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Andrey P. Cloud, Microservices and DevOps Platforms

My name is Andrey P. and I have over 9 years of experience in the tech industry. I specialize in the following technologies: RabbitMQ, MySQL Programming, Symfony, PHP, Microservice, etc.. Some of the notable projects I’ve worked on include: NodeJS/React Fullstack Developer for Online Memoria Quiz game, Telegram Bot ChatGPT integration, Monitoring tool for ML Models, Desktop Application For Policy management, Energy Price Calculation Tool, etc.. I am based in Berlin, Germany. I've successfully completed 14 projects while developing at Softaims.

I'm committed to continuous learning, always striving to stay current with the latest industry trends and technical methodologies. My work is driven by a genuine passion for solving complex, real-world challenges through creative and highly effective solutions. Through close collaboration with cross-functional teams, I've consistently helped businesses optimize critical processes, significantly improve user experiences, and build robust, scalable systems designed to last.

My professional philosophy is truly holistic: the goal isn't just to execute a task, but to deeply understand the project's broader business context. I place a high priority on user-centered design, maintaining rigorous quality standards, and directly achieving business goals—ensuring the solutions I build are technically sound and perfectly aligned with the client's vision. This rigorous approach is a hallmark of the development standards at Softaims.

Ultimately, my focus is on delivering measurable impact. I aim to contribute to impactful projects that directly help organizations grow and thrive in today’s highly competitive landscape. I look forward to continuing to drive success for clients as a key professional at Softaims.

Main technologies

  • Cloud, Microservices and DevOps Platforms

    9 years

  • RabbitMQ

    5 Years

  • MySQL Programming

    6 Years

  • Symfony

    1 Year

Additional skills

  • RabbitMQ
  • MySQL Programming
  • Symfony
  • PHP
  • Microservice
  • Docker
  • Azure DevOps
  • Kubernetes
  • Golang
  • RESTful Architecture
  • AWS Application

Direct hire

Potentially possible

Previous Company

SAP

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Experience Highlights

NodeJS/React Fullstack Developer for Online Memoria Quiz game

Development of scalable and reliable game data processing driven by Firebase Realtime Database, Managed Google Cloud SQL and Cloud Functions with Node JS, backend dashboard development with React/Typescript driven by Firebase Hosting/Auth.

Telegram Bot ChatGPT integration

Wrote a Telegram bot for a chat with ChatGPT. Here are some bot features: - keeping conversation context (aka remembering previous messages) - password authenticated users with the managed roles and access rights - service commands directly from the chat, e.g. resetting current conversation, adjusting the system role, changing current model etc - extendable software architecture to support multiple chat bots (e.g. Mattermost, Discord etc.) as well as the chat backends (e.g. Bard) - managed secrets with Transcrypt

Monitoring tool for ML Models

For one of the largest German automotive company I have created a practical case study for deploying monitoring tools in Kubernetes for machine learning models. The aim of the project was to research ways of representing performance of a ML model with standard monitoring tools like InfluxDB/Grafana or Prometheus/Grafana. I've created 2 cases: transferring of inputs to the model and performance metrics to monitoring tools with Kafka or exposing Prometheus API directly from the model. For the first case I've created following Kubernetes setup: - Model Deployment with Seldon with REST API - Model Detector in Seldon with REST API - Kafka with the stream of outputs from the Model Detector - Telegraf to convert outputs to the metrics format and write them to InfluxDB - InfluxDB as metrics storage - Grafana Dashboard with InfluxDB as the data source For the second case following setup was created: - Combined Model and Detector Deployment with Seldon API and custom Prometheus endpoint for metrics - Prometheus service - Scraping configuration with corresponding Network Policies - Grafana with the Prometheus as the data source The case study proved possibility to deliver machine learning metrics to standard monitoring tools in Kubernetes environment.

Desktop Application For Policy management

For one of the largest German automotive company I was requested to develop a cross platform Desktop application for internal usage. It's main goal was to manage auth policies for cars, devices and users for third party service providers, manufacturers and other departments. I developed the application in Golang as a Chrome based web application with internal Go server and Bootstrap 5 driven interface. The main functionality included: - loading external policy validation rules as yaml files - client/server-side validation with error highlighting for the corresponding fields or field groups - multi-step expandable forms - server side rendering with Go-templates, Bootstrap 5 and vanilla JS - file manager to upload/download files - auth with PKI cards (certstore and smimesign library) - go-git integration and communication with the gitlab server to push and pull policy updates - signing commits with PKI - update system and protected delivery of binary artefacts to the customers from Azure pipelines

Energy Price Calculation Tool

The goal of the project was to develop energy price calculation tool for a big energy provider company where all price components where delivered as a huge (over 2GB) pile of CSV files with tariffs data for all possible areas/subnets/consumption ranges/client types. The task was: - analyse and parse price components data - apply efficient search algorithms (binary search by multiple criteria) to for lookups - define GRPC photos to represent price models and price components - design API to receive calculation requests and response with calculation results - implement Go code with the calculation logic - build application code as docker images - deploy price generation tool in Azure Kubernetes - unittest all calculation steps - effort coordination with the frontend developers

Languages

  • German
  • English

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