AWS SYSTEM · LIVE DEPLOYMENT
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REGION: us-east-1
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VISITOR:

RAHUL PATEL

Cloud DevOps AWS Automation

Cloud & DevOps Engineer building reliable infrastructure, automating deployments, and architecting scalable solutions on AWS. Passionate about serverless, infrastructure as code, and continuous delivery.


About Me

Mission Profile & Engineering Focus

Cloud & DevOps Engineer specializing in scalable AWS cloud infrastructure, serverless architectures, and declarative automation.

Currently working at NICE in Pune, India, focusing on cloud-native solutions, serverless backends, and CI/CD pipelines. Passionate about automating repetitive workflows, eliminating manual toil, and architecting resilient systems on AWS.

Previously at Tata Consultancy Services, I designed and implemented event-driven microservices with AWS Lambda, DynamoDB, and API Gateway, provisioned multi-tier infrastructure declaratively using Terraform, and built automated release pipelines with Azure DevOps and GitHub Actions.

Location
Pune, India
Experience
5+ Years
Primary Cloud
Amazon Web Services
Core Specialization
Serverless & IaC
Current Status
Active
Infrastructure State
Live Production

System Architecture

"You're currently looking at a website running on AWS."

Website Delivery
CloudFront + S3
Static Asset Delivery
Visitor Counter API
API Gateway + Lambda
REST Endpoint & Compute
Visitor Database
DynamoDB
Atomic State Store
Delivery
GitHub Actions
Automated CI/CD Pipeline
Infrastructure
Terraform
Declarative IaC
Visitor Counter
API-backed
Mission Architecture & Request Flows
End-to-end cloud infrastructure powering this domain and visitor counter.
⚡ Click any component to inspect technical architecture
Request / Data Flow
Runtime Path
Deployment / Infrastructure Relationship
Flow 01 · Frontend Delivery Visitor → Route 53 → CloudFront → S3 → Static Frontend
Flow 02 · Visitor Counter Visitor → API Gateway → AWS Lambda → DynamoDB
Engineering & Deployment Architecture Decoupled from runtime request paths · Declarative IaC & GitOps Delivery
Amazon CloudFront
Global CDN & TLS Termination
Purpose
Global content delivery layer used to distribute the static frontend through AWS edge locations.
Engineering Rationale (Why Chosen)
CloudFront distributes cached content through edge locations, reducing the distance between users and the origin, while keeping the S3 origin private via Origin Access Control (OAC) with built-in AWS Shield Standard DDoS mitigation.
Configuration Specs: Origin: S3 via Origin Access Control (OAC) | Protocol: HTTPS Redirect | Cache Policy: Managed-CachingOptimized | Compression: Gzip/Brotli | TLS: 1.3

Architectural Rationale & Trade-Offs

Architectural justifications, alternatives evaluated, and production trade-offs.

Decision 01 // Compute Tier

Why Serverless Architecture?

Production Architecture
Chosen Because

Serverless services avoid always-on compute infrastructure and fit the low and variable traffic profile of this portfolio. Automatically scales with incoming request volume without provisioning virtual machines or managing operating system patching.

Alternatives Considered

Single EC2 instance or ECS Fargate container. Always-on compute introduces ongoing infrastructure management and idle resource costs, which are unnecessary for the low and variable traffic profile of this portfolio.

Trade-Off & Mitigation

Serverless introduces cold-start considerations. The Lambda function is intentionally kept lightweight with a minimal Python execution path.

Decision 02 // Edge Tier

Why CloudFront Edge CDN?

Production Architecture
Chosen Because

Keeps the S3 origin bucket private via Origin Access Control (OAC). Terminates TLS 1.3 at edge locations and distributes cached content through edge locations, reducing the distance between users and the origin, with built-in AWS Shield Standard DDoS mitigation.

Alternatives Considered

Direct S3 Static Website Hosting. Rejected because S3 web endpoints do not support custom domain SSL/TLS certificates natively and require public read bucket access.

Trade-Off & Mitigation

Cached content propagation delay on updates. Mitigated by automated CI/CD cache invalidation (/*) via GitHub Actions, which reduces stale-cache time by triggering CloudFront invalidation as part of deployment.

Decision 03 // Orchestration

Why Declarative Terraform?

Production Architecture
Chosen Because

Explicit state-driven infrastructure as code. Enables deterministic preview (terraform plan), full auditability, automated resource teardown/recreation, and version-controlled history in Git.

Alternatives Considered

AWS Management Console (ClickOps) or AWS SAM. Console lacks repeatability; SAM is specialized for Lambda but less flexible for managing multi-region ACM certs and Route 53 zones together.

Trade-Off & Mitigation

State file management and locking complexity. Mitigated by storing remote state in S3 with DynamoDB state locking to prevent concurrent modifications.

Decision 04 // State Store

Why DynamoDB NoSQL?

Production Architecture
Chosen Because

Supports atomic counter updates (UpdateItem with ADD visitor_count :inc), handling concurrent requests without requiring application-level mutexes or external database locks.

Alternatives Considered

Amazon RDS (PostgreSQL/MySQL). Rejected because relational databases require VPC networking, connection pooling management, and ongoing minimum compute charges.

