Engineering secure cloud platforms, automating infrastructure, strengthening CI/CD pipelines, and exploring AI-powered DevSecOps workflows.
I'm a DevSecOps Engineer with 3.5+ years of experience in designing, automating, securing, and managing modern cloud infrastructure.
My engineering experience spans Microsoft Azure, AWS, Infrastructure as Code, CI/CD automation, containerization, Kubernetes, cloud networking, identity & access management, monitoring, security automation, and Linux.
Alongside traditional DevOps and cloud engineering, I work with and explore Artificial Intelligence, Generative AI, Large Language Models (LLMs), Model Context Protocol (MCP), AI coding assistants, and Antigravity for infrastructure analysis, CI/CD troubleshooting, scripting, documentation, automation, and developer productivity.
Automate infrastructure. Integrate security. Observe everything. Use AI intelligently.
☁️ Cloud: Azure • AWS • GCP
🏗️ Infrastructure as Code: Terraform • HCL • Modules • Remote State
• Workspaces
🛡️ DevSecOps: Secure CI/CD • SAST • Secret Scanning • Vulnerability
Detection • Security Automation
🔄 CI/CD: Azure DevOps • GitHub Actions • YAML Pipelines
🐳 Containers: Docker • ACR • ECR
☸️ Orchestration: Kubernetes • AKS • EKS • GKE
🐧 Operating Systems: Linux Administration
⚙️ Automation: Python • Bash • PowerShell
🌐 Networking: VNet • VPC • Subnets • NSG • Load Balancers • VPN •
DNS • Hub-Spoke
🔐 Identity & Security: Entra ID • IAM • RBAC • OAuth 2.0 • Managed
Identity • Key Vault
📊 Observability: Prometheus • Grafana • Azure Monitor • CloudWatch
• CloudTrail
🤖 AI Engineering: Generative AI • LLMs • Prompt Engineering •
AI-Assisted DevOps
🔌 AI Integration: MCP • LLM Tool Integration • AI Coding Assistants
• Antigravity
I believe security should be integrated into every stage of the software delivery lifecycle rather than added after deployment.
- 🔐 Secure CI/CD pipeline design
- 🔍 Infrastructure security scanning
- 🛡️ SAST integration
- 🔑 Secret detection
- 🚨 Vulnerability detection
- ⚙️ Security automation
- 👤 IAM and RBAC
- 🔒 OAuth 2.0
- 🔐 Secrets management
- ☁️ Cloud security controls
- 📋 Security and compliance practices
- 🎯 Least-privilege access
- 🏗️ Secure Infrastructure as Code
CODE
│
▼
BUILD
│
▼
TEST
│
▼
SECURITY SCAN
│
├── SAST
├── Secret Detection
├── Vulnerability Detection
└── IaC Security
│
▼
DEPLOY
│
▼
MONITOR
│
▼
AI-ASSISTED ANALYSIS
│
▼
IMPROVE
One of my key areas of interest is the intersection of Cloud + DevSecOps + Artificial Intelligence.
I use and explore LLM-assisted workflows to support:
- 🧠 Infrastructure configuration analysis
- 🏗️ Terraform configuration review
- 🔄 CI/CD troubleshooting
- 📝 YAML pipeline assistance
- 🐍 Python/Bash/PowerShell scripting assistance
- 📚 Technical documentation
- 🔍 Deployment issue analysis
- ⚙️ Repetitive task automation
- 🛡️ DevSecOps workflow analysis
- 💡 Developer productivity
The objective is to use AI as an engineering accelerator while keeping engineering judgment at the center.
┌──────────────────┐
│ AI / LLM │
└────────┬─────────┘
│
┌────────────────┼────────────────┐
│ │ │
▼ ▼ ▼
Terraform CI/CD Kubernetes
Analysis Troubleshooting Analysis
│ │ │
└────────────────┼────────────────┘
│
▼
DevOps Automation
│
▼
Cloud Infrastructure
LLM-assisted troubleshooting • Infrastructure analysis •
Pipeline analysis • Configuration assistance •
Documentation automation • Operational automation •
AI-assisted security analysis
I'm particularly interested in Model Context Protocol (MCP) and its potential role in connecting AI/LLM systems with engineering tools and DevOps workflows.
