News For Dev-ops

AWS HealthOmics announces a Kiro Power and Kiro IDE extension to create, run, debug, and optimize HealthOmics workflows faster with AI agent-assisted development. With the HealthOmics extension for Kiro IDE, customers can create, modify, and analyze workflows in domain-specific languages including Nextflow and WDL directly in the Kiro interface. AWS HealthOmics is a HIPAA-eligible service that helps accelerate scientific breakthroughs at scale with fully managed bioinformatics workflows. Kiro Powers is a repository of curated and pre-packaged Model Context Protocol (MCP) servers, steering files, and agent hooks to accelerate specialized software development and deployment use cases. The Kiro Power for HealthOmics packages the HealthOmics MCP server with guidance, giving the Kiro agent expertise in HealthOmics workflow creation and optimization. The HealthOmics Kiro IDE extension provides syntax highlighting, code completion, and troubleshooting guidance, along with HealthOmics engi...

Amazon Redshift now supports allocating extra compute for automatic optimization features, known as autonomics. Database administrators managing Amazon Redshift workloads can now allocate additional resources for their clusters to enable autonomics even during periods of high user activity, eliminating the need to manually schedule optimizations such as Automatic Table Optimization (ATO), Automatic Table Sorting (ATS), Auto Vacuum, and Auto Analyze. This enhancement extends Amazon Redshift's autonomics capabilities to automatically leverage extra compute resources, to run reliably without impacting user workloads. It also includes a cost control feature for provisioned clusters, allowing database administrators to limit the amount of resources available to autonomics. Additionally, the new SYS_AUTOMATIC_OPTIMIZATION system table enhances observability by providing detailed information on autonomics operations for both provisioned clusters and serverless workgroups. This feature...

Applications often need to know what data looked like before. Who changed it, when it changed, and what the previous values were. Rebuilding that history in application code is tedious and error prone. This is especially valuable when exposing a database to an AI agent through MCP servers like SQL MCP Server, where information discovery matters. Learn more about SQL MCP Server at https://aka.ms/sql/mcp Azure SQL includes a built in feature that tracks row history automatically. Temporal tables let the database keep a full change history without triggers, audit tables, or custom logic. Working demo https://gist.github.com What We Are Building A table that automatically tracks every change over time. Step 1: Create the Table A temporal table requires two datetime columns that define the validity period. Azure SQL manages these automatically when you enable system versioning. CREATE TABLE dbo.Todos ( Id INT IDENTITY(1,1) PRIMARY KEY, Title NVARCHAR(200) NOT ...

If you call a wait function like Wait­For­Single­Object and receive the code WAIT_ ABANDONED , what does it mean and what should you do? The documentation says that WAIT_ ABANDONED means that you successfully claimed a mutex, but the thread that previously owned the mutex failed to release the mutex before it exited. This could be an oversight because the code encountered a code path that forgot to release the mutex. Or it could be because the thread crashed before it could release the mutex. The documentation also suggests that "If the mutex was protecting persistent state information, you should check it for consistency." This is to handle the second case: The thread crashes before it can release the mutex. If the purpose of the mutex was to prevent other threads from accessing the data while it is in an inconsistent state, then the fact that the thread crashed while holding the mutex means that the data might still be in that inconsistent state. Now, maybe you have no...

User preferences and settings are fundamental components of modern web applications. When developing SharePoint Framework (SPFx) solutions, the ability to store and manage user-specific configurations across devices and sessions becomes crucial for delivering personalized experiences. This article explores a robust, enterprise-ready pattern for handling user settings in SharePoint Framework applications. There is also a companion sample available on the Community Sample Solution Gallery . You can simply download the source code of the sample and then follow this article to understand how it works. Understanding the Challenge The Need for Persistent User Settings In SharePoint Framework development, we frequently encounter scenarios where web parts or extensions require the ability to store user-specific information, options, or preferences. Traditional client-side storage mechanisms, such as localStorage or sessionStorage , fall short when we need: Cross-device synchronization : S...

Amazon Web Services (AWS) is announcing the general availability of cross-account sharing for Amazon EC2 Capacity Blocks for ML. This capability allows organizations to share reserved GPU capacity across AWS accounts using AWS Resource Access Manager (RAM), helping optimize utilization and reduce costs. Organizations can now purchase Capacity Blocks and provision them across multiple accounts, allowing different workloads to access a pool of reserved capacity at no additional cost. This capability helps teams coordinate ML infrastructure investments and keeps reserved GPU capacity in continuous use across different workloads. This feature is available for all Instance Capacity Blocks in AWS Regions where EC2 Capacity Blocks for ML are offered. For a complete list of supported regions, refer to Capacity Blocks Supported Regions documentation .  To get started, create a Resource Share through AWS Resource Access Manager, add your Capacity Blocks for ML resources, and specify the t...