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You will get Automated Code Deployment to AWS or Azure | CI/CD Setup
Project details
This project helps automatically deploy code from GitLab or GitHub to AWS or Azure using strong CI/CD pipelines. When developers push code to GitLab or GitHub, the automation pipeline starts and handles everything from checking the code to deploying it live.
We use Docker to build the code, so the environment stays the same from development to production. This avoids issues like "it worked on my machine but not on the server" because everything runs in the same container.
The pipeline also runs important checks like code linting (to follow coding rules), unit testing (to make sure each part works properly), and security scans (if available) to find any weak points in the code. This ensures only clean and safe code is deployed.
At the end, based on what the project needs, the code is automatically deployed to AWS or Azure. This makes the process fast, smooth, and reliable for production updates.
We use Docker to build the code, so the environment stays the same from development to production. This avoids issues like "it worked on my machine but not on the server" because everything runs in the same container.
The pipeline also runs important checks like code linting (to follow coding rules), unit testing (to make sure each part works properly), and security scans (if available) to find any weak points in the code. This ensures only clean and safe code is deployed.
At the end, based on what the project needs, the code is automatically deployed to AWS or Azure. This makes the process fast, smooth, and reliable for production updates.
What's included $199
These options are included with the project scope.
$199
- Delivery Time 2 days
- Number of Revisions 4
- Design Customization
- Content Upload
- Responsive Design
- Source Code
Frequently asked questions
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NS
Nirmeet S.
Apr 1, 2026
DevOps Engineer Needed - Deploy 4 Websites on Digital Ocean
Excellent DevOps work. He successfully migrated all 4 apps from Replit to DigitalOcean/AWS with clean Ubuntu setup, Nginx reverse proxy, SSL via Certbot, and Route 53 DNS configured properly.
CI/CD with GitHub Actions is solid and fully automated. Also delivered a clear cost optimization report.
Strong technical skills, clean execution, and reliable delivery. Highly recommended.
CI/CD with GitHub Actions is solid and fully automated. Also delivered a clear cost optimization report.
Strong technical skills, clean execution, and reliable delivery. Highly recommended.
NS
Nirmeet S.
Mar 24, 2026
DevOps Expert Needed for Cloud Infrastructure Setup & CI/CD Automation
Had a really great experience working with this DevOps engineer. He’s very experienced, knows his stuff, and was able to deliver solid, scalable solutions without any hassle. Communication was smooth and timely throughout, which made the whole process easy to manage. He understood what was needed quickly and got things done efficiently. I’d definitely recommend him and would be happy to work together again very soon.
About Veekunth
Senior AWS DevOps Engineer | EKS Terraform GitOps | AI & GPU Infra
Chandigarh, India - 1:51 am local time
I work with start-ups and growing companies that need cloud infrastructure built right the first time secure, automated, observable, and cost-efficient.
What I deliver:
𝐀𝐖𝐒 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞
VPC, EC2, RDS, S3, IAM, Secrets Manager, Route 53
Multi-environment setup with proper isolation and least-privilege access
Cost optimisation and right-sizing built into every architecture
𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 & 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬
EKS cluster provisioning with Terraform and Terragrunt
GitOps deployments via Argo CD and Helm charts
Docker containerisation and microservices deployment
𝐂𝐈/𝐂𝐃 & 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧
GitHub Actions and GitLab CI pipelines
Deployment time reduced from 45 minutes to under 8 minutes on production systems
Self-hosted runners, approval gates, multi-environment rollouts
𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 & 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲
Prometheus + Grafana dashboards and alerting
Datadog, CloudWatch, Loki for logging
Incident response runbooks and SLO tracking
𝐀𝐈 & 𝐆𝐏𝐔 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞
GPU compute node operations across Akash Network, Nosana, Render Network, io.net, and Vast.ai
Private LLM deployment using Ollama, vLLM, and open-source models
Hybrid cloud + decentralised GPU architectures for cost-efficient AI inference
Docker, Kubernetes, NVIDIA GPU Operator, on-chain provider registration
Forward-Deployed AI Engineer experience - private LLM deployment, on-premises inference infrastructure, and AI workflow integration directly within client environments
Production highlights:
𝐍𝐨𝐯𝐚𝐠𝐞𝐦𝐬:- multi-tenant workforce SaaS on EKS: Terraform-managed, GitOps pipeline, Kafka for real-time data, Firebase, PostgreSQL, Redis, Datadog monitoring, daily GDrive backups
𝐍𝐕𝐈 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦:- government vehicle intelligence API on Ubuntu/DigitalOcean: Nginx, PostgreSQL, PM2, multi-environment CI/CD
𝗨𝗦 𝗖𝗹𝗶𝗲𝗻𝘁 𝗚𝗣𝗨 𝗙𝗮𝗿𝗺:- Akash Network provider with RTX 5070, on-chain bidding, health dashboards, security hardening
𝐖𝐡𝐲 𝐜𝐥𝐢𝐞𝐧𝐭𝐬 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐦𝐞:
Infrastructure is documented from day one - no black boxes
Every environment is code - Terraform, no manual console changes
13+ years of real-world experience across startups and enterprise
Fast communication, IST timezone with flexible overlap for US/EU/SG hours
MSc Advanced Computer Science, University of Leicester
If you need AWS infrastructure built, automated, secured, or migrated - let's talk.
Steps for completing your project
After purchasing the project, send requirements so Veekunth can start the project.
Delivery time starts when Veekunth receives requirements from you.
Veekunth works on your project following the steps below.
Revisions may occur after the delivery date.
AWS code deployment
1. Environments: 2. No of projects: 3. GitLab/GitHub: 4. AWS or Azure