Mihail Chinkov

Close-up of a young male with a neutral expression against a speckled black and white background.
I want to share with you my experience about DevOps pratcices and explain how to adjust the tech stack according to practices and how to speed up your career upgrade and get through all interviews.
Time zone: GMT +2

Experience

During the last few years I'm doing Web Operations for real-time and highly available Web-Applications. Here are the main checkpoints in my career.

  • Implementing from scratch complete infrastructure on AWS for 2 startups
  • Infrastructure Operations, Delivery Pipeline tuning and introduction of Docker containers with Amazon ECS to production environment for one of the most popular entertainment applications in the world iFunny
  • Infrastructure automation deployment based on Terraform and AWS Lambda functions at the most popular apps for online language learning Babbel

Currently my main job is WebOps and DevOps practices implementation at the service for medical students AMBOSS

I could share my experience as a mentor at: * IT infrastructure operations (Linux administration, monitoring, logging, backups etc.) * DevOps practices (culture, team collaboration, coaching, automation, time-to-market speed-up) * Cloud infrastructure operations (AWS/Google Cloud/Microsoft Azure) * Container virtualization, container platform design and improvement * Database administration and tuning * Release engineering (continuous integration, continuous delivery, continuous deployment)

If we talk about tech stack more precisely, I can help to learning the following:

  • Linux administration
  • Python and Bash-scripting
  • Docker + Kubernetes or Amazon ECS as an orchestration system
  • Ansible & Terraform
  • AWS services
  • Database systems: PostgreSQL, MongoDB, Cassandra
  • Monitoring systems: Prometheus, Grafana, Datadog, ELK-stack
  • CI/CD stack: Jenkins, Bamboo, CircleCI, TravisCI

Core skills

  • logstash
  • kibana
  • engineering
  • bash
  • terraform
  • unix
  • devops
  • kubernetes
  • mongodb
  • cassandra
  • redis
  • ansible
  • python
  • go
  • aws
  • sql
  • architecture
  • microservices
  • базы данных
  • cloud
  • infrastructure
  • jenkins
  • prometheus
  • datadog

Specialization

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