Agentic AI Advancements, GitHub Copilot Progress, Hybrid DevOps, and Secure Cloud Updates
Welcome to this week’s Tech Roundup, where updates in automation, developer capabilities, and security show how technology is evolving. GitHub Copilot introduces improvements in model speed, multi-model selection, and stronger IDE integration—helping developers work faster and with increased context. Step-by-step guides and community examples demonstrate how agentic workflows are becoming practical, with applications ranging from cloud migration to creative open-source solutions.
Microsoft’s AI and Azure offerings stand out, with new agent frameworks, multi-agent orchestration, adaptive signals, and automation tools that benefit cloud and edge deployments. Azure details new features including Python support for serverless apps, distributed tracing, and security. DevOps teams continue to use open observability, AI-powered code review, and refined cloud governance. Security remains a top priority: articles on Log4Shell, supply chain protection, and modern identity management provide actionable advice for avoiding threats. Whether you’re using Copilot to improve your processes, building reliable cloud-native platforms, or strengthening your supply chain, this week’s information helps you stay informed and prepared for ongoing changes in connected, secure, agent-driven technology.
This Week’s Overview
- GitHub Copilot
- Speed, Model Accuracy, and Copilot Integration Updates
- Model Choice and Agentic AI Platform Extensions
- Copilot Workflow Guides, Advanced Usage, and MCP Integration
- Copilot in Live Coding, Community, and Creative Use Cases
- Contextual AI and Copilot Highlights in Documentation
- Advanced Usage, Education, and Developer Adaptation
- AI
- Microsoft Agent Framework: From Application Upgrades to Multi-Agent Enterprise Orchestration
- Adaptive AI: Signals Loops, Agentic Lifecycle, and Fine-Tuning in Azure AI Foundry
- Edge and On-Premises AI: Azure AI Foundry Local Deepens Real-Time and Private Workloads
- Retrieval-Augmented Generation and Hybrid Search: Building Smarter Enterprise Applications
- Model Context Protocol (MCP), Registry, and Serverless GenAI on Azure
- Developer AI Agents and Agentic Automation: From Productivity to Open Source Extension
- Small Language Models and Local Agentic Workflows in .NET
- Multi-Agent Orchestration: Patterns and Practical Integration with Azure AI Foundry
- Microsoft Copilot Studio: Expanded Customization, Automation, Integration
- AI-Driven Code Quality and Security: Analysis, Tools, and DevOps Integration
- AI Workflow Reusability, Developer Experience, and the Future of Web Development
- AI, Cloud, and Security for Startups: Ignite 2025 Conference
- ML
- Azure
- Azure Functions Python Performance and Integration
- Advanced Cloud Observability: Distributed Tracing for Azure Microservices
- Cloud Reliability: Load Testing in Azure Chaos Studio
- Migration Preparedness: Azure Relay IP and DNS Changes
- Fabric Platform: Real-Time Analytics, Data Engineering, and Community Highlights
- Microsoft Fabric Data Engineering: Secure Connectivity and API Compatibility
- Azure Resource Management and Automation
- Architecture Patterns and Decision Making
- RabbitMQ Connector for Azure Logic Apps
- Azure API Management: Native Service Bus Integration
- Other Azure News
- Coding
- DevOps
- OpenTelemetry, AI, and Cost-Efficient Observability Architectures
- DevOps, AI Adoption, and Metrics Evolution
- Automated Vulnerability Remediation and Nano Updates in DevOps
- GitHub Enterprise Cloud: Governance, Security, and Organization Management
- AI-Powered Code Quality and Analysis in DevOps
- SRE for AI and Hybrid Infrastructure
- Hybrid Cloud and DevOps Workflows
- Security
GitHub Copilot
This week’s GitHub Copilot updates focus on increased speed, better model accuracy, model management features, and new workflow improvements. The developer community saw technical advances and practical guides for deploying tailored AI models, greater extension support in VS Code, and deeper analysis of Copilot’s place in real-world development. Tutorials and feature highlights show how Copilot is used both as a coding assistant and a link for agentic workflows, cloud migration, documentation help, and creative development.
Speed, Model Accuracy, and Copilot Integration Updates
Building on the recent rollout of GPT-4.1 and Claude Sonnet 4.5, GitHub made further advances in model training and benchmarking. Fine-tuning and custom reinforcement learning for fill-in-the-middle tasks enhance context-sensitive results. These improvements led to a 20% increase in accepted code, 12% higher suggestion acceptance, and higher speed, positioning Copilot as a multi-model platform for intelligent automation. The updates are now available in Copilot-compatible IDEs, offering developers faster, more automated workflows.
