Shubh Dixit | DevOps Engineer

Skills

☁️ Cloud Platforms

Designing and managing infrastructure across Azure and AWS with a focus on scalability, security, and cost-aware resource usage.

Tools: Microsoft Azure (AKS, Virtual Machines, Resource Groups, App Services, Azure Pipelines), AWS (EC2, S3, EKS)
🌐 Azure Networking

Provisioning and securing production network infrastructure to route and protect application traffic.

Tools: Virtual Network (VNet), Network Security Groups (NSG), Load Balancer, NAT Gateway, Application Gateway, VPN Gateway, Peering
🐳 Containers & Orchestration

Packaging applications into containers and orchestrating them at scale with Kubernetes for consistent, resilient deployments.

Tools: Docker, Kubernetes (AKS/EKS), Horizontal Pod Autoscaling (HPA), Ingress Controllers
🏗️ Infrastructure as Code

Building reusable, modular infrastructure definitions for repeatable, environment-parity provisioning.

Tools: Terraform (Modules, for_each, dynamic blocks, remote state, workspaces, variables/outputs), Ansible
🔁 CI/CD & Version Control

Building automated pipelines and deployment strategies to streamline build, test, and release workflows.

Tools: GitHub Actions, Azure DevOps Pipelines, Git/GitHub, Blue-Green & Canary Deployments, GitOps practices
🧰 Automation & Scripting

Writing scripts and tooling that reduce repetitive work and eliminate manual operational toil.

Tools: Python, Bash/Shell Scripting, PowerShell
📊 Observability & Monitoring

Implementing monitoring, alerting, and dashboards to observe system health and sustain high uptime.

Tools: Prometheus, Grafana, Azure Monitor, AWS CloudWatch, Custom Alerting & Dashboards
🖥️ OS, Networking & Security

Administering Linux systems and applying core networking and security practices in production environments.

Tools: Linux Administration (Ubuntu, RHEL), TCP/IP, DNS, RBAC, IAM, Security Scanning, Secrets Management
Unlocking new skill...

Always sharpening the stack. Check back soon for what's next.

Professional Experience

HCL Technologies — Lucknow, India

Oct 2024 — Present

DevOps Automation Engineer (Senior Analyst)

Architected robust CI/CD pipelines using GitHub Actions and Azure DevOps to automate the microservices lifecycle, reducing deployment lead time by 40%
Managed container orchestration on Azure Kubernetes Service (AKS) and AWS EKS; implemented Horizontal Pod Autoscaling (HPA) and Ingress controllers to optimize resource utilization
Designed and provisioned Azure network infrastructure including VNets, NSGs, Load Balancers, NAT Gateways, and Application Gateways to secure and route production traffic
Built reusable Terraform modules using for_each loops and dynamic blocks for multi-cloud infrastructure provisioning, ensuring environment parity across Dev, Staging, and Production
Established an enterprise observability stack using Prometheus and Grafana; created custom alerting rules and dashboards to monitor cluster health and application latency
Led Docker-based containerization strategy with multi-stage builds, optimizing image size and integrating security scanning into the CI/CD pipeline
Provided L1 production support and performed Root Cause Analysis (RCA) for infrastructure incidents, maintaining 99.9% uptime for business-critical applications

Feb 2023 — Sept 2024

Analyst – Infrastructure Support

Automated repetitive system administration tasks, log rotations, and daily health checks using Bash and Shell scripting, reducing manual operational effort by 25%
Monitored and debugged complex application incidents using Linux CLI tools (grep, awk, sed, top) and log analysis to ensure minimal downtime
Supported deployment validation and post-release monitoring using Azure Monitor and AWS CloudWatch, ensuring stable production rollouts
Implemented automated backup scripts using Shell scripting to ensure data integrity and disaster recovery readiness

Projects

🚀 End-to-End AKS Orchestration

Problem

Manual deployments were time-consuming, error-prone, and inconsistent across environments, making it difficult to deploy and manage microservices reliably.

Architecture / Approach

Deployed a scalable microservices architecture on Azure Kubernetes Service (AKS) using Helm for package management and Prometheus for monitoring.

