Michail Kakos

Cloud Resume Challenge - AWS Edition(Extended)

Personal Project | 2025 | https://cloudresumechallenge.dev/

• Architected and deployed a full stack serverless web application on AWS using S3, CloudFront, API Gateway, Lambda(Python), and DynamoDB.
• Automated infrastructure provisioning and CI/CD pipelines using Terraform and GitHub Actions.
• Implemented comprehensive IAM policies and role-based access control, ensuring secure access management and compliance with cloud security best practices.
• Integrated CloudWatch monitoring and custom alarms for real-time performance tracking, improving operational visibility and enabling proactive incident response.
• Utilised Infrastructure as Code (IaC) principles to enable rapid, repeatable deployments across multiple environments, streamlining environment management and version control.

Network Engineer

Six Degrees | 2020–2024

• Managed 900+ monthly incidents in 24x7 Service Management Centre, maintaining 98% SLA resolution rate and 99.7% network uptime
• Configured and troubleshot Juniper and Cisco routers, switches, and firewalls.
• Performed proactive monitoring and preventative maintenance, reducing critical incidents by 25%.
• Documented network configurations and standard operating procedures, improving team efficiency and knowledge transfer.

Senior Security Systems Engineer

NACD | 2017–2019

• Installed and maintained electronic security systems across 30+ commercial sites, achieving 95% first-call resolution rate.
• Coordinated security projects from requirements gathering through implementation, ensuring on-time delivery.

Automation Engineer

Home of Technologies Ltd | 2016

• Designed and implemented home and building automation solutions for residential and commercial clients, improving energy efficiency by an average of 20%.
• Developed KNX automation applications using ETS4 software, integrating lighting, HVAC, and security systems into unified control platforms.

Cloud Resume Challenge - AWS Edition (Extended)

A personal resume website hosted on AWS using serverless technologies with automated deployment and a live visitor counter. Built a modern resume website that doesn't use traditional web servers.Instead, it uses AWS cloud services where the website files are stored in S3, delivered globally through CloudFront CDN, and includes a visitor counter powered by a Lambda function that stores data in DynamoDB. When you push code changes to GitHub, it automatically deploys to AWS without manual intervention.

AI Chatbot Assistant | Amazon Lex + Lambda

An intelligent chatbot on the resume website that answers visitor questions about your experience, skills, and projects using Amazon's AI services. Added a chat widget to the resume website where visitors can ask questions like "What AWS services do you know?" or "Tell me about your projects" and get instant, intelligent responses. The chatbot uses Amazon Lex (same technology powering Alexa) to understand natural language and provide relevant answers. It remembers the conversation context and suggests follow-up questions.

Containerized Microservices Application

A task management application split into multiple independent services running in Docker containers, orchestrated by AWS ECS. Instead of building one large application, created four smaller applications (microservices) that work together: a gateway that routes requests, a task service for managing tasks, a user service for handling users, and a notification service for alerts. Each service runs in its own Docker container (like a lightweight virtual machine), and AWS ECS manages them—starting, stopping, and scaling automatically based on traffic.

Multi-Environment Infrastructure Automation Pipeline

Automated system that creates and manages identical cloud infrastructure across Development, Staging, and Production environments using code.Created a system where you write code (using Terraform) to define what cloud resources you need (servers, databases, networks), and it automatically creates identical setups for Development (testing), Staging (pre-production), and Production (live). When you want to make changes, you submit them through GitHub, and the system automatically checks for problems, requires approval for production changes, and applies them safely. No more clicking through AWS console manually.