News For Dev-ops

We are excited to announce the general availability of Amazon Nova Multimodal Embeddings, a state-of-the-art embedding model for agentic RAG and semantic search. It is the first unified embedding model that supports text, documents, images, video, and audio through a single model, to enable cross-modal retrieval with leading accuracy. Managing and searching across different content types traditionally required multiple specialized embedding models, leading to complexity, higher costs, and data silos. Amazon Nova Multimodal Embeddings maps diverse content types into a unified space with leading accuracy, helping break down these silos. Developers can build cross-modal applications that search video archives using complex queries, find relevant product images based on customer questions, or search financial documentation that contain both infographics and text explanations, all using a single embedding model. The model supports inputs of up to 8K tokens in length and video/audio segm...

This article was co-authored by Zack Rossman, Staff Software Engineer, Veeam; Ashlie Martinez, Staff Software Engineer, Veeam; and James Nguyen, Senior Principal Cloud Solution Architect, AI/ML, Microsoft. Most people think of data resilience as two steps: backup and recovery. Backup creates a copy. Recovery brings it back when disaster strikes. But what if you can’t find the file you need to recover when it matters? At Veeam, we’re committed to delivering reliable and comprehensive data resiliency at planet-scale. That’s why we’ve invested in intuitive, powerful data discovery. It makes sure that contract email, or that missing finance spreadsheet, is right at your fingertips. Before we reinvented the data discovery workflow in Veeam Data Cloud, everything lived in Azure Blob Storage. Durable, yes. Searchable, not so much. On a small scale, scanning blobs byte by byte was fine. But at enterprise scale with billions of new items added each day across multiple petabytes? That was a no ...

A long time ago, somebody asked, "How did the new Windows 95 user interface get brought to the Windows NT code base? The development of Windows 95 lined up with the endgame of Windows NT 3.1, so how did the finished Windows 95 code get brought to the Windows NT code base for Windows NT 4.0? Did they reimplement it based on the existing specification? Was the code simply merged into the Windows NT code base?" Members of the Windows 95 user interface team met regularly with members of the Windows NT user interface team to keep them aware of what was going on and even get their input on some ideas that the Windows 95 team were considering. The Windows NT user interface team were focused on shipping Windows NT, but they appreciated being kept in the loop. During the late phases of the development of Windows 95, the Windows NT side of the house took a more active role in bringing the Windows 95 user interface to Windows NT. They started implementing the new window manager featu...

Thank you for your interest in the new Azure SDKs! We release new features, improvements, and bug fixes every month. Subscribe to our Azure SDK Blog RSS Feed to get notified when a new release is available. You can find links to packages, code, and docs on our Azure SDK Releases page . Release highlights Azure AI Foundry 1.0.0 for .NET The first stable release of the Azure AI Foundry library for .NET provides comprehensive access to Azure AI Foundry Project resources. The library enables developers to: Create and run AI Agents Manage AI model deployments Handle connections to Azure resources Upload documents and create datasets Manage search indexes This release introduces important API improvements with consistent AIProject prefixing for key models ( AIProjectDeployment , AIProjectConnection , AIProjectIndex ), simplified client access through direct properties on AIProjectClient (replacing individual Get*Client methods), and new convenience CreateOrUpdate methods for i...

AWS Payment Cryptography  has expanded its global presence with availability in three new regions - Canada(Montreal), Africa (Cape Town) and Europe (London). This expansion enables customers with latency-sensitive payment applications to build, deploy or migrate into additional AWS Regions without depending on cross-region support. For customers processing payment workloads in Europe, availability in London offers additional options for multi-Region high availability. AWS Payment Cryptography is a fully managed service that simplifies payment-specific cryptographic operations and key management for cloud-hosted payment applications. The service scales elastically with your business needs and is assessed as compliant with PCI PIN and PCI P2PE requirements, eliminating the need to maintain dedicated payment HSM instances. Organizations performing payment functions - including acquirers, payment facilitators, networks, switches, processors, and banks can now position their payment c...

Amazon Cognito now enables app clients to specify resource indicators during access token requests as part of its OAuth 2.0 authorization code grant and implicit grant flows. The resource indicator identifies the protected resource, such as a user’s bank account record or a specific file in a file server that the user needs to access. After authenticating the client, Cognito then issues an access token for that specific resource. This ensures that access tokens can be limited from broad service level access down to accessing specific individual resources. This capability makes it simpler to protect resources that a user needs to access. For example, agents (an example of app clients) on behalf of users can request access tokens for specific protected resources, such as a user’s banking records. After validation, Cognito issues an access token with the audience claim set to the specific resource. Previously, clients had to use non-standard claims or scopes for Cognito to infer and iss...

A denial of service vulnerability report was filed against a program, let's call it Notepad. The actual text of the report was very hard to understand because the grammar was all messed up. I'll give the finder the benefit of the doubt on the assumption that they are not a native English speaker. Here's a cleaned-up version: If you open multiple documents, one very large document and several small documents, and then try to exit all of them at once, the program will take a very long time saving the large document, resulting in a denial of service against the small documents. I'm not sure what the point is here. The program does eventually finish saving the large document, so everything works out in the end. Are they suggesting that the program should save the smallest documents first? But then wouldn't that be a denial of service against the large document if you had lots of small documents? But wait, let's ask the standard questions. Who is the attacker? I...