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I'm a software engineering leader with over 14 years of experience delivering full-stack, cloud-native, and AI-powered enterprise applications. My technical expertise spans JavaScript frameworks (Angular, React, Node.js), backend systems with Spring Boot, and a strong focus on DevOps practices—ranging from CI/CD pipelines, Docker and Kubernetes, infrastructure as code, to performance optimization and monitoring at scale. I've led teams in architecting resilient systems, automating deployment workflows, and scaling platforms across hybrid environments. I regularly write about DevOps, cloud engineering, and modern software architecture, with published articles on SitePoint, DZone, Hackernoon, Medium, and Dev.to. My posts often blend hands-on experience with real-world challenges—covering topics like container orchestration, environment automation, testing strategies with Cypress, and AWS-based deployments. I’m passionate about sharing knowledge, mentoring teams, and driving engineering excellence across the stack.

SRE, autoscaling, Tailscale, Kubernetes, argo cd, Kubernetes v1.33,  AI, Nelm, Kubernetes, architecture, , architecture, Rackspace, GPUs, Kubernetes, Solo.io Kubernetes cloud foundry keptn cloud-native automation

Unleashing the Power of Argo CD by Streamlining Kubernetes Deployments

There are many CD tools for Kubernetes on the market, but the popular ones include Argo CD, Flux CD, Jenkins X and GitHub Actions ...
Raju Dandigam | July 1, 2025 | ArgoCD, devops, kubernetes

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You Can’t Just Layer AI on Your Observability Platform: Why Context is King
19 May 2026
You Can’t Just Layer AI on Your Observability Platform: Why Context is King
AppSec in 2026: Security at Machine Speed — or Not at All
18 May 2026
AppSec in 2026: Security at Machine Speed — or Not at All
Multi-Million-Dollar Lessons: What FinOps Maturity Actually Looks Like
14 May 2026
Multi-Million-Dollar Lessons: What FinOps Maturity Actually Looks Like
From Prompt to Exploit: How LLMs Are Changing API Attacks
13 May 2026
From Prompt to Exploit: How LLMs Are Changing API Attacks
Data is the Differentiator for Exposure Management
6 May 2026
Data is the Differentiator for Exposure Management
The Context Engine: Why Consolidation is the Natural Future of AppSec
5 May 2026
The Context Engine: Why Consolidation is the Natural Future of AppSec

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ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

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SUSE Rancher Prime Throws a Lasso Around VM and Container Management

March 26, 2026

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March 24, 2026

Docker Inc. Allies with NanoCo to Deploy General-Purpose AI Agent Safely

April 1, 2026

Kubernetes Builds a Sandbox CRD for AI Agents

March 25, 2026

Istio Weaves ‘Future-Ready’ Service Mesh for AI 

March 27, 2026

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AI in CI/CD: Where Are You Really?

Step 1 of 7

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How would you describe your organization’s current level of AI adoption within your CI/CD pipeline?(Required)
How would you describe your current CI/CD environment?(Required)
In which areas of your software delivery pipeline are you currently using AI? (Select all that apply)(Required)
In which areas of your software delivery pipeline are you considering using AI? (Select all that apply)(Required)
Which AI use cases are delivering, or do you expect to deliver, measurable value in your CI/CD pipeline? (Select up to three)(Required)
What, if anything, is limiting your organization’s progress with AI in CI/CD? (Select up to three)(Required)
How do you expect your use of AI in CI/CD pipelines to change over the next 12–18 months?(Required)

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