┌──────────────┐
│ Engineer │
└──────┬───────┘
│
▼
┌──────────────┐
│ AI / LLM │
└──────┬───────┘
│
▼
┌──────────────┐
│ MCP │
└──────┬───────┘
│
┌────────────────────┼────────────────────┐
│ │ │
▼ ▼ ▼
Terraform GitHub CI/CD
│ │ │
▼ ▼ ▼
Infrastructure Source Code Pipelines
│ │ │
└────────────────────┼────────────────────┘
│
▼
DevSecOps Automation
- LLM-to-tool integration
- Context-aware DevOps assistance
- Infrastructure analysis
- CI/CD workflow interaction
- Engineering automation
- AI-assisted troubleshooting
- Developer productivity
I explore Antigravity and AI coding assistants as part of modern AI-assisted engineering workflows.
- Infrastructure development
- Terraform assistance
- DevOps scripting
- YAML pipeline development
- Troubleshooting
- Documentation
- Repository analysis
- Automation workflows
- Developer productivity
AI ENGINEERING
│
┌───────────┼───────────┐
│ │ │
▼ ▼ ▼
LLM MCP Antigravity
│ │ │
└───────────┼───────────┘
│
▼
AI-Assisted DevOps
│
┌───────────────┼───────────────┐
▼ ▼ ▼
Terraform CI/CD Kubernetes
│ │ │
└───────────────┼───────────────┘
│
▼
DevSecOps
│
▼
Azure / AWS / GCP
Virtual Machines • VNet • Subnets • NSG • Load Balancer •
App Services • Azure SQL • Storage Account • Key Vault •
Bastion • Azure Firewall • Azure Monitor • Log Analytics •
Application Insights • Entra ID • RBAC • Azure Policy •
Defender for Cloud • ACR • Azure DevOps • Azure CLI
EC2 • VPC • Subnets • Security Groups • NAT Gateway •
Internet Gateway • ALB • ELB • Auto Scaling • S3 • RDS •
EBS • ECR • IAM • KMS • Secrets Manager • Route 53 •
CloudWatch • CloudTrail • Lambda • EKS • AWS CLI
Compute Engine • GKE • VPC • Subnets • Firewall Rules •
Cloud Load Balancing • Cloud NAT • Cloud Router • Cloud Storage
• Cloud SQL • Artifact Registry • IAM • Service Accounts •
Secret Manager • Cloud DNS • Cloud Monitoring • Cloud Logging •
Cloud Audit Logs • Cloud Functions
Terraform is one of the core technologies in my cloud engineering stack.
- Terraform HCL
- Providers
- Resources
- Variables & Outputs
- Data Sources
- Terraform Modules
- Reusable Infrastructure
- Remote Backend
- State Management
- State Locking
- Terraform Workspaces
- Resource Dependencies
- Multi-environment Infrastructure
- Infrastructure Automation
Terraform
│
┌─────────────┼─────────────┐
│ │ │
▼ ▼ ▼
Azure AWS GCP
│ │ │
└─────────────┼─────────────┘
│
▼
Automated Infrastructure
- Docker Images & Containers
- Dockerfile
- Docker Compose
- Container Networking
- Container Volumes
- Image Management
- Container Registries
- Azure Container Registry
- Amazon ECR
- Containerized application deployment
Application → Dockerfile → Docker Image → Container Registry → Kubernetes
Pods • Deployments • Services • ConfigMaps • Secrets •
Namespaces • Ingress • Persistent Volumes • RBAC •
Horizontal Pod Autoscaling • Rolling Updates
☁️ Azure → AKS
☁️ AWS → EKS
☁️ GCP → GKE
- Linux administration
- Bash scripting
- File and permission management
- Process management
- Service management
- Networking & troubleshooting