The October VS Code AI Toolkit update (v0.24.0) tightens Copilot’s editor integration, allowing Copilot Tools to be used directly within VS Code. New features like the Agent Evaluation Planner and Runner simplify analysis of metrics and results, reducing tool-switching and supporting context-driven tasks as mentioned in previous roundups.
- Building a Faster, Smarter GitHub Copilot with Custom Models
- AI Toolkit for VS Code October Update: GitHub Copilot Tools Integration
Model Choice and Agentic AI Platform Extensions
Increasing options for multi-model support and agentic workspaces, VS Code now provides Bring Your Own Key (BYOK) and the Language Model Chat Provider API. This opens up new choices for enterprise and open-source models such as Hugging Face, Ollama, and Cerebras, in addition to existing support for OpenAI, Claude Sonnet 4.5, and Grok Code Fast 1. Support for modular AI assistance keeps growing; note that code completion is not yet available for BYOK.
Copilot’s Planning mode preview in Visual Studio 2022 offers hierarchical, editable prompt plans with models including GPT-5 and Claude Sonnet 4. User feedback on live editing continues to drive improvements in agentic workflows.
Copilot is retiring older Claude, OpenAI, and Gemini models, continuing the changes discussed in previous updates. Teams should update to newer models to ensure continued compatibility, and broader Claude Haiku 4.5 support (now in all Copilot plans and IDEs) helps tailor workflow fit.
- Expanding Language Model Choice in VS Code with Bring Your Own Key and New API
- Introducing Planning in Visual Studio: Copilot Agent Mode Public Preview
- GitHub Copilot Deprecates Legacy Claude, OpenAI, and Gemini Models
- Claude Haiku 4.5 Now Available in GitHub Copilot Across All Supported IDEs
Copilot Workflow Guides, Advanced Usage, and MCP Integration
New guides on prompt engineering and context management, such as the Persona Pattern guide, build on last week’s information regarding prompt versioning and .prompt.md usage. The focus remains on accuracy and productivity, and aligns with recent best practices.
Copilot’s integration into agentic AI workflows for updating legacy Java and .NET applications continues the shift toward system upgrades and PowerShell automation. Real-world examples, automated upgrades, and Infrastructure-as-Code template generation mark Copilot’s increasing role in hybrid cloud migration, consistent with previous orchestration discussion.
MCP server extensions for VS Code provide faster documentation and quick database deployments, demonstrating better support for external data and APIs. This continues the evolution of secure, domain-specific suggestions featured in last week’s roundup.
A new GitHub Copilot Certification article reinforces responsible use, privacy, and test automation, extending earlier discussions on training, community education, and actual feature usage in development.
- Context Engineering Recipes: Using the Persona Pattern with GitHub Copilot
- AI & GitHub Copilot: Modernizing Legacy Apps for the Cloud
- Rapid Database Integration in VS Code with Microsoft Learn MCP Server and GitHub Copilot
- Adding a Database to Your App with GitHub Copilot and Microsoft Docs MCP Server
- What is Model Context Protocol (MCP) in GitHub Copilot?
- What Is the GitHub Copilot Certification and Why It Matters for Developers
Copilot in Live Coding, Community, and Creative Use Cases
GitHub Universe and the ‘For the Love of Code’ hackathon highlighted Copilot’s integration into practical events and creative open-source development, continuing the story from previous weeks. Live coding in VS Code provided chances to interact directly with tool creators and get actionable advice, further building on MCP community involvement.
Showcases of open-source projects using Copilot demonstrated both accessibility and unique deployment scenarios, following last week’s ‘No Bark’ case study. Tutorials on building a DJ app illustrated Copilot’s value for creative coding and prompt-driven experiments.
- VS Code Live Coding with GitHub Copilot at GitHub Universe
- VS Code Live at GitHub Universe: Live Coding with Copilot
- For the Love of Code: GitHub Hackathon Winners Showcase Creative Projects with Copilot
- Live-Coding a DJ App with VS Code and GitHub Copilot
Contextual AI and Copilot Highlights in Documentation
Copilot Highlights in Microsoft Learn documentation are refining delivery methods. Building on last week’s introduction of AI-powered guidance and step reasoning, this update supports technical writers and developers with more practical, example-oriented workflows.
Tutorials for maintaining community health files now include Copilot-supported automation for ongoing compliance and iterative updating. These enhancements help to reduce manual maintenance and improve prompt strategies for better context assistance.
