Instant access incremental snapshots: Restore without waiting

Today, we’re excited to introduce instant access support for incremental snapshots of Premium SSD v2 (Pv2) and Ultra Disk, delivering an industry-leading snapshot experience where creation, disk restore, and production-ready performance all happen instantly.

Instant access snapshots of Pv2 and Ultra Disk are usable immediately upon creation, allowing you to restore new disks without waiting for snapshots to be ready. Newly restored disks also deliver near-full performance from the start, allowing applications to resume operations immediately.

For mission-critical workloads, speed matters—especially when every minute of downtime or degraded performance has real business impact. Whether you’re rolling out critical application updates, recovering unexpected issues, scaling stateful workloads, or refreshing environments for development and testing, snapshots play a central role in keeping your business moving forward.

Standard incremental snapshots have long provided a cost-effective method to protect data and create point-in-time disk copies for these workflows. However, this came with tradeoffs: after snapshot creation, data must be fully copied before snapshots can be used to restore disks, and disks must fully hydrate to reach full performance.

With instant access snapshots, that wait is gone.

As soon as snapshots are created, you can restore new disks from them with near-full performance from the start. This means faster recovery, faster scaling, and faster iteration—redefining what customers should expect from snapshot operations in cloud.

See instant access documentation

Instant access snapshot in action

When creating incremental snapshots of Pv2 and Ultra Disk, you can opt in to enable instant access using the existing snapshot API. Once enabled, snapshots enter the Instant Access state at creation and can be used to create new disks right away with fast restore performance.

Instant access snapshots come with the following benefits:

Instant availability: Instant access snapshots are available to restore new disks immediately upon creation, eliminating the wait time for background data copy to snapshot in Standard storage.

Fast restore: Disks restored from instant access snapshots hydrate rapidly and deliver near-full performance with single-digit millisecond read latencies and sub-millisecond write latencies from the start.

Incremental storage: Instant access snapshots store only the incremental changes made to the source disk after snapshot creation, avoiding the need for a full base snapshot to keep your storage costs low.

Cross-zonal restore: Like incremental snapshots in Standard storage, instant access snapshots support restoring disks into a different availability zone within the same region, providing flexibility for deployment and recovery.

These benefits make instant access snapshots best suited for time-sensitive scenarios where immediate availability and performance are essential.

Common use cases include:

Fast rollback: Before deploying major software upgrades, you can use instant access snapshots to create an immediate recovery point. If issues occur such as accidental deletes, you can restore disks from snapshots to quickly rollback changes, maintain business continuity, and minimize downtime.

Uninterrupted maintenance: Instant access snapshots let you begin maintenance immediately after snapshot creation—without waiting for them to become ready. This reduces application downtime and keeps large systems within tight maintenance windows.

Rapid scale-out: You can scale stateful applications by leveraging instant access snapshots to create multiple disk copies of your primary instance in seconds, such as adding secondary SQL Server replicas. You can also create copies across availability zones within the same region quickly to achieve high availability and resiliency.

Refresh secondary environments: Instant access snapshots let you copy production disks and spin up secondary environments for development and testing in seconds. This ensures your test environment is always in sync with production and delivers high performance right away.

Here’s what instant access snapshots looks like in practice

For Azure Database Services such as PostgreSQL, instant access snapshots are a core building block for backup, recovery, and scaling. Consider a SaaS provider running PostgreSQL for a customer-facing application. During peak business hours, read traffic spikes requiring rapid scale-out of read capacity. With instant access snapshots, the Azure Database Service can create snapshots from the existing instance and quickly create new disks and instances with zero wait time. This allows new read replicas to be brought online much faster than traditional snapshot workflows, immediately serving read traffic with low latency and allowing the application to absorb traffic surges on demand.

