Vladimir Kiyko
Verified Expert in Engineering
Software Developer
Moscow, Russia
Toptal member since March 18, 2020
Vladimir is a senior DevOps engineer who went from Sun server support to working with Amazon cloud and writing infrastructure as a code. Right now, he works with development teams, designing and implementing infrastructure for various services. Vladimir is looking forward to working on challenging projects.
Portfolio
Experience
- Amazon Web Services (AWS) - 5 years
- Amazon EC2 - 5 years
- Python - 3 years
- MySQL - 3 years
- Terraform - 3 years
- AWS CloudFormation - 3 years
- Kubernetes - 2 years
Availability
Preferred Environment
Python, Terraform, Linux
The most amazing...
...thing I've done was tuned a MySQL instance to handle 30,000 requests per second in a production environment.
Work Experience
DevOps Engineer
Align Technology
- Developed infrastructure for a batch processing service, that combined three applications in an autoscaling Windows cluster using Chef and Sparkleformation.
- Supported a containerized infrastructure built with Rancher 1 and Traefik.
- Rewrote existing infrastructure code using Python and Terraform.
System Administrator
codefather.cc
- Tuned a MySQL instance to handle 30,000 read and 3,000 write requests per second.
- Designed, implemented, and supported a local Openstack cloud.
- Covered all infrastructure with monitoring using Zabbix.
UNIX Engineer
Jet Infosystems
- Deployed a number of Solaris and RHEL servers according to specifications.
- Deployed an OpsCenter monitoring system for Oracle servers.
- Fixed hardware and OS-level problems in a data center.
Experience
Autoscaling Cluster for Batch Processing Tasks
The cluster combines three applications on each node, two of which do actual computations and one exchanges data with the queue.
Software set: Windows OS, C++ and Java applications, stack_master/Sparkleformation and chef-solo as provisioning software, Python, and Powershell scripts.
Cluster features:
• no separate management servers, all configuration is stored in Cloudformation metadata
• can be deployed with a single command
• each application can be updated independently
• scales automatically according to SWF queue size
• can be updated in a blue-green way
Currently, the cluster works in four regions and scales up to 400 servers in production.
Skills
Tools
AWS CloudFormation, Terraform, Zabbix, Hitachi HPLC, DataStax OpsCenter, Chef, SparkleFormation, Traefik, NGINX, Amazon Elastic Container Service (ECS)
Platforms
Amazon Web Services (AWS), Docker, Kubernetes, Rancher, Amazon EC2, Linux, OpenStack, Solaris, Oracle, Windows
Languages
Python, Go
Storage
MySQL, Cassandra, PostgreSQL
Frameworks
Serverless Framework
Other
RHEL, SAN Brocade
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