Trade-Off & Mitigation

Limited query capability compared to SQL, but well-suited since the visitor counter data model requires only single-key lookups and atomic updates.

Decision 05 // CI/CD Pipeline

Why GitHub Actions CI/CD?

Production Architecture
Chosen Because

Seamless native repository integration without requiring self-hosted infrastructure. Automatically syncs frontend builds to S3 and triggers CloudFront cache invalidation upon push to main.

Alternatives Considered

AWS CodePipeline / CodeBuild or manual AWS CLI uploads. AWS CodePipeline introduces excess console switching and configuration overhead for lightweight static assets.

Trade-Off & Mitigation

Dependency on GitHub runner uptime. Mitigated by storing standard AWS CLI deployment scripts that can execute locally with one command if needed.


Flagship Cloud Architectures

Production cloud architectures, serverless backends, and automated deployment pipelines.

MISSION CRC-001 OPERATIONAL · LIVE PRODUCTION

Cloud Resume Challenge — AWS Serverless Architecture

Architected and deployed a serverless web application and AWS-backed visitor counter on Amazon Web Services. Infrastructure provisioned declaratively via Terraform, featuring edge CDN distribution with CloudFront, private S3 storage via Origin Access Control, serverless Python Lambda compute, and continuous deployment through GitHub Actions.

EDGE LATENCY < 35ms
STATE INTEGRITY Atomic DynamoDB
PROVISIONING 100% Terraform
AWS S3 CloudFront AWS Lambda DynamoDB API Gateway Route 53 Terraform GitHub Actions ACM

Engineering Journey

Continuous technical progression across enterprise systems, cloud migrations, and automation.

NOW
CURRENT STATE // ACTIVE EXPLORATION

Building Cloud Systems

Currently building & exploring
Active

Continuously designing and refining resilient cloud architectures, serverless backend patterns, declarative Terraform modules, and automated CI/CD deployment pipelines on AWS.

AWS Cloud Terraform Serverless GitHub Actions Docker
2023
MISSION 02 // ENTERPRISE CLOUD

Cloud DevOps Engineer

NICE
May 2023 – Present · Pune, India

Specializing in cloud-native solutions, serverless backends, and CI/CD pipelines. Focused on eliminating manual toil, automating deployment cycles, and engineering resilient production systems on AWS.

AWS DevOps CI/CD Cloud Automation Serverless
2021
MISSION 01 // CLOUD FOUNDATIONS

System Engineer / AWS Developer

TATA Consultancy Services
May 2021 – May 2023 · Pune, India
  • Designed and implemented serverless architecture using AWS Lambda, DynamoDB, AWS Glue and API Gateway to create a highly scalable and cost-effective backend.
  • Orchestrated cloud infrastructure provisioning and management using Terraform, improving resource consistency and scalability.
  • Implemented CI/CD pipelines for deploying and managing Lambda functions and APIs, enhancing development efficiency and reliability.
  • Integrated Azure Repos into the development workflow, ensuring version control and code collaboration with team members.
  • Orchestrated the deployment and continuous integration/continuous delivery (CI/CD) pipelines with Azure DevOps, automating software releases and updates.
AWS Lambda DynamoDB API Gateway Terraform Azure DevOps AWS Glue

Engineering Toolkit

Production cloud services, infrastructure tooling, and automated deployment frameworks.

CLOUD Cloud Infrastructure (AWS)
AWS Lambda Amazon S3 Amazon CloudFront Amazon DynamoDB Amazon API Gateway Amazon Route 53 AWS CloudWatch AWS Glue AWS IAM AWS Certificate Manager (ACM) Amazon EC2 AWS SAM
IAC Infrastructure as Code & Containers
HashiCorp Terraform Docker Kubernetes Helm Git
CI/CD CI/CD & DevOps Automation
GitHub Actions Azure DevOps AWS CodePipeline Jenkins Postman Jira & Agile Workflows
CODE Programming, Scripting & Data
Python PowerShell Bash / Shell RESTful APIs JSON / YAML Django Pandas & NumPy

Certifications & Education

Verified AWS cloud credentials, academic degree, and professional engineering diplomas.

Verified
Verified
Verified
Verified
Verified
Verified

Shri S'ad Vidya Mandal Institute Of Technology

Bachelor of Engineering — Information Technology
CGPA: 8.13 · August 2016 – May 2020

DevOps Engineer

Edureka
March 2023

Be A DevOps Pro

INeuron
October 2022 – February 2023

Python for Data Science Professional

Edureka
January 2022

Interests

🌐

Technology

In the era of tech, technology has become a key part of human life. I love to discover and learn new technologies.

Sports

Enthusiastic badminton player. Play and watch Cricket, Football. Enjoy watching Formula 1, swimming, and diving.

✈️

Travelling

I love exploring new places, cultures, and experiences.

🚀

Space

I love to explore space-related things, the advancement of science and the vision of space exploration to Mars.


LET'S BUILD
RELIABLE SYSTEMS.

Cloud infrastructure, DevOps automation, serverless systems, and engineering conversations.

Interested in working together, have a question, or just want to connect? Feel free to reach out through any of the channels below.

Status Online
Location India
Response Time < 24h
Open to Work Yes
Last Updated 2026