AWS, EKS, Terraform, Jenkins

- OS: RHEL 7-8- PaaS: OpenShift- Scripting: Shell, Maven, Python- Configuration Management: Ansible- Version Control: Git- Build Automation: Jenkins- Artifact Management: Nexus- Atlassian tools: Opsgenie, Jira, Confluence, Bitbucket- LB: Citrix- DB: Oracle, Postgresql, Mongo, Cassandra, Couchbase- Log: ELK, Grafana, Zabbix- Cache: Varnish, Redis- Queue: Kafka

Migrated to Git from SVN (self-managed GitLab)Windows Server, Linux ServerIIS, NginxGitlabCI, TeamcityELK, GrafanaCloudflare WAF, DNS, OWASP, SonarQube

Docker, Docker-Compose Gitlab, GitlabCI, TeamCity.Net Core, React, PHPWindows Server, Linux ServerPowerShell, BashIIS, Nginx, RedisMonitoringMSSQL, PostgreSql, MySQLAzure, AWS, Google StorageAzure AppService, VM, Google Cloud

Used Technologies: Docker, Bitbucket Pipeline, Azure, Python PostgreSQL, AngularJS, Angular2, JavaScript HTML, CSS I created Docker deployment containers according to we needs.I used the Bitbucket Pipeline (cloud) automation execution tool to create Docker deployment containers and run tests.I deployed Docker deployment containers created by the Bitbucket Pipeline to Azure. Using the Azure Container Registry and the Azure Container Instance.The whole operation is as follows:At the end of the sprint, all enhancements are pushed for example, creating a git tag.Docker deployment containers are created automatically run. Using thesei front-end and back-end tess are run. It is then deployed to Azure.

I planned and managed planning, review, retrospective and refinement meetings.