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Naga Santhosh Reddy Vootukuri, a seasoned professional with over 16+ years working at Microsoft, reflects on his journey from India to the USA. Graduating from Sreenidhi Institute of Science and Technology in 2008, he now serves as a Principal Software Engineering Manager for Azure SQL. His role involves leading his team through software development cycles, ensuring successful product launches. Currently, Naga focuses on a significant initiative in Azure SQL Deployment, emphasizing high availability for SQL customers during feature rollouts. Previously, he managed Master Data Services (MDS) within SQL Server, gaining community connections and contributing actively to Microsoft forums. Currently his focus is mainly on AI LLM's and he shares his knowledge through detailed articles. Aside from technical responsibilities, Naga engages in Microsoft hackathons and mentors junior engineers, finding fulfillment in guiding their career paths. He also champions diversity and inclusion, advocating for equality within the tech industry. Naga sees himself not only as a technical leader but also as a catalyst for positive change at Microsoft.

CNCF, cloud native, NVIDIA, AI, Peritus microservices

Building AI Agents Using Open-Source Docker cagent and GitHub Models 

Discover how Docker’s open-source cagent framework and GitHub Models simplify AI agent orchestration. Learn to build, package, and share a vendor-neutral podcast-generation AI system with production-grade quality and cost efficiency ...
Naga Santhosh Reddy Vootukuri | January 6, 2026 | AI agent orchestration, AI agent runtime, AI development workflows, AI vendor lock-in, cagent framework, containerized AI agents, Docker AI framework, Docker cagent, Docker Hub AI agents, GitHub Models, MCP tools, Model Context Protocol, multi-agent AI systems, OpenAI compatible API, podcast generation AI, production AI agents, vendor-neutral AI, YAML-based AI configuration
cloud-native Gartner

Enabling Efficient AI Workloads in Cloud-Native Development using Docker Offload

Docker Offload brings cloud scalability to local development, enabling AI and ML workloads to run on GPU-powered cloud infrastructure seamlessly ...
Naga Santhosh Reddy Vootukuri | October 8, 2025 | AI Workloads, cloud compute, cloud infrastructure, cloud native AI, cloud offloading, cloud-native development, container builds, container orchestration, developer productivity, DevOps tools, Docker GPU, Docker Offload, GPU acceleration, hybrid workflows, local development, managed service, ML workloads, secure containers, SSH tunnel, VDI environments, virtualization

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From Experimentation to Production: Why Inference Is the Defining Layer of AI
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Beyond Embedded! RISC-V in the Performance CPU segment
27 May 2026
AI in DevOps: Vendor Promise vs. Enterprise Reality
21 May 2026
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35 Million Lines, Zero Build-Breakers: How Adyen Scaled DevSecOps
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18 June 2026
How to Conduct AI-Native Bug Discovery & Triage
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Intruder Adds Container Image Scanning to Cloud Security Platform

April 14, 2026

Kubernetes v1.36 Promotes Stability, Compatibility & Reproducibility

April 22, 2026

Report: Utilization of Kubernetes Infrastructure Remains Abysmal

April 21, 2026

AWS Drives Kubernetes Simplification With EKS Hybrid Nodes Gateway

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Solo.io Extends kagent Runtime to NemoClaw Governance Framework for AI Agents

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