The customer perspective below demonstrates how instant access snapshots transform their day-to-day operations:

For Providence, instant access snapshots have transformed how we refresh our Epic training and support environments. Instead of waiting on long background copy processes for snapshot creation and disk hydration, our teams can create fully usable disks immediately for the day’s training and support workflows. The ability to refresh downstream environments quickly has been a massive boost to our operational efficiency and has significantly improved the experience for our end users.
— Chris Calas, Senior Principal Service Engineer, Providence

At Microsoft Ignite 2025, instant access support for incremental snapshots is highlighted as a key innovation by Azure Storage product leaders, underscoring Azure’s focus on mission-critical workloads.

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How instant access snapshots improve disk restore performance

Standard incremental snapshots for Pv2 and Ultra Disk are designed to optimize cost efficiency and durability by storing point-in-time data in Standard Zone-Redundant Storage (ZRS). This approach provides strong resilience and is well suited for long-term backups and protection against zonal disasters. Once snapshot data has been fully copied into Standard ZRS, it becomes available for restoring new disks. A disk restored from a Standard storage snapshot can be used immediately, but until the background data copy to the disk completes, reads are served from Standard storage, resulting in slower performance and a longer copy time.

Incremental snapshots with instant access enabled take a different approach to optimize instant availability and restore performance. With instant access snapshots, point-in-time data captured remains in the same high-performance storage location as the source disks for the duration specified. As a result, snapshots are available to restore new disks immediately upon creation, without waiting for snapshot background data copy to be completed. Newly restored disks from instant access snapshots benefit from high hydration bandwidth and low latency from the start, as data is served directly from instant access snapshots.

When snapshots are created with instant access enabled, the system begins copying the data to Standard storage in parallel. This ensures that once the instant access duration expires, a fully hardened Standard ZRS snapshot is automatically available, without requiring any additional action.

This architecture enables faster recovery, quicker environment refreshes, and more predictable performance for time-sensitive operations.

How to create instant access snapshots

Instant access snapshots are not a separate snapshot resource class to manage. They are incremental snapshots that temporarily enter Instant Access state for the specified duration. When this duration expires, snapshots automatically transition out of the Instant Access state and continue as Standard ZRS snapshots for better reliability and long-term retention.

If you are already familiar with creating incremental snapshots with existing Azure Snapshot API, enabling instant access support will feel completely natural. The same commands and API endpoints apply; the only difference is a single additional parameter that defines how long the snapshots remain in the Instant Access state. The Azure CLI example below illustrates how to enable instant access when creating incremental snapshots.

Here’s how you create incremental snapshots using Azure CLI today:

< az snapshot create –resource-group <rg-name> –name <snapshot-name> –source <disk-id> –incremental true >

To enable instant access, simply include the InstantAccessDurationMins parameter:

< az snapshot create –resource-group <rg-name> –name <snapshot-name> –source <disk-id> –incremental true   –InstantAccessDurationMins 300 >

The technical demo video below demonstrates how to create instant access snapshots and restore disks in Azure Portal. You will also learn how to easily integrate this capability into your existing snapshot workflow.

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Availability and pricing

Instant access support for incremental snapshots of Premium SSD v2 and Ultra Disk is available in all Azure regions where these disk types are supported, ensuring the capability is available wherever supported mission-critical workloads run.

Instant access support uses a simple, usage-based billing model that charges only for the additional storage capacity consumed and for each restore operation. This approach keeps costs closely aligned with your actual usage, making cloud spend easier to understand and forecast. For full pricing details, see Managed Disk Pricing.

Getting started

As organizations continue to run increasingly time-sensitive mission critical workloads in Azure, instant access support for incremental snapshots of Premium SSD v2 and Ultra Disk provides a practical way to improve recovery time, streamline operations, and scale with confidence.

Explore instant access snapshots documentation
Learn everything you need to know for Azure managed disks.

Explore more

The post Instant access incremental snapshots: Restore without waiting appeared first on Microsoft Azure Blog.
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Unlocking document understanding with Mistral Document AI in Microsoft Foundry

Enterprises today face a familiar yet formidable challenge: mountains of documents -contracts, invoices, reports, forms – remain locked in unstructured formats. Traditional OCR (optical character recognition) captures text, but often struggles with context, layout complexity, or multilingual content. The result? Slow workflows, error-prone manual reviews, and missed insights.