Implementation

Configured GitHub Actions and Azure DevOps workflows to trigger on code changes
Built and validated Docker images with multi-stage builds automatically
Deployed services to AKS with Helm charts and Ingress controllers
Implemented Horizontal Pod Autoscaling (HPA) for dynamic resource utilization

Challenges Faced

Managing secrets securely in CI/CD pipelines
Ensuring consistent Docker builds and image sizes
Handling deployment failures during pipeline execution

Outcome / Impact

Reduced deployment lead time by 40%
Improved deployment consistency and resource utilization
Enabled faster feedback and iteration during development

Tools Used: GitHub Actions, Azure DevOps, AKS, Helm, Docker, Prometheus

☁️ Hybrid Cloud Infrastructure as Code with Terraform

Problem

Manually configuring infrastructure across multiple clouds led to configuration drift and inconsistent environments.

Architecture / Approach

Provisioned secure Azure VNets and AWS VPCs from a single modular Terraform codebase using for_each loops and reusable modules.

Implementation

Built reusable Terraform modules with for_each loops and dynamic blocks
Configured remote state and workspaces for multi-environment provisioning
Automated network provisioning (VNets, NSGs, VPCs) across clouds

Challenges Faced

Designing reusable modules that work across Azure and AWS
Managing state consistency across environments

Outcome / Impact

Consistent infrastructure configurations across clouds
Reduced provisioning time
Improved environment parity across Dev, Staging, and Production

Tools Used: Terraform, Azure, AWS, Ansible

🔄 Zero-Downtime Deployment Strategy

Problem

Feature releases risked downtime and inconsistent rollouts, impacting availability of business-critical applications.

Architecture / Approach

Configured Blue-Green and Canary deployment strategies in Azure DevOps to ensure high availability during releases.

Implementation

Set up Blue-Green deployment pipelines in Azure DevOps
Implemented Canary release strategies with gradual traffic shifting
Integrated GitOps practices for declarative, auditable deployments

Challenges Faced

Coordinating traffic shifting without service disruption
Automating rollback on failed health checks

Outcome / Impact

Zero-downtime releases for business-critical applications
Maintained 99.9% uptime
Faster, safer feature rollouts

Tools Used: Azure DevOps, Kubernetes, GitOps

📊 Enterprise Observability Stack

Problem

Lack of unified monitoring made it difficult to detect performance issues or failures early across a growing Kubernetes footprint.

Architecture / Approach

Established an observability stack using Prometheus and Grafana, complemented by Azure Monitor and AWS CloudWatch, to observe system health and respond proactively.

Implementation

Deployed Prometheus for metrics collection across AKS/EKS clusters
Built custom Grafana dashboards for cluster health and application latency
Created alerting rules with meaningful thresholds to reduce noise

Challenges Faced

Choosing meaningful alert thresholds
Avoiding alert noise across multiple services

Outcome / Impact

Improved system visibility and faster incident detection
Sustained 99.9% uptime for business-critical applications
Better understanding of application behavior under load

Tools Used: Prometheus, Grafana, Azure Monitor, AWS CloudWatch, AKS, EKS

About Me

Skills

☁️ Cloud Platforms

🌐 Azure Networking

🐳 Containers & Orchestration

🏗️ Infrastructure as Code

🔁 CI/CD & Version Control

🧰 Automation & Scripting

📊 Observability & Monitoring

🖥️ OS, Networking & Security

Unlocking new skill...

Professional Experience

DevOps Automation Engineer (Senior Analyst)

Analyst – Infrastructure Support

Projects

🚀 End-to-End AKS Orchestration

Problem

Architecture / Approach

Implementation

Challenges Faced

Outcome / Impact

☁️ Hybrid Cloud Infrastructure as Code with Terraform

Problem

Architecture / Approach

Implementation

Challenges Faced

Outcome / Impact

🔄 Zero-Downtime Deployment Strategy

Problem

Architecture / Approach

Implementation

Challenges Faced

Outcome / Impact

📊 Enterprise Observability Stack

Problem

Architecture / Approach

Implementation

Challenges Faced

Outcome / Impact

Currently Learning

Education

Bachelor of Computer Applications (BCA)

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