End-to-End CI/CD Pipeline with Docker & GitHub Actions
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Summary
Designed a robust CI/CD pipeline that automates the build, test, and deployment of containerized applications to AWS EC2.
About
Fast-learning Entry-level Cloud & DevOps Engineer with practical, hands-on experience across AWS, Linux, Docker, and Kubernetes, specializing in deploying scalable applications and automating delivery with CI/CD. Leverages strong analytical skills and cloud-native engineering practices to solve real-world problems through automation and scalable deployments, ensuring reliability and enhanced developer experience.
Work
BUILD AND SHIP ACADEMY LTD, UK
|DevOps & Cloud Projects - SIWES (Students Industrial Work Experience Scheme)
UK, United Kingdom of Great Britain and Northern Ireland
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Summary
Actively designs and ships robust CI/CD pipelines, multi-tier AWS deployments, and Kubernetes workloads, focusing on reliability, automation, and optimizing developer experience.
Highlights
Designed and implemented CI/CD pipelines to streamline software delivery, reducing manual intervention and accelerating deployment cycles.
Deployed multi-tier applications on AWS, configuring scalable and resilient cloud infrastructure to support diverse application requirements.
Managed and orchestrated containerized workloads using Kubernetes, ensuring high availability and efficient resource utilization.
Focused on enhancing developer experience by automating routine tasks and improving system reliability through cloud-native practices.
Gained hands-on experience in cloud architecture and infrastructure as code (IaC) principles within a real-world development environment.
Education
OZ University, partnered with Africa Agility
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Training Program
Cloud Security Engineering
Miva Open University, Abuja
Abuja, FCT, Nigeria
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B.Sc.
Computer Science
Schull Technologies, Lagos
Lagos, Lagos, Nigeria
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Training Program
Cloud Engineering Training
Kubernetes African Developer Training Program by Andela
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Training Program
Linux and Kubernetes Coursework
Languages
English
Certificates
AWS Cloud Quest: Generative AI Practitioner
Issued By
Amazon Web Services
AWS Cloud Quest: Cloud Practitioner
Issued By
Amazon Web Services
Introduction to Linux (LFS101)
Issued By
The Linux Foundation
Introduction to Kubernetes (LFS158)
Issued By
The Linux Foundation
Kubernetes & Cloud Native Essentials (LFS250)
Issued By
The Linux Foundation
Skills
Cloud & DevOps
AWS (EC2, S3, IAM, CloudFront), Cloud Architecture, CI/CD Pipelines, Infrastructure Monitoring, Docker, Kubernetes (Pods, Deployments, Services, ReplicaSets), Image Management, Container Lifecycle, Linux CLI, File Systems, Shell Scripting, System Monitoring, Troubleshooting, Git, GitHub Actions, Infrastructure as Code (IaC), Cloud-Native Systems, Deployment Automation, Operational Reliability, Infrastructure Security, Scalable Application Delivery.
Programming & Tools
Python, JavaScript, Java, C++, Git, GitHub, VS Code, Netlify, Bash, AWS CLI.
Projects
Production-Ready Multi-Tier App Deployment
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Summary
Deployed a secure and scalable multi-tier frontend and backend application on AWS EC2 using Docker, with configured networking and environment settings.
Kubernetes-Based Scalable Application Deployment
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Summary
Deployed containerized workloads using Kubernetes Deployments, Services, and ReplicaSets, implementing rolling updates, self-healing, and horizontal scaling.
Cloud-Based Static Website Deployment (AWS)
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Summary
Hosted a scalable and cost-efficient static website on Amazon S3 with CloudFront CDN and IAM-secured access.
Infrastructure Automation (IaC Practice)
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Summary
Automated cloud resource provisioning using Bash scripting and AWS CLI, enabling repeatable and low-touch environment setups.
Monitoring & Logging Simulation
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Summary
Set up Linux monitoring and logging workflows to track system performance and practice troubleshooting and incident response.