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AI-Optimized Cloud & MLOps Infrastructure

Scalable cloud architecture, MLOps pipelines, and intelligent DevOps automation — built to deploy and scale your AI products reliably.

Overview

TechChubby designs and manages AI-ready cloud infrastructure on AWS, Azure, and Google Cloud. We build MLOps pipelines that automate model training, deployment, and monitoring — so your AI products scale effortlessly. From serverless APIs to Kubernetes clusters, our cloud engineers ensure high availability, cost optimization, and enterprise-grade security for every AI workload.

Key Features

  • Multi-cloud architecture (AWS, Azure, GCP)
  • MLOps pipelines for model lifecycle management
  • Kubernetes & container orchestration
  • Serverless & microservices deployment
  • CI/CD automation with intelligent testing
  • Auto-scaling & load balancing
  • Cloud cost optimization & monitoring
  • Disaster recovery & backup strategies

What You Get

  • Cloud architecture design & documentation
  • Infrastructure as Code (Terraform/CloudFormation)
  • MLOps pipeline setup & model registry
  • CI/CD pipeline configuration
  • Monitoring, logging & alerting dashboards
  • Security hardening & compliance setup
  • Migration from on-premise to cloud
  • Ongoing cloud management support

Our Cloud Process

1

Assess

Audit current infra & AI requirements

2

Architect

Design scalable cloud blueprint

3

Build

Deploy infra & MLOps pipelines

4

Secure

Harden, test & compliance check

5

Optimize

Monitor, scale & cost-tune

Technologies We Use

AWS Azure Google Cloud Kubernetes Docker Terraform MLflow GitHub Actions Prometheus

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