azure VM’s and their impact on performance
- See how leveraging Azure VM configurations can drive enhanced Spark performance.
- Performance best practices
- Review essential strategies for optimizing query performance in your workspace.
- Microsoft Fabric Capacity Smoothing and Data Warehouse Throttling
- Learn how capacity smoothing and throttling techniques ensure consistent performance under load.
- Caching in data warehousing
- Discover how in-memory and SSD caching can significantly reduce query latency.
- Performance at Scale with Microsoft Fabric: Concurrency!
- Explore how Fabric handles concurrency to maintain high performance even at scale.
- Performance at Scale with Microsoft Fabric: Query Optimizations!
- Dive into techniques for optimizing query execution to boost efficiency.
- Performance at Scale with Microsoft Fabric: Query Processing!
- Understand the underlying mechanics of query processing and performance tuning.