- AI-Powered Enhancements in Microsoft Learn Developer Docs with Copilot Highlights
- Streamline Community Health Files with AI and GitHub Copilot
Advanced Usage, Education, and Developer Adaptation
New education and advanced usage guides build on last week’s podcast discussions and agent memory content. Revisions now add details for chat agent configuration and GPT-4.1 setup in VS Code. Fresh podcasts and articles continue the series on optimizing Copilot workflows.
Reviews of how Copilot affects software engineer and student workflows extend last week’s focus on AI agents, productivity, and project speed using MCP and Copilot CLI. Automatic documentation, test creation, and code review for large codebases continue to be central, promoting updates in curriculum and organizational adoption as Copilot gains traction.
- Mastering Chat Modes in VS Code with Burke Holland
- How Software Engineers and Students Use AI to Move Faster than Ever (without breaking things)
- Your 6-Step Guide to Deploying a Website with GitHub Codespaces and Copilot Agent Mode
AI
Recent AI developments include growth in agent frameworks, better cloud and edge integrations, and updates in automation and security. Microsoft’s platforms—Agent Framework, MCP, Copilot Studio, and Azure AI Foundry—continue to put agents at the core of cloud-native, privacy-aware, and edge scenarios. Updates include new patterns in multi-agent orchestration, ongoing monitoring, signals-driven adjustments, and lifecycle management, with concrete progress on developer productivity and compliance.
Microsoft Agent Framework: From Application Upgrades to Multi-Agent Enterprise Orchestration
Advancing last week’s discussion of MCP and agent-based workflows, Agent Framework adds more features and new integration options. Step-by-step guides and workshops help developers move from older Semantic Kernel and Blazor chat applications to orchestrated, multi-agent solutions in .NET 9. Support for enterprise orchestration—including sequential and concurrent workflow patterns—continues the focus on modularity. OpenTelemetry and DevUI integrations improve observability, while hosting agents on Azure App Service and using Cosmos DB for agent state expand guidance toward scalable, production deployments.
Multi-agent coordination with MCP and audit features carry forward the open-source registry approach for enterprise adoption. New SentinelStep and SentinelBench tools are maturing agent lifecycle and reliability standards for sustained workloads.
- Upgrading to Microsoft Agent Framework in Your .NET AI Chat App
- .NET AI Community Standup: Microsoft Agent Framework Workflows & Migration
- Multi-Agent Orchestration in Enterprise AI with Microsoft Agent Framework
- Build Long-Running AI Agents on Azure App Service with Microsoft Agent Framework
- Orchestrating Multi-Agent Intelligence with Microsoft Agent Framework and MCP
- Building Persistent Monitoring Agents with SentinelStep in Magentic-UI
- Microsoft Agent Framework WorkFlows Explained
- Microsoft Agent Framework Workflows: Deep Dive and Advanced Concepts
Adaptive AI: Signals Loops, Agentic Lifecycle, and Fine-Tuning in Azure AI Foundry
Building on last week’s coverage of model fine-tuning, this week brings more emphasis on signals loops and continuous improvement for agentic AI. Agentic Lifecycle Management (ALM) now formalizes agent development and governance, expanding feedback cycles.
More business-centric feedback processes extend previous GPT-4o-mini documentation automation, supporting quality checks and autonomous code review. Step-by-step resources for enterprise adoption now include operational details such as telemetry pipelines and MELT stack tools. The nine safety guardrails maintain a consistent focus on secure deployments and agent monitoring.
- The Signals Loop: Fine-Tuning for World-Class AI Apps and Agents
- The Developer’s Guide to Agentic AI: The Five Stages of Agent Lifecycle Management
- Rewriting the Rules of Software Quality: Why Agentic QA is the Future CIOs Must Champion
- The Agentic AI-Driven Future of Telemetry
- Before You Deploy AI Agents in Observability: Nine Key Guardrails for Safety
Edge and On-Premises AI: Azure AI Foundry Local Deepens Real-Time and Private Workloads
Azure AI Foundry Local advances last week’s toolkit discussion, offering local and edge deployment options to meet stricter privacy and compliance requirements found in healthcare, energy, and regulated settings.
SDKs designed for multiple frameworks, support for low-latency inference, and GPU acceleration tutorials continue last week’s focus on automation and container hosting. These features expand agentic AI intelligence to edge and on-prem infrastructure.
