Automating Large‑Scale Data Management with Azure Storage Actions

Microsoft

Feb 25, 2026

Azure Storage customers increasingly operate at massive scale, with millions or even billions of items distributed across multiple storage accounts. As the scale of the data increases, managing the data introduces a different set of challenges.

In a recent episode of Azure Storage Talk, I sat down with Shashank, a Product Manager on the Azure Storage Actions team, to discuss how Azure Storage Actions helps customers automate common data management tasks without writing custom code or managing infrastructure.

This post summarizes the key concepts, scenarios, and learnings from that conversation. Listen to the full conversation below.

The Problem: Data Management at Scale Is Hard

As storage estates grow, customers often need to:

Apply retention or immutability policies for compliance
Protect sensitive or important data from modification
Optimize storage costs by tiering infrequently accessed data
Add or clean up metadata (blob index tags) for discovery and downstream processing

Today, many customers handle these needs by writing custom scripts or maintaining internal tooling. This approach requires significant engineering effort, ongoing maintenance, careful credential handling, and extensive testing, especially when operating across millions of item across multiple storage accounts.

These challenges become more pronounced as data estates sprawl across regions and subscriptions.

What Is Azure Storage Actions?

Azure Storage Actions is a fully managed, serverless automation platform designed to perform routine data management operations at scale for:

Azure Blob Storage
Azure Data Lake Storage

It allows customers to define condition-based logic and apply native storage operations such as tagging, tiering, deletion, or immutability, across large datasets without deploying or managing servers. Azure Storage Actions is built around two main concepts:

Storage Tasks

A storage task is an Azure Resource Manager (ARM) resource that defines:

The conditions used to evaluate blobs (for example, file name, size, timestamps, or index tags)
The actions to take when conditions are met (such as changing tiers, adding immutability, or modifying tags)

The task definition is created once and centrally managed.

Task Assignments

A task assignment applies a storage task to one or more storage accounts. This allows the same logic to be reused without redefining it for each account.

Each assignment can:

Run once (for cleanup or one-off processing)
Run on a recurring schedule
Be scoped using container filters or excluded prefixes

Walkthrough Scenario: Compliance and Cost Optimization

During the episode, Shashank demonstrated a real-world scenario involving a storage account used by a legal team.

The Goal

Identify PDF files tagged as important
Apply a time-based immutability policy to prevent tampering
Move those files from the Hot tier to the Archive tier to reduce storage costs
Add a new tag indicating the data is protected
Move all other blobs to the Cool tier for cost efficiency

The Traditional Approach

Without Storage Actions, this would typically require:

Writing scripts to iterate through blobs
Handling credentials and permissions
Testing logic on sample data
Scaling execution safely across large datasets
Maintaining and rerunning the scripts over time

Using Azure Storage Actions

With Storage Actions, the administrator:

Defines conditions based on file extension and index tags
Chains multiple actions (immutability, tiering, tagging)
Uses a built-in preview capability to validate which blobs match the conditions
Executes the task without provisioning infrastructure

The entire workflow is authored declaratively in the Azure portal and executed by the platform.

Visibility, Monitoring, and Auditability

Azure Storage Actions provides built-in observability:

Preview conditions allow customers to validate logic against a subset of blobs before execution
Azure Monitor metrics track task runs, targeted objects, and successful operations
Execution reports are generated as CSV files for each run, detailing:
- Blobs processed
- Actions performed
- Execution status for audit purposes

This makes Storage Actions suitable for scenarios where traceability and review are important.

Common Customer Use Cases

Shashank shared several examples of how customers are using Azure Storage Actions today:

Financial services: Applying immutability and retention policies to call recordings for compliance
Airlines: Cost optimization by tiering or cleaning up blobs based on creation time or size
Manufacturing: One-time processing to reset or remove blob index tags on IoT-generated data

These scenarios range from recurring automation to one-off operational tasks.