Enter mistral-document-ai-2512 in Microsoft Foundry. This new model brings together high-end OCR using mistral-ocr-2512 and intelligent document understanding using mistral-small-2506 to turn unstructured documents into actionable data. It doesn’t just “read” pages – it understands them: multi-column layouts, handwritten annotations, tables with merging cells, multilingual content-all processed with enterprise-grade speed and precision.

In this blog, we’ll explore what Mistral Document AI 2512 is, why it matters, how it stacks up, and the business impact it promises, especially when paired with solution accelerators like ARGUS.

Meet Mistral Document AI

Mistral Document AI is an enterprise-grade document understanding model, offered via Microsoft Foundry. It’s built to convert both physical (scans, photos) and digital (PDFs, DOCX) documents into highly structured, machine-readable outputs. Key features include:

Top-tier accuracy: According to benchmarks, Mistral’s OCR 2512 stacks display significantly higher accuracy than many alternatives, especially on scanned documents and complex layouts. For example, in comparisons it achieved ~95.9 % “overall” vs ~89-91 % for other platformsGlobal / multilingual reach: In language-by-language tests (Russian, French, German, Spanish, Chinese, etc), Mistral’s error-rate/fuzzy-match metrics reached 99 %+ in many casesLayout & context awareness: It’s built to not just extract linear text but understand multi-column layouts, tables, charts, images, handwritten input and moreStructured output functionality: The model supports structured extraction (JSON), markup (Markdown with interleaved images), preserving document structure for downstream systemsEnterprise-ready deployment: With availability via Microsoft Foundry and support for private/secure inference, the model is geared for regulated industries and high-volume workflowsPutting it another way: where traditional OCR stops at “here’s the raw text on page 7”, Mistral DocumentAI 2512 can say “here’s the vendor invoice, here are line-items, here’s the total, here’s the signature block, and here’s the part that was handwritten”, ready to plug into downstream systems.

Business Impact & Industry examples

Mistral Document AI isn’t just another OCR tool; it’s a strategic enabler that turns document-heavy operations into intelligent, automated workflows. The business value comes down to four key advantages:

Speed and efficiency: Automating document understanding eliminates manual reviews and retyping. Tasks that took days can be done in minutes, accelerating core business processesAccuracy and consistency: With 99 %+ recognition accuracy and deep layout understanding, Mistral delivers cleaner data and fewer downstream errors – essential in compliance-critical or analytics-driven operationsCost and productivity gains: Reducing manual extraction frees teams for higher-value work, cutting operational costs while increasing output per employeeScalability and adaptability: Cloud-native performance allows organizations to scale document processing instantly during peak loads, across multiple languages and formats, without sacrificing qualityOverall, mistral-document-ai-2512 excels where consistency and quality are critical.

Industry and Use CasesIn regulated industries or big-data scenarios, even a small improvement in accuracy or speed can translate into substantial business gains. Its benchmarks indicate not just incremental progress, but a major step forward – giving enterprises a powerful new engine for their document workflows.

Here’s where that impact becomes tangible:

Financial services: Banks and insurers handle vast document volumes – loan applications, KYC forms, and claims reports – where data integrity and auditability are non-negotiable. Mistral automates extraction, classification, and clause identification across diverse formats, improving turnaround time and compliance accuracy while reducing manual handling costs

Healthcare & life sciences: Clinical records, lab results, and insurance claims often combine handwritten, tabular, and multi-language content. Mistral’s layout awareness and multilingual support ensure clean, structured datasets for downstream analytics and regulatory submissions

Manufacturing & logistics: From quality certificates to shipping manifests, Mistral streamlines the flow of operational documents. It can extract production parameters, vendor data, and timestamps at scale – building a unified, queryable data layer that supports supply chain traceability

Legal & public sector: Legal teams and agencies depend on consistency and transparency. Mistral helps index, summarise, and validate contracts or permits with full structural fidelity – dramatically cutting review cycles while maintaining evidential quality

Retail & consumer goods: Retailers process supplier invoices, product specifications, and marketing briefs from global partners. With Mistral’s multilingual precision and structure preservation, global document flows become searchable and analytics-ready

Across these industries, the result is the same: cleaner data, faster throughput, and fewer human errors – the foundation for more reliable decisions and more agile operations.