- A Developer’s Guide to Edge AI with Microsoft Foundry Local
- Understanding Azure AI Foundry Local: On-Premises AI for Privacy and Security
- What is Azure AI Foundry Local?
Retrieval-Augmented Generation and Hybrid Search: Building Smarter Enterprise Applications
RAG pipelines with Azure AI Search and OpenAI Service extend the scope of smart documentation and embedding search covered last week. New how-to articles, prompt methods, and troubleshooting tips build on distributed inference and dynamic routing with GPT-4o-mini. The introduction of BYOPI (Build Your Own Private Indexer) moves deployment resources toward secure, hybrid-compliant scenarios for regulated businesses.
- Unlocking Smarter Search: Integrating Azure AI Search and Azure OpenAI Service
- BYOPI: Building a Custom Private Azure AI Search Indexer with Azure Data Factory
Model Context Protocol (MCP), Registry, and Serverless GenAI on Azure
Open-source MCP registries and related tools remain important for agentic collaboration. New articles detail server setup, security integration, and CLI adoption, marking increased use and operational stability. Serverless GenAI guides for LangChain.js v1 build on last week’s MCP preview, providing concrete deployment and observability directions for Azure.
Articles focus on authentication, CI/CD automation, and allowlist management, building on last week’s compliance coverage and strengthening secure and scalable AI deployments.
- How to Find, Install, and Manage MCP Servers with the GitHub MCP Registry
- Serverless MCP Agent with LangChain.js v1: Full-Stack GenAI Deployment on Azure
Developer AI Agents and Agentic Automation: From Productivity to Open Source Extension
Open source agent extensions and developer automation continue the series of updates related to Copilot Studio and developer-tier guides. The SRE Agent and community modules keep building out the ecosystem with flexible, modular AI developer tools—a shift begun last week. New extensions make it easier to increase productivity and adapt to workflow changes.
- Advancements in Developer Agents: Task Automation and Open Source Extensions
- Agents for Developers: Latest Advancements in Developer Productivity
Small Language Models and Local Agentic Workflows in .NET
New tutorials on small language models in .NET expand last week’s focus on agent orchestration and autonomous workflows built with Semantic Kernel. Step-by-step articles provide code samples for embedding retrieval-augmented generation and agentic patterns locally, transitioning from theory to actionable implementation.
Multi-Agent Orchestration: Patterns and Practical Integration with Azure AI Foundry
Azure Essentials guides advance last week’s coverage of modular orchestration frameworks, now introducing reusable patterns and advanced integration options. The move from concepts to practical cloud-native multi-agent governance is supported with actionable resources.
- Optimize Complex Workflows with Multi-Agent AI Patterns in Azure
- Optimize Complex Workflows Using Multi-Agent AI Patterns
Microsoft Copilot Studio: Expanded Customization, Automation, Integration
September 2025 Copilot Studio updates continue last week’s coverage of customizable agents and prompt engineering. New features like hosted browser options and WhatsApp integration provide additional agent workflow choices, while evaluation tools and analytics dashboards connect to past topics in enterprise management. The Agent Academy adds new training resources, extending the focus on developer education.
AI-Driven Code Quality and Security: Analysis, Tools, and DevOps Integration
Progress in code security and validation for AI-generated output builds on last week’s SonarSweep coverage. New tools for detecting code anti-patterns reinforce previous themes of AI-powered quality assurance, supporting enterprise-level review and best practices.
- 10 AI Coding Tool Behaviors That Ignore Software Engineering Best Practices
- SonarSweep: Improving AI-Generated Code Quality and Security
AI Workflow Reusability, Developer Experience, and the Future of Web Development
Workflow modularity and reuse continue to stand out, following last week’s cataloging focus. New guides present strategies for versioning, repeatable design, and future agentic interfaces in web development—helping teams achieve operational efficiency and plan durable projects.
- Don’t Reinvent the Wheel: A Developer’s Guide to AI Reusability
- The Future of Web Development with AI Integration
AI, Cloud, and Security for Startups: Ignite 2025 Conference
The Ignite 2025 agenda parallels last week’s discussions on ecosystem strategies, with tips for startups regarding Copilot, Azure AI Foundry, compliance, and agentic AI product design. Topics such as generative AI, SDK extension, and marketplace readiness remain at the forefront, keeping the material relevant for builders and the broader community.
ML
Recent progress in machine learning underlines improvements in model fine-tuning and deployment, emphasizing vision-language models (VLMs) for image classification on Azure AI Foundry. Developers are given clearer steps for achieving better accuracy, controlling costs, and supporting production deployments.
