iNTeresTs (list grows): DevOps philosophy, Infrastructure automation (Fabric, Ansible, Chef), practical applications of Machine learning, Data science, Full Hadoop2(Yarn/Hive/Pig/Hbase/Sqoop/Impala/Spark) analytics infrastructure builds, data visualization, NoSQL technologies, infrastructure security application architecture, high availability and scalable architectures, Linux OS internals, Linux networking, Linux Container technologies (Docker, LXC, OpenVZ, LMCTFY), Cloudy things (AWS, DigitalOcean, Google Compute Engine), Virtualization tools (vagrant, packer), Web Application development, Restful API development, Chess, playing Piano, Soccer, basketball, cycling, traveling and "experiencing" new places - And a gadget freak :)

Senior Lead DevOps Engineer @ I work remotely from home in the Seattle area, but work from San Fransisco with the rest of my team twice a quarter or as necessary. From December 2014 to Present (1 year 1 month) Greater Seattle AreaEngineering Boss @ - Interested in machine learning problems - supervised and unsupervised learning - Built a text classification application with a REST API to update/train a model and predict categories of product data, and tested several algorithms like K-nearest neighbor, LogisticRegression, SVM, Naive Bayes and a few others. Evaluated training speed and prediction accuracy (scikit-learn is awesome). - GeekStats: The app Loads and Trains ~30,000 products in 6 seconds. Prediction API can handle up to 250 requests/sec from 10 parallel clients, with response minimum 4ms, mean 40ms - 1 process, 1 thread (tornado magic) running on my laptop yet to test with multiple processors. Also played with twitter sentiment analysis in python using scikit-learn and pattern (ML python package), and charted (with librato) positive vs negative posts around a hashtag or search term. - Built a fully functional 20+ server environment running on a single 16GB Hexacore bare metal server using LXC for virtualization and nginx request proxying for containers with a web UI that needs to be publicly exposed. I also set up a VPN server on the host machine to access the containers directly via internal IPs. Containers include Jenkins build server, Logging server, zookeeper cluster, elasticsearch cluster, mongodb cluster, aerospike database,Kibana 4, NSQ and many others - great lab environment. - Built a web application to manage Linux containers (LXC) on my home lab server. Through the app, I can create containers, create templates, reboot, start, stop, clone and terminate containers as needed for my tests - built using python Flask for the backend API and AngularJS on the frontend. - Wrote a python app to download, extract and parse product data from XML to JSON and load into several types of databases elasticsearch, mongo or any NoSQL backend. - I use fabric for most of my server builds I have a very healthy appetite for the latest and greatest tools - I learn from building. Fun times. From 2010 to Present (5 years) Greater Seattle AreaSr. Infrastructure/DevOps Engineer @ - Heavy use of Amazon web services: EC2, VPC, Kinesis, Autoscaling, ELB, RDS, SQS, SNS, S3, Glacier as necessary - Moved infrastructure from half VPC half Classic EC2, to 100% VPC with no downtime - Built a Hadoop 2 (Yarn) analytics platform configuration management tool in Python, used for disposable hadoop installations which includes auto configuration based on system resources for: Hue, Hadoop2(yarn), Hive, Impala, Sqoop, Hbase, Oozie, Zookeeper,Pig,Spark,MySql DB (for metadata persistence). It dynamically configures and joins all instances that belong in the same cluster. - Built several productivity tools and infrastructure management tools. Few of the tools include: *ninja - a parallel execution commandline tool used everyday to search for AWS and Datacenter instances based on their metadata and run API actions, run arbitrary commands or run deployments *gatekeeper - A simple tool used to manage ssh authentication keys on all servers created for our environment *mg_stats - an app used to collect and send runtime metrics for mongodb *spot_trends - A tool that uses historical AWS spot instance pricing stats to find the least volatile availability zones with lowest price. *ebs_to_instancestore - A tool that creates an instance store AMI from an EBS backed instance - Managed several applications that