14000131_nilushan

Nilushan Costa

I am a well organized and hardworking person who can handle responsibilities well. I am a quick learner and I am always willing to expand my knowledge and improve myself.


Email: nilushancosta@yahoo.com
Phone: 0776337593
Course: CS

Interests: Operating systems, Parallel computing, Computer performance
analysis, Computer networks, Aviation, Photography

Technical Skills:  Java, Python, Bash, SQL, Puppet, Nagios, Netty, Docker, Linux, LDAP, Samba, AWS, Bitnami

Project Experience

Automated security scans of cloud servers
A puppet module to automate the set up and running of security audits with Lynis, file integrity checks with Tripwire and vulnerability scans with OpenVAS.
Automated set up of an LDAP server and LDAP based Multi Factor Authentication to secure SSH access
A puppet module to automate the installation and configuration of an LDAP server and the set up of LDAP based Multi Factor Authentication to secure SSH access to cloud servers
LDAP Instance Manager Application
A web application to manage LDAP servers
DocMan
A Document Management System
Workflow Management System
A system to manage the workflow within an organization

Work Experience

  • Intern – DevOps, WSO2 – August 2017 to January 2018 (6 months)

Achievements | Awards

  • Nominated for the 2017/2018 Industrial Placement Award
  • Member of the team that was placed runner-up at the Information Security Quiz 2017 conducted by Sri Lanka CERT
  • Member of the team that was placed 3rd at the Netcom competition of SLIIT CodeFest in 2017

Final Year Project

Adaptive concurrency control based on workload characteristics

Title – Adaptive concurrency control based on workload characteristics
A research project aimed at studying performance characteristics of different workloads in a client server
environment and the effect of the number of concurrent users and thread pool sizes on these characteristics. This study also aims to develop a method to adaptively change the concurrency level in a server based on performance metrics that are gathered at run time.