Fine-Tuning GPT-4o Vision-Language Models on Azure AI Foundry
A new guide covers fine-tuning GPT-4o for image classification (using Stanford Dogs), continuing last week’s push for performance and usability in ML stacks. The tutorial covers data formatting in Azure JSONL, using Batch Inference API for large workloads (with higher latency and reduced cost), and connects to past automation topics drawn from Microsoft Fabric.
Instructions include using the Vision Fine-Tuning API to adapt GPT-4o for breed identification. The inclusion of public code samples and templates supports research and encourages wider use, echoing Azure ML’s focus on analytics and efficiency. Demonstrated results improved accuracy from 61.67% (CNN) to 82.67% for a fine-tuned model, with a detailed breakdown of cost and latency to help with deployment planning.
Production guidance centers around Azure’s security and scalability, detailing parameter adjustment, throughput, and best practices. Open-source code and Azure documentation make this a practical resource for ML engineers.
Azure
Azure this week introduces new platform features, broader integration, and guides for modern cloud-native and hybrid resource management. Recent improvements include better performance for Azure Functions Python, expanded Fabric support, and upgrades in real-time analytics for efficiency and monitoring. New developer tools and more advanced resource management improve productivity and governance. Step-by-step resources for distributed tracing, architecture, and automation help teams optimize operations. Other releases simplify integration, supplement security, and support hybrid/multi-cloud deployments for reliability and modernization.
Azure Functions Python Performance and Integration
Furthering last week’s improvements, Azure Functions Python adopts orjson for faster JSON handling. Serverless applications show reduced latency (by 40-50%) across HTTP/Event Hub/Service Bus triggers. Automated upgrades for Python strengthen high-throughput workloads, and advice is available for managing multi-version compatibility and validating production environments.
Advanced Cloud Observability: Distributed Tracing for Azure Microservices
A new guide on distributed tracing supports deeper monitoring, building on recent OpenTelemetry API integrations. Readers get best practices for trace propagation and improved correlation in Application Insights and KQL, helping technical teams achieve visibility and scalable monitoring.
Cloud Reliability: Load Testing in Azure Chaos Studio
Resilience and capacity planning continue with Azure Chaos Studio’s new guide for running live load tests, supporting real-time log monitoring. Instructions encourage effective autoscaling and retry analysis, following last week’s automation enhancements for Fabric and Azure.
Migration Preparedness: Azure Relay IP and DNS Changes
Building on last week’s hybrid management topics, the Azure Relay update provides migration scripts for upcoming IP and DNS changes. Features for updating firewall and allow lists improve cloud/hybrid infrastructure readiness, connecting with previous guidance on Fabric Managed Endpoints and Azure Arc security.
Fabric Platform: Real-Time Analytics, Data Engineering, and Community Highlights
Microsoft Fabric expands capabilities with the Eventhouse Endpoint, enabling real-time analytics on Lakehouse tables, schema sync, and simple dashboards using KQL/Python. Comparisons between virtualization and materialization reflect recent data engineering discussions, while enhanced dashboards add value for managing SQL resources.
Community highlights continue to bring attention to MVPs and new tutorials, sustaining last week’s momentum for practical platform empowerment.
- Unlock Real-Time Intelligence with the Eventhouse Endpoint for Lakehouse
- External Data Materialization Strategies in Fabric Data Warehouse
- Enhanced Performance Dashboard for SQL Databases in Microsoft Fabric
- Fabric Influencers Spotlight October 2025: Microsoft Fabric Community Highlights
Microsoft Fabric Data Engineering: Secure Connectivity and API Compatibility
Hybrid integration expands as Fabric introduces Managed Private Endpoints for safe Spark compute to on-premises and network-isolated databases, plus API support for allowlisting. OneLake APIs gain broader compatibility with Blob/ADLS protocols, supporting easier migration and integration in line with earlier API updates.
- Securely Accessing On-Premises Data with Microsoft Fabric Managed Private Endpoints
- OneLake APIs: Bring Your Apps and Build New Ones with Familiar Blob and ADLS APIs
Azure Resource Management and Automation
Automation for cloud resource management moves forward, highlighted by new Azure Resource Graph and PowerShell guides. Readers find patterns for batch queries and Skip Token pagination, helping teams manage large inventories and maintain better oversight.
Architecture Patterns and Decision Making
New guides for established architecture patterns and choices introduce reusable checklists and best practices, supporting teams in making reliable decisions and keeping solution builds consistent.
