Sep 2017 – Jun 2019 · 1 yr 9 mos · Porto Area, Portugal

• Along with a small team of brilliant engineers, designed, built, and promoted tools to enable others, in the simplest manner possible, to examine the complexities of performance testing, monitoring, and capacity planning for large-scale, complex and dynamic services with over 400 micro-services distributed and replicated across several world regions.
• The tools that we developed lead the way for real-time data-driven decisions, based on historical time-series data collected from the entire technological stack, that ultimately resulted in a more stable platform and more reliable predictions and communications between engineering and business teams across Farfetch.
• The same data that was once difficult, non centered, required an expert analysis and a lot of effort to bring value, is now serving our engineering and business teams in an independent, clear and concise manner.
• OS's, Languages, API's, Libraries, and Technologies:
• OS's:
• GNU Linux; OpenSolaris; MacOS; Windows;
• Performance and Profiling Tools:
• sysdig; Dtrace; Perf; XPerf; Perfmon; iperf; qperf; gdb; vmstat; dstat; Visual studio load test tool; Jmeter;
• Languages:
• C; C++; Python; C#; Java; SQL; .D (Dtrace); JavaScript; HTML;
• Cloud:
• AWS, Google Cloud Platform, Microsoft Azure;
• Messaging:
• Kafka, RabbitMQ, Redis Streams;
• Applications and Services hosting:
• Docker, Microsoft IWS;
• Datastores:
• InfluxDB, ELK stack, Redis and Redis-modules, PostgreSQL, MySQL, Cassandra, MongoDB;
• Productivity software and Tools:
• Grafana; Kibana; Cmake; Matlab; RSutdio; Visual Studio; Intel Parallel Studio; Microsoft SQL Server; Eclipse; NetBeans; XCode;

Oct 2016 – Sep 2017 · 11 mos · Braga Area, Portugal

• Researcher, as part of the protocol between the University of Texas at Austin & Portugal, in efficient computation to refine atomic models for TEM image simulation and matching.
• Currently migrating from a parallel monolith to a large scale distributed system.
• Together with a team of chemist's and high performance scientists we are leading the way to enable real-time 3D nano particles simulations, with use cases both in medicine, technology and industry.
• What once took hours to a traineed scientist to simulated is now reaching real-time in a distributed cloud infrastructure. Any device with internet connection will be able to start simulation processes that once required a dedicated HPC cluster.
• https://github.com/filipecosta90/im2model

Jul 2016 – Aug 2016 · 1 mo · Austin, Texas Area

• Summer Internship in Grid and Distributed Computing at the the University of Texas at Austin
• from July 10, 2016 - August 16, 2016 as part of the collaboration between Universidade do Minho
• and the University of Texas at Austin.
• During the internship we are collaborating closely with students, PostDocs, and faculty in the
• CDGC group, working at the Bill and Melinda Gates Computer Science Complex and Dell Computer
• Science Hall, recurring to the advanced computing infrastructure STAMPEDE located at
• TACC - Texas Advanced Computing Center.

Sep 2014 – Jun 2016 · 1 yr 9 mos

Sep 2009 – Jun 2013 · 3 yrs 9 mos