Hi, my name is Mert Doğan
I am the Software/DevOps Engineer you need to improve your business, lets grow together.

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About me

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Software/DevOps Engineer that specializing in DevOps Engineering and Backend development. Well-versed with nearly all stages of the development cycle for dynamic web projects. Have a good background in Computer Science.

Experienced in numerous programming languages and various technologies including Golang, Python, Docker, Kubernetes, Helm, JavaScript, TypeScript, Node.js, PostgreSQL, MySQL, MongoDB, Redis, AWS, Azure, Git, Github, JIRA, Grafana, Prometheus, Elasticsearch, Kibana.

My current work experience includes Cloud Native DevOps infrastructure development. Heavily developing, maintaining and monitoring scalable Kubernetes operators with Golang that are mainly responsible for system infrastructure; management of DevOps and orchestration of other operators that work in harmony.

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Projects

Kubernetes Pod Logger

Two separate golang app (client-server) to monitor kubernetes pods inside their namespaces and communicate with each other when pod events occur.

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AI News

Conversational Voice Controlled React News Application that used Alan AI. Alan AI is a speech recognition software that allows you to add voice capabilities to web applications. It allows user to control everything in the app using voice.

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Chat4Fun

Real-time chat application for practicing skills that are React.js, Node.js, Express.js, and Socket.io.

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CoronApp

Corona tracker application that consists of different country's virus case information. The application is made of these technologies: React.js, Chart.js, Material UI.

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Facefication

Face recognition app that I made for practicing when learning fullstack development. During the development of the project, I have learned frontend and backend development, working with APIs, databases, sql and the basics of web development The tech stack: React, Node.js, Express, PostgreSQL, Face Recognition API (Clarifai).

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Hunt-AI

Developed an Artificial Intelligence-based object recognition system for C2C marketplaces.DarkNet53 Convolutional Neural Network was used to train a proper neural network.The final model output's accuracy is 90% on the top 3 categories.

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Contact

mm3rtdogann@gmail.com

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