RabbitMQ Connector for Azure Logic Apps
Integration options improve with the public preview of RabbitMQ Connector for Logic Apps, offering capabilities for event-driven workflow including direct publishing, triggering, and queue management. These resources support automation patterns for hybrid deployment scenarios.
- Introducing the RabbitMQ Connector for Azure Logic Apps (Public Preview)
- Introducing RabbitMQ Connector for Azure Logic Apps (Public Preview)
Azure API Management: Native Service Bus Integration
Azure API Management now includes native Service Bus publishing with managed identities and RBAC, transforming API calls into Service Bus messages and supporting event-driven and decoupled architecture patterns.
Other Azure News
Recent releases span developer tool integration, operational guidance, and hybrid security. Updates for SSMS 22 improve both web and desktop SQL workloads, while live Azure Developer CLI sessions spotlight multi-agent orchestration and ongoing community support.
New security tools and hybrid features help administrators audit and enable Windows Recovery Environment on remote machines. Migration, cost management, and troubleshooting resources now include guides on Azure Storage Mover GA, Copy Job tutorials, and well-architected templates—furthering the theme of cost-effective modernization.
- SSMS 22 Meets Fabric Data Warehouse: Evolving the Developer Experiences
- AMA Spotlight: Build Smarter with Azure Developer CLI ‘AZD’
- Audit and Enable Windows Recovery Environment (WinRE) via Azure Arc Policies
- Securely Accessing On-Premises Data with Microsoft Fabric Managed Private Endpoints
- Fully Managed Cloud-to-Cloud Transfers with Azure Storage Mover
- Step-by-Step: Using Copy Job to Move Data Across Tenants in Fabric Data Factory
- Optimize Azure Local Deployments with the Well-Architected Review Assessment
- Understanding Azure Availability Zone Mappings for Subscriptions
- Azure Managed Redis Deep Dive
- Azure Pricing Calculator: Estimate Smarter, Plan Confidently
- Driving Change with Migration to Azure SQL Managed Instance
- Capacity Usage Now Enabled for Test Capability in Fabric User Data Functions
- Azure Weekly Update: Python 3.13 Functions, AKS Linux 3.0, Storage Mover, and More (24th October 2025)
Coding
Coding resources this week provide guides and new tools for smoother workflows, easier migration, and new hands-on experience. There’s a strong sense of continuity in the ecosystem, with changes to extension support, open source funding options, and game development help for C#, Godot, and distributed .NET caching. Tutorials span beginner-friendly introductions to advanced debugging and prototyping, assisting both new and experienced developers.
Godot Engine with .NET and C#
Picking up from last week’s .NET and workflow tutorials, this week the Godot C# Essentials series wraps up with tips for designing responsive UIs using Control Nodes, containers, and signals—useful for features like crafting or inventory screens. Fresh articles explain event-driven code, Area3D collisions, and how to use signals for input, broadening strategies for prototyping.
Additional material on CSG nodes assists with 3D game development. Beginners have access to thorough onboarding guides for installing Godot with .NET, setting up VS Code and key extensions, and adding GitHub version control—creating a smooth path to professional workflows.
Core guides reinforce onboarding, covering player controls, user interfaces, and C# scripting integration. Tutorials on scripting basics—input mapping, movement, lifecycle methods, inspector variables, and debugging in VS Code—reflect last week’s focus on tool improvement and step-by-step learning.
- Building Responsive UI in Godot C# with Control Nodes
- Interactions in Godot C#: Handling Player Input with Signals and Collision Detection
- Prototyping Game Environments in Godot C# with CSG Nodes
- Scenes and Nodes - The Core Building Blocks in Godot with C# (Part 4 of 9)
- Installing Godot with .NET and Setting Up VS Code for C# Game Development
- Introduction to Game Development with C# in Godot: Beginner Essentials
- Scripting Basics in Godot: Writing and Attaching C# Scripts (Part 5 of 9)
- Engine Overview: Navigating the Godot Editor with C# (Part 3 of 9)
- Debugging Godot C# Games with Visual Studio Code (Godot Series, Part 6)
.NET Ecosystem: Migration, Sponsorship, and Caching
Coming after last week’s .NET 10 RC2 and security updates, Visual Studio 2026 now introduces an improved compatibility model for easier extension migration. New API versioning helps extension developers reduce maintenance, progressing the workflow upgrade story.
NuGet.org launches a Sponsorship feature, allowing open source maintainers to share direct links to funding platforms—continuing discussion from last week about sustainability in the ecosystem.
