Hi, I'am Omotebi

DevOps Engineer

With a high level experience in infrastructure engineering, site reliability engineering, platform engineering and a cybersecurity specialist.

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More About Me

An introduction

AWS and DevOps specialist with over 5 years of experience in cloud computing, automating workflows, and securing cloud infrastructures. Proficient in designing and maintaining AWS environments, using tools like CloudFormation, AWS CLI, and IaC. Expertise in automating software delivery with Jenkins and TeamCity, and skilled in Python and Bash scripting for improving operational efficiency.

05+ Years experience
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Skills

My Expertise

Cloud Infrastructure and Management

More than 5years

Cloud Platforms:

AWS, Azure, GCP

IaC Tools:

Terraform, Cloud Formation

Configuration Management:

Ansible, Puppet, Chef, SaltStack

Networking:

Virtual Networks, Load Balancing, DNS, API Gateway, Firewall and Security, CDN, Kube-proxy

Operating Systems:

Ubuntu, Red Hat Linux, Windows

Monitoring Tool:

Datadog, CloudWatch, Prometheus, Grafana

Logging Tools:

ELK Stack, Splunk

Security Tools:

Network Policies, RBAC, TerraScan, KubeSec, Burp Suite, OWASP ZAP, Wireshark, Metasploit

Collaboration and Project Management

More than 5years

Project management tool:

Microsoft Team, Slack, Jira, Salesforce

Development and Deployment

More than 5years

CI/CD tool and Build Tools:

Maven, Jenkins, TeamCity, ArgoCD, GitLab, GitHub Actions

Version Control:

Git, GitHub, GitLab, SVN

Scripting & Other Tools:

Bash, Python, PowerShell, Groovy

Containers:

Docker, ECS, EKS, Kubernetes (Kubectl and Helm)

SAST Tool:

SonarQube, Synk

Artifactory:

Nexus, JFrog

Databases

More than 5years

Databases:

Oracle, Microsoft SQL Server (MS-SQL Server), RedShift, Dynamo DB, Aurora, RDS

Qualification

My personal journey
Education
Work

Msc Cybersecurity

University of Bradford UK

DevOps Engineer

SupportNEX | Remote
Jan 2022 - Current

DevOps Engineer

BIWE Consulting | Remote
Sept 2019 - Nov 2021

Certifications

My Badges

Aws Certified
Cloud Practitioner

Iso Iec 27001
Lead Implementer

Project

Digital Business Card

E-commerce Microservice Application (Java & C++) with CI/CD Pipeline

The project successfully automated the build and deployment process for the e-commerce application.

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Digital Business Card

Dynamic Website (Three-Tier Application) using LAMP Stack with High Availability

This project successfully created a highly available, secure, and scalable web application infrastructure

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Digital Business Card

Deploying Infrastructure on AWS using Jenkins CI/CD and Docker

This project automated the deployment of infrastructure on AWS using Jenkins CI/CD and Docker, enabling efficient infrastructure management and container orchestration.

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Digital Business Card

Machine Learning Model Deployment on AWS with Jenkins CI/CD and Kubernetes

The project automated the entire deployment lifecycle, ensuring scalable and secure real-time machine learning predictions.

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Digital Business Card

Automating Server Configuration with Ansible

The project reduced configuration time by 80% and improved server consistency across environments, while making it easier to scale infrastructure by reusing Ansible playbooks for new servers.

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E-commerce Microservice Application (Java & C++) with CI/CD Pipeline

Project Description : In this project, we deployed a Java-based microservice e-commerce application, with a backend written in Java and a frontend in C++, onto an Elastic Kubernetes Service (EKS) cluster. This end-to-end deployment utilized Jenkins for CI/CD, ensuring a smooth workflow from GitHub to Kubernetes. The process involved source code management, automated builds, security scanning, and deployment to AWS EKS.

