Azure Files is excited to announce the Unlimited public preview of Metadata Caching for the premium SMB/REST file share tier. 

Unlimited Public Preview allows customers to automatically self-serve the onboarding process though feature registration (AFEC) in the support regions.

Feature Overview

Metadata Caching is an enhancement aimed at reducing metadata latency for file workloads running on Windows/Linux clients.  In addition to lowering metadata latency, workloads will observe a consistent latency experience which will allow metadata intensive workloads to be more predictable and deterministic.  Reduced metadata latency also translates to more data IOPS (reads/writes) and throughput.  Once the Metadata Caching feature is register within your subscription, there is no additional cost or operational management overhead when using this feature. 

The following Metadata APIs will benefit from Metadata Caching.

Create: Creating a new file; Up to 30% Faster
Open: Opening a file; Up to 55% Faster
Close: Closing a file; Up to 45% Faster
Delete: Deleting a file; Up to 25% Faster

Workloads that perform a high volume of metadata operations (creating/opening/closing/deleting) against a SMB/REST Premium File share will receive the biggest benefit compared to workloads that are primarily data IO (e.g. databases)

Example of metadata heavy workloads include:

WebApp Services: Frequently accessed files for CMSLMS services such as MoodleWordPress.
IndexingBatch Jobs: Large scale processing using Azure Kubernetes or Azure Batch.
Virtual Desktop Infrastructure: Azure Virtual DesktopCitrix users with home directories or VDI applications management needs.
Business Application: Custom line of business or legacy application with “Lift and shift” needs.
CICD – DevOps Pipeline: Building, testing, and deployment workloads such as Jenkins open-source automation

GitHub Solutions using Metadata Caching

Moodle deployment + Azure Premium Files with Metadata Caching

Moodle consists of server hosting (cloud platforms), a database (MySQL, PostgreSQL), file storage (Azure Premium Files), and a PHP-based web server.  It is used for course management (uploading materials, assignments, quizzes), user interaction (students accessing resources, submitting work, and discussions), and performance monitoring (tracking progress, reporting).

Metadata Cache Benefit: Provides a faster and more consistent user experience.

GitHub Actions + Azure Premium Files with Metadata Caching

GitHub Actions is an automation tool integrated with GitHub that allows developers to build, test, and deploy code directly from their repositories. It uses workflows, defined in YAML files, to automate tasks such as running tests, building software, or deploying applications. These workflows can be triggered by events like code pushes, pull requests, or scheduled times. 
Metadata Cache Benefit: Shorter build and deployment times when using Azure Premium Files with Metadata cache as the build artifact.

Expected Performance Improvement with Metadata Cache.

2-3x Improved Metadata Latency Consistency
Up to 3x increased scale for Metadata operations
Improved Metadata Latency beyond 30%
Increased IOPS and Bandwidth up to 60%

How to get started

To get started, register your subscription with the Metadata Cache feature using Azure portal or PowerShell.

Australia Central
Jio India West
India South
Mexico Central
Norway East
Poland Central
Spain Central
Sweden Central
Switzerland North
UAE North
US West 3

Note: As we extend region support for the Metadata Cache feature, Premium File Storage Accounts in those regions will be automatically onboarded for all subscriptions registered with the Metadata Caching feature.

Who should Participate?

Whether it is a new workload looking to leverage file shares or existing ones looking for improvements. Any workloads/usage patterns that contains metadata should be encouraged to onboard, specifically metadata heavy workloads that consist primarily of Create/Open/Close or Delete requests.

To determine if your workload contains metadata, can use Azure Monitor to split the transactions by API dimension as described in the following article

Thanks

Azure Files Team

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