Distributed caching in .NET gains a new option: Microsoft.Extensions.Caching.Postgres, which performs well and includes features like unlogged tables, supporting scalability and reliability in cloud applications as highlighted in previous updates.
- Effortless Extension Migration in Visual Studio 2026: Modern Compatibility Model for Developers
- Announcing Sponsorship on NuGet.org
- Postgres as a Distributed Cache Unlocks Speed and Simplicity for Modern .NET Workloads
ASP.NET Core Endpoint Management
Updates in security and routing include new guides on adding metadata to ASP.NET Core endpoints and managing fallback routes. These tutorials deliver practical examples and match ongoing recommendations for robust and secure platform development.
Other Coding News
Developer stories and DIY toolmaking continue from last week, highlighted by a GitHub Podcast discussing motivations for building custom utilities and Copilot’s role in supporting those efforts. The episode extends coverage on workflow personalization, toolchain improvement, and script development.
DevOps
DevOps topics this week center on AI-enhanced automation for observability, security, infrastructure management, and improved productivity. Key articles discuss cloud-native tools paired with AI features for log handling, automatic remediation, agile governance, and platform updates from GitHub for enterprise-scale workflows. swamUP 2025 sessions revisit changing DevOps metrics, encouraging responsible deployments and teamwork in hybrid infrastructure.
OpenTelemetry, AI, and Cost-Efficient Observability Architectures
Building on last week’s OpenTelemetry and observability coverage, AI’s role increases in log management, with better support for file, Kubernetes, and system journal logs in the OpenTelemetry Collector. New deployment options like Helm help teams standardize logging and adopt open architectures, moving away from vendor lock-in and toward scalable in-house databases.
Features like AI-driven log enrichment contribute real-time event grouping, anomaly detection, and improved root cause analysis. The Elastic Streams extension integrates AI normalization, supporting cross-signal visualization. The move to open standards and developer-friendly tools allows organizations to build cost-effective, flexible observability.
- OpenTelemetry and AI are Unlocking Logs as the Essential Signal for ‘Why’
- Open Cost-Efficient Architectures for Observability: Escaping Vendor Lock-In and Ballooning Costs
DevOps, AI Adoption, and Metrics Evolution
New DevOps metrics shift from speed alone to include trust and transparency. swamUP 2025 talks feature pipelines incorporating explainability and continuous safeguards, blending automation with solid governance and policy enforcement for responsible software delivery.
- The New Metrics of DevOps: Speed, Trust and Transparency
- How DevOps Is Evolving for the Age of Intelligent Automation
Automated Vulnerability Remediation and Nano Updates in DevOps
Security and remediation stay in focus with ActiveState’s vulnerability report, showing high costs of manual patching for open source. Automated patch platforms for smart CI/CD are recommended to lower risk and developer effort.
Small, targeted updates (“nano updates”) allow for secure system maintenance with minimal disruption, especially when paired with solid dependency management and container rebasing. Collaboration across security and engineering teams supports ongoing vulnerability response and continuous improvement.
- The Silent Technical Debt: Why Manual Remediation Is Costing You More Than You Think
- Why Nano Updates Only Work if You Begin with the Latest and Greatest Software
GitHub Enterprise Cloud: Governance, Security, and Organization Management
GitHub Enterprise Cloud adds new previews for centralized team and role management, introducing roles like Enterprise Security Manager and controls for code/secret scanning and Dependabot alerts. Admins gain abilities to manage permissions and compliance exceptions using APIs and the UI.
A preview for organization custom properties lets admins attach metadata and automate rules across organizations, improving compliance and reducing manual mistakes.
- Enterprise Teams Public Preview: Centralized Role and Security Management in GitHub Enterprise Cloud
- Streamlining Enterprise Governance with GitHub Organization Custom Properties
AI-Powered Code Quality and Analysis in DevOps
Building on MCP and prior code analysis, Opsera’s Hummingbird AI reviews code in CI/CD, surfacing insights into quality and productivity. Its recommendations, natural-language search, and system compatibility address compliance requirements for teams using several AI solutions.
SRE for AI and Hybrid Infrastructure
Site Reliability Engineering (SRE) now includes operations for GPU clusters, hybrid pipelines, and AI inference metrics. Automation and incident prediction tools support the changing reliability landscape for AI-specific workloads, including cost management and deployment across multiple clouds.
Hybrid Cloud and DevOps Workflows
More DevOps teams are moving workloads to private/hybrid clouds for greater control, data security, and cost oversight. Modern private clouds now support container orchestration, Infrastructure-as-Code, and microservices for easier automation and planning—improving budget management and reducing hidden IT risks.