Technologies Used

  • Backend: Java

  • Frontend: C++

  • CI/CD: Jenkins (Declarative pipeline)

  • Containerization: Docker, AWS Elastic Container Registry (ECR)

  • Orchestration: Amazon Elastic Kubernetes Service (EKS)

  • Automation: Helm Charts, Terraform

  • Security: SonarQube (SAST), OWASP ZAP(DAST) scanning

Key Responsibilities

  • Configured Jenkins with POLL SCM to automatically check for GitHub changes using cron jobs.

  • Integrated Jenkins Credentials Plugin to securely manage GitHub and AWS credentials for authentication

  • Automated the CI/CD process, including building, testing, and deploying Java and C++ applications to EKS.

  • Integrated SonarQube for SAST scanning, ensuring code quality by setting Quality Gates.

  • Scanned Docker container images for vulnerabilities using DAST scanning before deployment

  • Used Helm Charts to manage the deployment of built Docker images to the EKS cluster

  • Managed deployment and service manifests for automated deployment of pods and public exposure of services.

Outcome : The project successfully automated the build and deployment process for the e-commerce application. By integrating static and dynamic security testing, the pipeline ensured that only high-quality, secure code reached production. Deployment to AWS EKS was efficient, reducing manual intervention and streamlining operations.

Dynamic Website (Three-Tier Application) using LAMP Stack with High Availability

Project Description : This project involved building a highly available, scalable, and secure dynamic website using the LAMP stack deployed on AWS. The infrastructure follows a three-tier architecture with separate layers for the web server, application logic, and database. The project was designed to ensure high availability by distributing the web and database layers across multiple Availability Zones (AZs) and utilizing auto-scaling for performance optimization. The project also integrated various AWS services like Elastic Load Balancing (ALB), EC2, RDS, S3, Route 53, and security best practices for managing traffic and data.

Technologies Used

  • AWS Services: VPC, EC2, RDS (MySQL), S3, Route 53, ALB, NAT Gateways, IAM

  • Web Server: Apache (LAMP stack)

  • Database: MySQL (RDS)

  • Security: Security Groups, IAM Roles, SSL Certificates

  • High Availability: Auto Scaling Group (ASG), Multi-AZ deployment

  • Monitoring & Testing: k6 for load testing

Key Responsibilities

  • Network Configuration: Created a VPC with public and private subnets, NAT Gateways, and routing tables to route traffic properly across AZs.

  • Web and Database Setup: Deployed the web application on EC2 instances in the private subnets, with the MySQL database hosted on RDS in a multi-AZ setup.

  • Security Implementation: Set up multiple security groups for the web server, load balancer, and database to control inbound and outbound traffic securely.

  • Load Balancer and SSL Setup: Configured an ALB to balance traffic across multiple web servers and set up SSL certificates for secure HTTPS connections.

  • Auto Scaling and High Availability: Created an Auto Scaling Group (ASG) to automatically scale web servers based on traffic and demand, ensuring high availability.

  • S3 Bucket Integration: Utilized an S3 bucket for storing static files and backups, enabling better management of assets and scalability.

  • Testing: Used k6 to load test the web application, verifying that the auto-scaling mechanism works efficiently under load.

Outcome : This project successfully created a highly available, secure, and scalable web application infrastructure. With automatic scaling, multi-AZ deployment, and load balancing, the application can handle increased traffic and ensure uptime. Security was enforced through strict access controls and SSL encryption, while load testing demonstrated the system's ability to auto-scale effectively.

Deploying Infrastructure on AWS using Jenkins CI/CD and Docker

Project Description : This project focused on automating the deployment of infrastructure on AWS using Jenkins CI/CD pipelines and Docker. The process started with the configuration of Terraform for setting up the remote state in S3 and DynamoDB for backend storage, followed by deploying and managing Docker containers. Jenkins was used to automate the CI/CD pipeline, pulling Docker images, creating containers, and ultimately pushing the Jenkins container image to Docker Hub for reuse. The project also involved setting up Nginx, HTTPd, and Tomcat containers, port forwarding, and configuring security groups.

