Position: DevOps engineer
Category: DevOps
English level: upper
Years of experience: 2.5


My first project:

Building infrastructure via Terraform code on AWS platform. Main services that were used are VPC, EC2, IAM, S3, Route53, RDS. Infrastructure configuration via Ansible roles and playbooks. Continuous integration, delivery and deployment of internal applications via GitLab version control system. Working on containerizing by using docker. Creating docker-compose files for 2 different internal applications and using them in our Ansible code for automated deployment.

My second project:

Migrating Jenkins to Bitbucket. Creating new bitbucket pipelines for continuous integration, delivery and deployment. Separate CI/CD for different environments such as dev, staging and prod. Containerize those services via Docker, create Dockerfiles and docker-composes to deploy services and simplify building application to reduce build time. Working on automating deployment, scaling and management of containerized services based on Kubernetes clusters. Writing Helm Charts for monitoring services Prometheus, Grafana and Fluentbit. Also, setting up alert system to notify our team about cpu, memory, disk space and other usage, setting up slack notifications. Collecting the logs for efficient workaround regarding any problem, quick access and simplicity (EFK stuck). Setup Nginx-Ingress with AWS provided certificate to the necessary domain. Used to work with AWS EKS as our provider and orchestration solution for this project. Creating project documentation with schemas of infrastructure, logical algorithm with code to describe how it works and posted it on Confluence.

The third one:

Refactoring Terraform code to update services on Azure platform. Using Azure DevOps as our version control system for building pipelines to transfer data that are in different data types from one service to another. Main object is big data processing, so I supported Azure Data Factory, Synapse and Databricks flow. Configuration transferring data on purpose via Data Flow and backing it up to Azure Blob Storage.

The fourth one:

Create infrastructure in GCP via Terraform code. Also, create microservices via helm charts that are deployed through terraform modules to Google Kubernetes Cluster. Was working on 19 custom applications with deployments, services, hpa. Nginx-ingress should route the traffic to 10 of that custom applications via service path. Setup monitoring and logging. Grafana & Prometheus + EFK stuck. Was integrating alert manager to slack & Microsoft teams.