Pricing

Argus – A ready-to-implement accelerator to start using Mistral Document AI

To spin up a solution faster, one can leverage solution accelerators such as ARGUS (open-source repository available on GitHub).ARGUS serves as a full-pipeline implementation: from document ingestion, OCR/extraction (via Mistral Document AI), to downstream processing and structured output. It shows how to deploy end-to-end, integrate with storage, preprocess documents, handle large-scale batches, output JSON schemas, and integrate into existing business workflows.

Mistral Document AI Integration

ARGUS now offers flexible OCR provider selection with Mistral Document AI as one of the several options. This enhancement gives you the freedom to choose the best OCR engine for your specific document processing needs.

Key Features:

Dual Provider Support: Toggle between Azure Document Intelligence (default) and Mistral Document AIRuntime Switching: Change OCR providers on-the-fly through the Settings UI without redeploymentSimple Configuration: Set up Mistral via environment variables (OCR_PROVIDER, MISTRAL_DOC_AI_ENDPOINT, MISTRAL_DOC_AI_KEY) or the web interfaceSeamless Integration: Both providers expose the same interface, ensuring consistent behavior across your document processing pipelineWhy This Matters:

Different OCR engines excel at processing different document content. Azure Document Intelligence offers enterprise-grade form and table recognition, while Mistral Document AI 2512, in addition, enables extraction to structured JSON with customizable schemas, document classification, and image processing—including text, charts, and signatures. It can convert charts into tables, extract fine print from figures, and even define custom image types for specialized workflows. Now you can select the optimal provider for each use case.

In effect, instead of building from scratch, ARGUS gives you the legs to run: pipeline orchestration, ingestion, error-handling, schema-mapping, output integration-all wired to Mistral’s engine. This significantly accelerates time-to-value and reduces risk for enterprise adopters.

Getting Started:

Navigate to the ARGUS frontend interface (Streamlit app) and click on the Settings tab. In the OCR Provider Configuration section, select your preferred provider. If using Mistral, enter your endpoint URL, API key, and model name. Click Update OCR Provider to apply changes immediately—no restart required. All new document processing will use your selected OCR engine.

If your organization is looking to unlock document intelligence, here’s a structured path:

Explore Mistral Document AI via Microsoft Foundry: Browse the model card, review endpoint specs, try sample documents to test accuracy and extraction structureDeploy and Pilot with ARGUS: Use the GitHub repo to spin up an end-to-end pipeline on a small workload (e.g., a batch of invoices or contracts) and compare manual vs AI-driven throughput and error-ratesDefine business value metrics: Track processing time, error rate, manual hours saved, and downstream impact (faster decision cycles, fewer reworks).Scale and govern: Once pilot proves value, expand into multiple document types, languages, geographies – and ensure governance (data handling, compliance, model-monitoring)Embed continuous improvement: As usage grows, feed back learnings, tune schema definitions, refine extraction rules, and extend into QA, insights or analytics layers

Conclusion

In today’s data-rich but document-heavy environment, the ability to truly understand documents (and not just digitize them) is becoming a strategic imperative. Mistral Document AI represents a next-generation shift: accurate, layout-aware, multilingual, structured. When paired with accelerators like ARGUS, enterprises can move from manual bottlenecks to streamlined, insight-rich document workflows.

If you’re thinking about unlocking the value buried in your documents-be it invoices, contracts, forms or reports, now is the time. With mistral-document-ai-2512, what used to be a cost-center is now a potential performance lever.

