DevOps Projects in AhmedabadDevOps Projects in Ahmedabad
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Cover image for Intelligent B2B Marketplace for Agricultural
Intelligent B2B Marketplace for Agricultural Sourcing Wikifarmer needed a scalable, trust-driven digital platform to connect thousands of agricultural suppliers with large global buyers — eliminating the inefficiencies, price volatility, and quality uncertainty that plague traditional supply chains. I contributed to the end-to-end design and development of the platform, integrating AI-powered features to enhance sourcing intelligence — including smart supplier matching, dynamic pricing insights, and automated quality assurance workflows. The platform covers the full supply chain lifecycle: from harvest and packing to shipping, logistics, and final delivery. Key features built include a multi-category product marketplace (olive oil, fruits, vegetables), a 360° logistics management system, AI-assisted buyer-supplier negotiation tools, and a transparent transaction layer ensuring security and accountability for every order. The result is a high-performing B2B marketplace that has revolutionized agricultural sourcing for buyers and producers across Europe and beyond — reducing procurement costs, improving cash flow with net-30 financing, and delivering measurable gains in supply chain efficiency and product quality.
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Cover image for AI Content Automation on AWS
AI Content Automation on AWS | GitHub + Slack + Bedrock Description:- I built a production-grade AI content automation system that transforms GitHub commits and Slack conversations into authentic LinkedIn posts. The solution uses AWS, Terraform, ECS Fargate, and EventBridge to automate content generation, approval, and scheduling. - Automated content generation from GitHub and Slack activity - Human-in-the-loop Slack approval workflow - Security filtering to reduce sensitive data exposure - Scheduled content publishing with EventBridge - Production-ready AWS infrastructure managed with Terraform The result is a reliable, scalable automation pipeline that eliminates repetitive content creation while maintaining human control over what gets published. My Role: AWS DevOps Engineer Technologies: AWS ECS · Fargate · Terraform · Docker · CI/CD · EventBridge · GitHub · Slack · AWS Bedrock
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Cover image for LiDAR-Powered As-Built Scanning & CAD
LiDAR-Powered As-Built Scanning & CAD Collaboration Platform Builders Spec is a specialized platform for the architecture, engineering, and construction industry — built to digitize physical spaces using LiDAR scanning and 360-degree cameras, turning real-world environments into precise, measurable 3D models that remote teams can collaborate on. The client needed a centralized system to replace costly hardware, manual measurements, and siloed workflows across renovation and remodeling projects. We built a full-stack web application featuring a web-based CAD viewer, 360-degree virtual tour integration, LiDAR data upload and processing, precise in-browser measurement tools, role-based access control, and a structured project management workflow — all in one platform. The result is a streamlined, affordable solution that lets contractors scan on-site with an iPad and gives design teams full access to accurate as-built data remotely — no expensive software required.
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Cover image for I built an AI-powered AWS
I built an AI-powered AWS log investigation system that allows teams to query logs stored in their existing S3 buckets using natural language. The solution uses AWS Lambda, API Gateway, S3, Bedrock, and Terraform to: - Convert natural-language questions into structured log searches - Automatically discover and filter JSON, CSV, JSONL, and compressed log files - Search across multiple S3 buckets without migrating log data - Use Bedrock to summarize results and provide actionable insights - Keep the log-search function private with IAM-based access control The serverless architecture delivers typical queries in 2–4 seconds at approximately $0.001 per query, while keeping log data within the AWS environment. Technologies:- AWS Lambda · API Gateway · S3 · AWS Bedrock · Terraform · IAM · Python
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Cover image for Automated Windows AMI Patching &
Automated Windows AMI Patching & AWS Infrastructure Automation I built an automated AWS pipeline to eliminate the manual process of patching Windows servers and updating the AMI used by an Auto Scaling Group. The solution uses AWS Image Builder, SSM Patch Manager, CloudWatch, EventBridge, Lambda, and CloudFormation to automate the complete patching lifecycle. Automated Windows patch scanning and installation Automated Sysprep and patched AMI creation CloudWatch logging for patching and audit visibility Automatic Launch Template and ASG updates Preserved existing production configuration The infrastructure is deployed through a single CloudFormation template, creating a repeatable and auditable workflow with minimal manual intervention. My Role: AWS DevOps / Cloud Automation Engineer Technologies: AWS Image Builder, SSM Patch Manager, EC2, Auto Scaling, Lambda, EventBridge, CloudWatch, CloudFormation, IAM, Windows Server, PowerShell
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