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Veera Ravindra Divi is a principal software engineer, independent researcher, and IEEE-published author specializing in agentic AI, distributed systems, and B2B commerce. With 11+ years of industry experience, he has developed trading systems, AI platforms, and marketplace solutions at Wells Fargo and Amazon. His research focuses on AI interoperability, enterprise procurement, supply chain optimization, and resilient, scalable software systems.

Stop Treating GPUs Like Web Pods

Stop Treating GPUs Like Web Pods

Kubernetes schedules accelerators as opaque integers, and your bill pays for it. Share the silicon, scale on the right signal and keep weights out of the image ...
Veera Ravindra Divi | August 12, 2026 | AI infrastructure, AI serving, autoscaling, cloud costs, cloud native AI, DCGM exporter, DRA, Dynamic Resource Allocation, GPU costs, GPU scheduling, GPU sharing, GPU utilization, GPUs, inference workloads, KEDA, kubernetes, Kubernetes GPU scheduling, LLM Inference, MIG, model weights, MPS, NVIDIA GPUs, NVIDIA MIG, Prometheus, scale-to-zero, time-slicing
Self-Healing Kubernetes

Self-Healing Kubernetes Gets Real—and Risky: Running AI Agents on Amazon EKS

For years, “self-healing Kubernetes” meant a liveness probe restarting a crashed pod. In 2026 it means something far more literal: an autonomous agent that reads your cluster’s logs and metrics, forms a ...
Veera Ravindra Divi | July 7, 2026 | AI agents, AIOps, Amazon EKS, cloud security, kubernetes, MCP

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The Economics of Infrastructure Modernization
4 November 2026
The Economics of Infrastructure Modernization
The AI-Powered Modernization Playbook for Financial Services Secure Migration, Modernization & the AI-Driven Development Lifecycle
14 October 2026
The AI-Powered Modernization Playbook for Financial Services Secure Migration, Modernization & the AI-Driven Development Lifecycle

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Practitioner Perspective: Achieving Fine-Grained Control for Data and AI on the Endpoint
20 October 2026
Practitioner Perspective: Achieving Fine-Grained Control for Data and AI on the Endpoint

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Kubernetes Did Not Miss the AI Wave. It Absorbed It

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Komodor Extends AI SRE Reach for Kubernetes to AI Agents

September 17, 2026

Manifestly Safer, Why Kubernetes Wants Developers to Speak KYAML

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Karmada Federated Control Plane for Kubernetes Achieves CNCF Graduation

September 24, 2026

CloudBolt Adds Ability to Optimize GPU Consumption by Kubernetes Workload

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Cloud Observability Is More Than a Cloud-Native Story

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