Ready to get started? Explore the model, and let your documents begin talking back.
The post Unlocking document understanding with Mistral Document AI in Microsoft Foundry appeared first on Microsoft Azure Blog.
Quelle: Azure

Amazon OpenSearch Ingestion now supports unified ingestion endpoint for OpenTelemetry data

Amazon OpenSearch Ingestion now supports a unified ingestion endpoint that can accept all three OpenTelemetry observability signals — logs, metrics, and traces — through a single pipeline. Previously, customers who wanted to ingest all three OpenTelemetry data types had to create and manage three separate pipelines, one for each signal type. With this launch, a single pipeline can now receive any combination of OpenTelemetry signals, simplifying pipeline architecture and reducing operational overhead. Customers can now build centralized observability pipelines that consolidate logs, metrics, and traces in one place, making it easier to correlate signals and gain a holistic view of application health. Teams operating at scale can reduce the number of pipelines they manage, lowering infrastructure costs and simplifying access control, monitoring, and lifecycle management. This also makes it easier to adopt OpenTelemetry incrementally as teams can begin with one signal type and add others over time without any pipeline reconfiguration. The unified ingestion endpoint for OpenTelemetry data is supported in all regions that Amazon OpenSearch Ingestion is currently available. Customers can get started by using the new unified OpenTelemetry source in their pipeline configuration via the AWS Management console or using the AWS CLI and point their OpenTelemetry clients to the new unified endpoint. To learn more and get started, visit the Amazon OpenSearch Ingestion documentation.
Quelle: aws.amazon.com

Amazon SageMaker HyperPod now provides comprehensive observability for Restricted Instance Groups

Amazon SageMaker HyperPod now offers comprehensive observability for Restricted Instance Groups (RIG), enabling teams training foundation models with Nova Forge to gain deep visibility into their compute resources and training workloads. This new capability eliminates the manual effort of collecting and correlating metrics across the infrastructure stack, providing a unified view of GPU performance, system health, network throughput, and Kubernetes cluster state through a pre-configured Amazon Managed Grafana dashboard backed by Amazon Managed Service for Prometheus.
You can now monitor GPU utilization, NVLink bandwidth, CPU pressure, FSx for Lustre usage, and pod lifecycle from a single Grafana dashboard, with metrics collected across four exporters covering GPU performance, host-level system health, network fabric, and Kubernetes object state. In addition, curated logs are automatically made available in these dashboards, covering epoch progress, step-level training logs, pipeline errors, and Python tracebacks, so you can quickly diagnose training failures. HyperPod Observability for Restricted Instance Group is automatically enabled when you create a new cluster using RIGs, or can be enabled for existing clusters in a few clicks in the HyperPod cluster management console.
Amazon SageMaker HyperPod RIG observability is available in all AWS Regions where SageMaker HyperPod RIG is supported. To learn more, visit the documentation.
Quelle: aws.amazon.com

AWS simplifies IAM role creation and setup in service workflows

AWS Identity and Access Management (IAM) now makes it easier to create and configure IAM roles directly within service workflows, allowing you to customize role permissions without switching between browser tabs. Now, when you are performing console tasks that involve role configuration, a new panel will appear to set the permissions required. IAM roles enable secure AWS cross-service connections using temporary credentials, eliminating the need for hardcoded access keys. This launch integrates role creation capabilities with custom permissions directly into service workflows, allowing you to configure roles and permissions without navigating to the IAM console. You can use default policies or the simplified statement builder to customize your permissions, streamlining your resource setup while maintaining the full functionality of IAM role management. This feature is available when working with Amazon EC2, AWS Lambda, Amazon EKS, Amazon ECS, AWS Glue, AWS CloudFormation, AWS Database Migration Service, AWS Systems Manager, AWS Secrets Manager, Amazon Relational Database Service, and AWS IoT Core in the US East (N. Virginia) Region. The feature will gradually become available across additional AWS services and regions. To learn more, refer to individual service User Guide or IAM documentation.
Quelle: aws.amazon.com