Technologies Used

  • Automation: Jenkins (CI/CD), Terraform

  • Containerization: Docker, Docker Hub

  • Infrastructure: AWS (S3, EC2, DynamoDB), Security Groups

  • Web Servers: Nginx, HTTPd, Tomcat

Key Responsibilities

  • Terraform for Infrastructure: Used Terraform to create the S3 bucket and DynamoDB tables for storing remote state. Applied changes to security groups to open necessary ports for Docker containers and web servers

  • Docker Containerization: Set up and managed Docker containers on EC2 instances, pulling images (e.g., Nginx, HTTPd, and Tomcat) from Docker Hub, and configuring them with port forwarding to expose web servers to the internet.

  • Jenkins Setup and CI/CD Pipeline: Configured Jenkins as a CI/CD server, running inside a Docker container. Automated the process of building and deploying infrastructure on AWS using Jenkins pipelines.

  • Docker Image Management: Pushed the Jenkins container image to Docker Hub, tagging and managing different versions of the image for reuse.

  • Security Configuration: Updated the security group using Terraform to allow traffic on the forwarded ports (8080, 2005, etc.) to ensure proper communication between the Docker containers and external users.

Outcome : This project automated the deployment of infrastructure on AWS using Jenkins CI/CD and Docker, enabling efficient infrastructure management and container orchestration. The Jenkins server container was successfully pushed to Docker Hub, allowing for reuse in other environments. The use of Terraform for infrastructure and security group configuration ensured that the setup was secure and scalable.

Machine Learning Model Deployment on AWS with Jenkins CI/CD and Kubernetes

Project Description : This project focused on deploying a machine learning model for real-time anomaly detection on AWS using Kubernetes (EKS) for orchestration and Jenkins for CI/CD automation. The model was containerized with Docker, and the deployment process was fully automated, utilizing Datadog for monitoring and the ELK Stack for logging and troubleshooting.

Technologies Used

  • CI/CD: Jenkins

  • Container Orchestration: Kubernetes (EKS)

  • Containerization: Docker Groups

  • Monitoring: Datadog

  • Logging: ELK Stack (Elasticsearch, Logstash, Kibana)

  • Cloud Services: AWS (S3, ECR, RDS)

Key Responsibilities

  • Deployed a machine learning model as a container on Amazon EKS, using Helm for Kubernetes resource management.

  • Built a Jenkins pipeline to automate code builds, Docker image creation, and deployment to EKS.

  • Used Datadog for real-time monitoring of pod performance and system metrics in Kubernetes.

  • Integrated the ELK Stack to collect logs from containers, enabling centralized logging and easier debugging.

  • Managed datasets in S3 and stored sensor data in AWS RDS (PostgreSQL) for the model to use in predictions.

  • Applied Kubernetes RBAC and Network Policies to secure the cluster, along with SSL/TLS encryption for API access.

Outcome : The project automated the entire deployment lifecycle, ensuring scalable and secure real-time machine learning predictions. Datadog provided detailed monitoring, while the ELK Stack centralized logging for quick troubleshooting. Auto-scaling and high availability were achieved using Kubernetes’ Horizontal Pod Autoscaler (HPA).

Automating Server Configuration with Ansible

Project Description : This project focused on automating the configuration and management of multiple servers using Ansible. The goal was to standardize the setup of web servers and databases across various environments, ensuring consistency and reducing manual configuration errors. Ansible playbooks were used to install necessary packages, configure services, and manage system settings.

Technologies Used

  • Automation: Ansible

  • Servers: Linux (Ubuntu, CentOS)

  • Tools: SSH, YAML (for playbooks)

Key Responsibilities

  • Wrote Ansible playbooks to automate the installation of web servers (Apache, Nginx) and databases (MySQL, PostgreSQL).

  • Configured firewall rules, user permissions, and SSH key management for secure server access.

  • Used Ansible roles to modularize configurations, making it easier to manage large infrastructure setups.

  • Implemented idempotent configurations, ensuring that tasks were only executed if needed.

Outcome : The project reduced configuration time by 80% and improved server consistency across environments, while making it easier to scale infrastructure by reusing Ansible playbooks for new servers

Contact Details

Get in touch

Contact Address

Manchester, United Kingdom