Security
This week’s security updates highlight tools, incident reviews, and new practices for protecting cloud environments, supply chains, and agentic platforms. Ongoing analyses of vulnerabilities like Log4Shell are paired with stronger Azure and Microsoft defense options, including static analysis, access controls, and threat monitoring tools. Security automation and AI governance remain pressing topics.
Open Source Security, Vulnerability Response, and Developer Support
Log4Shell continues to be a central issue. Deep analysis shows the technical details of JNDI-based remote code execution in Log4j, with tips on mitigating open source dependencies: disabling risky settings, automating defense using Dependabot/code scanning, and using SBOMs. Maintainers describe the intensity of rapid incident response, making the case for better funding and community support via programs like Secure Open Source Fund and OpenSSF. Guides advise developers on proper dependency auditing and supply chain security.
A video interview with Log4j’s Christian Grobmeier adds perspective, sharing crisis details and team challenges. Topics covered include the importance of education, funding, trust, and governance, as well as the emerging relationship between AI and security. These resources offer meaningful insights for anyone facing zero-day exploits in open ecosystems.
- Inside the Log4Shell Breach: Lessons in Open Source Security and Sustainability
- The Untold Story of Log4j and Log4Shell: Inside the Crisis with Christian Grobmeier
Security Analysis and Automation in Enterprise Azure Workloads
Security for Azure workloads is explored through detailed attack chain analysis on Blob Storage. Recommended defenses include Zero Trust, role-based access controls (RBAC) via Entra ID, network isolation, encryption, and monitoring using Defender for Cloud and Sentinel SIEM. Step-by-step instructions for incident automation connect MITRE ATT&CK models with real remediation needs.
Agentic solution security guidance expands to include Key Vault management, strong RBAC, secret rotation, plugin isolation, and PII protection for agent endpoints and data resources. This builds on last week’s security best practices for agentic AI.
ContraForce/Microsoft collaboration pushes forward autonomous MDR workflows for startups and MSPs, using Azure AI Foundry and Sentinel/Defender integrations. These solutions offer automated monitoring and incident response, helping smaller teams develop secure operations.
- Mitigating Threat Activity Targeting Azure Blob Storage: Attack Chain Insights and Defenses
- Selecting the Right Agentic Solution on Azure – Security Deep Dive
- ContraForce and Microsoft: Enabling Autonomous Cybersecurity for Startups and MSPs
Security Engineering and Supply Chain Defense within the GitHub Ecosystem
GitHub’s security research moves forward through new Bug Bounty details and tips for detecting supply chain and injection vulnerabilities. The VIP program offers early access and feedback for active security researchers.
CodeQL v2.23.3 brings Rust security queries, improvements for Go, Java, Kotlin, and better C/C++ detection. These improvements assist teams in automating security analysis and mapping supply chain risks—helpful for Rust and C/C++ developers in particular.
- Inside the GitHub Bug Bounty Program: Researcher Insights and Security Advances
- CodeQL 2.23.3 Adds Rust Security Query, Rust Support, and Easier C/C++ Scanning
Identity, Authorization, and Platform Governance
Identity security is enhanced with the general availability of Defender for Identity’s unified sensors, combining signals from on-prem AD, Entra ID, and Okta. New APIs, improved alert accuracy, and more operational context strengthen monitoring and access management.
Fabric now supports row/column level security policies for Spark in OneLake, improving fine-grained data access alongside cluster protection—building on earlier broad workspace safeguards.
Live ASP.NET Community Standup sessions explain MCP authorization flows for .NET/ASP.NET Core, giving actionable integration and troubleshooting steps.
Cycode’s new ASPM previews provide dev teams automated AI/ML inventory and MCP/LLM detection, adopting the concept of AI BOM (Bill of Materials)—similar to SBOM—for software traceability and policy controls.
Microsoft Security Store enters public preview, unifying security software provisioning for Microsoft and partners, with direct billing and compliance mapping. This supports simplified, automated setup for security and compliance teams.
- Harden Your Identity Defense with Microsoft Defender and Entra: Enhanced ITDR and Unified Insights
- Implementing Row and Column Level Security for Spark in OneLake
- ASP.NET Community Standup: Understanding the MCP Authorization Flow
- Cycode Unveils AI Tool and Platform Detection for Application Security Teams
- The New Microsoft Security Store: Unifying Partners and Innovation for Stronger Security