- Automation
- Nginx
- Apache
- Git
- GitHub
- GitHub Actions
- Repository Management
- Branching Strategies
- Pull Requests
- Version Control
- CI/CD Integration
- Infrastructure Repositories
- YAML Workflows
Developer → Git → GitHub → GitHub Actions
│
┌────────────┼────────────┐
▼ ▼ ▼
Build Security Deploy
│ │ │
└────────────┼────────────┘
▼
Cloud / Kubernetes
Azure DevOps + GitHub Actions + YAML
SOURCE CODE
│
▼
BUILD
│
▼
TEST
│
▼
SECURITY CHECK
│
▼
TERRAFORM / CONTAINER BUILD
│
▼
DEPLOY
│
▼
DEV / QA / UAT / PRODUCTION
VNet / VPC • Public & Private Subnets • Routing •
NSG / Security Groups • Firewall Rules • Load Balancers •
NAT Gateway • VPN • DNS • VNet / VPC Peering •
Hub-and-Spoke Architecture • Hybrid Connectivity •
Cloud Network Security
Azure: Microsoft Entra ID • RBAC • Managed Identity •
Key Vault
AWS: IAM • KMS • Secrets Manager
GCP: IAM • Service Accounts • Secret Manager
Additional focus: OAuth 2.0 • Least Privilege • Secrets Management
• Azure Policy • Microsoft Defender for Cloud
Azure: Azure Monitor • Log Analytics • Application Insights
AWS: CloudWatch • CloudTrail
GCP: Cloud Monitoring • Cloud Logging • Cloud Audit Logs
Open Source: Prometheus • Grafana
Applications + Infrastructure
│
▼
Metrics / Logs
│
▼
Monitoring Stack
│
▼
Alerts & Dashboards
│
▼
Troubleshooting
│
▼
AI-Assisted Analysis
KRISHNA SHARMA
│
▼
DEVSECOPS
│
┌──────────────────┼──────────────────┐
│ │ │
▼ ▼ ▼
CLOUD IaC CI/CD
│ │ │
Azure AWS GCP Terraform GitHub Actions
│ │
└──────────────────┬──────────────────┘
│
▼
Docker + Kubernetes
│
▼
Linux
│
▼
Security + IAM
│
▼
Monitoring / Logging
│
▼
AI + LLM
│
┌──────┴──────┐
▼ ▼
MCP Antigravity
│ │
└──────┬──────┘
▼
AI-Powered DevSecOps
- ☁️ Multi-Cloud Engineering --- Azure • AWS • GCP
- 🏗️ Terraform & Infrastructure as Code
- 🛡️ DevSecOps & Security Automation
- 🔄 Azure DevOps & GitHub Actions
- 🐳 Docker & Containerization
- ☸️ Kubernetes --- AKS • EKS • GKE
- 🐧 Linux & Automation
- 🐙 Git & GitHub
- 📊 Monitoring & Observability
- 🤖 Generative AI & AI-Assisted DevOps
- 🧠 Large Language Models
- 🔌 Model Context Protocol
- 🚀 Antigravity & AI-Assisted Engineering
CLOUD
↓
DEVOPS
↓
DEVSECOPS
↓
INFRASTRUCTURE AS CODE
↓
DOCKER + KUBERNETES
↓
CLOUD-NATIVE DEVOPS
↓
AI + LLM
↓
MCP
↓
ANTIGRAVITY
↓
AI-POWERED DEVSECOPS
↓
INTELLIGENT CLOUD AUTOMATION
Build infrastructure that can evolve with application requirements.
If a process is repeatable, look for opportunities to automate it.
Integrate security into infrastructure and delivery pipelines.
Reliable systems require visibility into infrastructure and applications.
Apply AI where it can improve analysis, automation, troubleshooting, documentation, and productivity while keeping engineering judgment at the center.
DevSecOps Engineer | Cloud & AI Automation
📧 Email: krishna.sharma.cloud.ops@gmail.com
💻 GitHub: krishnasharma-cloudops
🔗 LinkedIn: Krishna Sharma
::: {align="center"}
Automate → Secure → Deploy → Observe → Analyze → Improve
⭐ Always Learning • Always Automating • Always Improving :::