utilize AWS Autoscaling to expand and collapsed resources based on metrics - Built an application logging process using Splunk, with logfile auto discovery and pager duty alerting - Built, configured and managed several types of database systems and clusters as needed: * Aerospike cluster (processing up to 80K TPS (transactions per second)) * mongodb (replicasets/sharded cluster - up to 30K TPS) * elasticsearch cluster * Splout cluster * Couchbase cluster * CouchDB cluster - Built and managed a Jenkins CI server and a Jenkins based job scheduling server using a Github repository as config backup location - All code versioned using git From February 2014 to December 2014 (11 months) Manager, Infrastructure Services @ * Managed the Vivaki Infrastructure Engineering team - 3 onshore Infrastructure Engineers and 4 offshore Systems Administrators * Defined processes and operating procedures for managing the infrastructure for offshore and onshore teams * Worked directly with VP of Infrastructure & Operations on measures to cut cost and improve efficiencies in our infrastructure -- DevOps/Software development * Built a Web application (SquareONE - Screenshots here: http://goo.gl/mUr0Mo) integrated with Chef to provision and manage instances in Amazon VPC (Linux, Python, AngularJS, Redis and RQ). * Python (Flask) Backend RESTful API on a Linux system * Authentication/Authorization managed through Active directory system * Asynchronous backend job queue to run/schedule long running jobs and application maintenance tasks * UI view to track and promote reserved instance purchase and usage * Administrative panel to perform multiple tasks - Move instances between AWS accounts or availability zones - Expand EBS volumes attached to instances - Create and attach EBS volumes to instances in one step * Redis caching layer for quick data access * Frontend powered by AngularJS and JQuery * Standardized server deployments using the SquareONE tool --- Opensource contribution * Chef individual contributor - Contributed code to add functionality that fixed an issue with the knife-windows plugin that affected windows servers. The fix was necessary to launch and provision windows servers using the Chef knife tool. From August 2013 to February 2014 (7 months) Sr. Systems Engineer @ Worked with a team of engineers to build out VPC infrastructure Worked closely with management to implement cost saving measures in our infrastructure Created a set of applications for Amazon Web Services usage tracking and cost management in a multi-tenant environment. Cut AWS cost by ~30% and aids in keeping AWS cost down by providing aggregated and detailed resource usage, plus reserved instance usage tracking. (Mostly Python & MySQL) Created a set of applications for auto-discovery and monitoring of Linux and Windows EC2 instances for a Centreon monitoring system (Powershell (Windows), MySQL, Python (Linux), some Bash) - In production Created an application for auto-discovery and monitoring of EC2 instances (Linux/Windows) for a Zenoss monitoring system ( Python ) Created EC2 instance image backup manager (with retention period) that operates across multiple regions and can scale out to managing backups for multiple AWS accounts (Currently used for all our AWS accounts) - In production Created a tool for managing EBS snapshot retention by cleaning up according to our retention policy - In production Worked with a team to define processes for Tier 1 and Tier 2 offshore production operations teams From July 2010 to August 2013 (3 years 2 months) Network Operations Engineer II @ Did systems admin type things in a multi-datacenter environment with a crap ton (tech term) of Windows servers to keep MSN services up - And was in school full time. FuN!! - not really - but kinda. From January 2008 to June 2010 (2 years 6 months) Network Operations Center Analyst @ From August 2007 to January 2008 (6 months) MSN Service Operations Center Systems Analyst @ From May 2007 to August 2007 (4 months)

Bachelors of Science, Electrical and Computer Engineering + Minor in Math + Minor in Computer Science @ Seattle University From 2007 to 2011 Okezie Eze is skilled in: Linux, Unix, Virtualization, Python, Software Development, Amazon Web Services (AWS), Servers, MySQL, Operating Systems, Systems Engineering, MongoDB, Infrastructure Management, Databases, DevOps, Git