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table of contents Pattern matching is not just condition checking. It reflects how you think as a developer. Matching and validation can be achieved in a naive, descriptive way. However, a cleaner approach stands out in terms of readability and sometimes performance. Pattern matching combines patterns to express …
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The complexity of modern containerized applications often leaves developers drowning in a sea of "noise"—vulnerabilities that exist in the file system but pose zero actual risk to the application. The integration between Black Duck and Docker Hardened Images (DHI) provides a definitive answer to this …
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Hello Java customers! We are happy to announce the latest April 2026 patch & security update release for the Microsoft Build of OpenJDK. Check our Link to article: https://devblogs.microsoft.com/java/java-openjdk-april-2026-patch-security-update
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Learn Regex.Match, Matches, and IsMatch in C# with named groups, capture collections, and .NET 7 EnumerateMatches for zero-allocation matching. Link to article: https://www.devleader.ca/2026/05/04/regexmatch-matches-and-ismatch-in-c-named-groups-and-capture-collections
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Business leaders across industries rely on operational dashboards as the shared source of truth that their teams execute against daily. But dashboards are built to answer known questions. When teams need to explore further, ad-hoc, multi-dimensional, or unforeseen questions, they hit a bottleneck. They wait hours or …
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Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evolve, user behavior shifts, and prompts get reused in new contexts they were never designed for. Agent quality quietly …
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Amazon SageMaker AI now offers an agentic experience that changes this. Developers describe their use case using natural language, and the AI coding agent streamlines the entire journey, from use case definition and data preparation through technique selection, evaluation, and deployment. In this post, we walk you …
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Welcome back to the building blocks for AI in .NET series! In part one, we explored Microsoft Extensions for AI (MEAI) and how it provides a unified interface for working with large language models. In Link to article: https://devblogs.microsoft.com/dotnet/microsoft-agent-framework-building-blocks-for-ai-part-3
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Building meaningful dashboards demands hours of manual setup, even for experienced BI professionals. Amazon Quick now generates complete multi-sheet dashboards from natural language prompts, taking you from one or more datasets to a production-ready analysis in minutes. Data analysts building recurring operations …
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Placing SQL MCP Server between your AI agent and your SQL database lets your agent interact with data through a controlled API surface instead of direct database access. Built on Data API builder (DAB), SQL MCP Server brings DAB features to agentic solutions, including caching, telemetry, authentication, and …
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"Is ContosoParts.msix installed?" is a common - but misleading - question The term install is not a formal concept in MSIX. This may seem paradoxical for a deployment technology, but it makes perfect sense once you understand MSIX deployment’s core ar Link to article: …
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Put a capable coding model inside a developer’s primary workspace, and the IDE stops being a place where you write code. It becomes a place where you direct an agent, watch how it reasons, manage what it pays attention to, and decide when its output is worth shipping. That was the defining theme of the […] Link to …
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Amazon Quick introduces Amazon S3 Tables (Apache Iceberg tables) as a new data source. With this feature, customers can directly query and visualize Apache Iceberg tables stored in an Amazon S3 table bucket without the need for intermediate data layers. In this post, we explored how Amazon Quick’s new Amazon S3 Tables …
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Introducing Dataset Q&A: Expanding natural language querying for structured datasets in Amazon Quick
In this post, you learn how to get started with Dataset Q&A, explore real-world use cases with hands-on examples, and discover advanced capabilities like auto-discovery across all your data assets and multi-dataset querying in a single conversation. Link to article: …
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Today, Amazon SageMaker AI introduces capacity aware instance pool for new and existing inference endpoints. You define a prioritized list of instance types, and SageMaker AI automatically works through your list whenever capacity is constrained at creation, during scale-out, and during scale-in. Your endpoint …
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When you migrate .NET applications from SQL Server to Amazon DynamoDB, your existing pagination patterns need adaptation. .NET applications commonly use page number navigation with Language Integrated Query (LINQ) Skip() and Take() methods, which rely on SQL Server’s OFFSET/FETCH NEXT clauses and indexed ordering to …
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In February, we announced how GitHub Copilot can now use C++ symbol context and CMake build configuration awareness to deliver smarter suggestions in Visual Studio Code. Today, we're excited to share new Link to article: …
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A customer wanted to know how to inform Windows that they were opening a file in text mode, as opposed to binary mode. That way, Windows can perform text conversions as necessary, like adding carriage returns before linefeeds, or converting ASCII to Unicode. Windows doesn't know whether your file is binary or text. As …
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We ran the same coding tasks with and without prebundled tooling, across multiple models and languages. Here’s what changed. Eval-driven development IDE-native search reduced latency, cost, and budget overruns. The comparison below uses paired task-level deltas. Aggregate medians and totals are shown for orientation. …
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