Matheen Khan
AWS Cloud & DevOps Engineer | Reliability, FinOps & AI
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Designing a Multi-Tenant Serverless SaaS Platform on AWS
One app. Many businesses. Completely separated data. Zero infrastructure drama.
I’m currently designing a multi-tenant SaaS platform where each customer gets an isolated experience, configurable features, and their own branded subdomain — while the backend stays centralized and serverless.
What I’m building🚀
The platform is being designed to support dozens of independent business tenants from a single AWS architecture, while keeping tenant data isolated, authentication secure, infrastructure cost-efficient, and deployments centralized.
Tech stack:
AWS Lambda • API Gateway • DynamoDB • S3 • CloudFront • Cognito • Route 53 • WAF • Terraform • React • TypeScript
Cloud Architect / DevOps Lead
I’m responsible for designing the AWS architecture, tenant-isolation model, authentication flow, environment strategy, deployment approach, infrastructure automation, and scalability model for the platform.
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ASVU — Automated Social Media Video Distribution Platform
Creators should create.🙌 Teams should grow. Nobody should spend half the day copy-pasting captions and re-uploading the same video🧠 .
That’s why I built ASVU — a cloud automation platform for turning repetitive social-media publishing into a much simpler workflow.
SUMMARY:
Designed and built a cloud-hosted automation platform that simplifies repetitive social-media publishing workflows into a centralized, one-click distribution pipeline.
PROBLEM:
Publishing short-form content across multiple platforms can involve repetitive downloading, local file handling, caption management, platform logins, uploads, and cleanup. I wanted to automate that workflow and reduce the amount of manual operational work required for each piece of content.
SOLUTION:
I built ASVU (Automated Social-Media Video Uploader) — a cloud-based automation platform designed to centralize the content distribution workflow.
Instead of manually moving media between systems, a user provides the authorized source content/link and caption, selects the required destination, and the backend handles processing, API integration, publishing, and temporary-storage cleanup automatically.
KEY CAPABILITIES:
-One-click content publishing workflow
-Cloud-hosted backend automation
-Social-platform API integrations & Cache integrations
-Automated media processing
-Caption and metadata handling
-Temporary-file lifecycle and cleanup
-Multi-destination publishing architecture
-Centralized distribution interface
-Python-based backend automation
-AWS-hosted infrastructure
-Google-API authentication and workflow orchestration
Cloud: AWS
Backend: Python
Integrations: Social Media APIs
Focus: Process Automation • API Integration • Cloud Engineering • SaaS • Workflow Automation
My Role — Cloud Engineer / Full-Stack Automation Developer
I designed the workflow, developed the backend automation, implemented cloud infrastructure and API integrations, handled content-processing logic, and built the publishing orchestration from source input through destination delivery.
just late night caffeine hits!!😂
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Improving AWS Reliability During High-Traffic Production Events
Helped stabilize a high-traffic AWS workload during peak demand by analyzing load balancer errors, scaling bottlenecks, compute capacity, health checks, and monitoring signals. Implemented capacity and reliability improvements to restore stable service and reduce recurrence risk.
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AI-Powered Multi-Account AWS Fleet Optimization Platform
Built a centralized AWS operations platform to monitor Auto Scaling Groups across multiple accounts, analyze Spot vs On-Demand usage, surface FinOps opportunities, and generate AI-assisted optimization recommendations.
The Problem:
Managing Auto Scaling Groups across multiple AWS accounts can become messy very quickly. Capacity, scaling behavior, instance mix, utilization, and cost optimization often have to be reviewed account by account. I wanted to build a single operational view that brings fleet visibility, cost intelligence, and reliability insights together.
The Solution:
I designed and built a centralized AWS CloudOps dashboard that collects ASG information across multiple AWS accounts using cross-account IAM roles. The platform provides a single UI for fleet visibility, capacity analysis, Spot and On-Demand comparison, historical trends, and optimization recommendations.
Key Capabilities-
Use this compact section:
-Multi-account AWS Auto Scaling visibility
-Cross-account IAM role integration
-Spot vs On-Demand capacity analysis
-7–30 day fleet trend analytics
-Cost and FinOps insights
-Estimated savings opportunities
-Workload resilience scoring
-CloudWatch metrics integration
-AI-assisted recommendations using Amazon Bedrock
-Centralized authentication and operations dashboard.
Architecture / Tech Stack:
AWS Lambda, STS/IAM, Auto Scaling, EC2, CloudWatch, DynamoDB, API Gateway, Cognito, Amazon Bedrock
Development: Python, React, REST APIs
Focus: DevOps, FinOps, Cloud Operations, AI Automation.
Outcome:
The project demonstrates how DevOps, FinOps, and AI automation can be combined into a single operational platform. Instead of checking AWS accounts individually, infrastructure teams can use one interface to understand fleet health, capacity distribution, optimization opportunities, and recommended actions.
Built as an independent cloud engineering project focused on real-world AWS operations, reliability, FinOps, and AI-assisted automation.
https://lnkd.in/p/gv8HXd23
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