Patrick Crocker Email & Phone Number

North Carolina, United States

The value I delivered for IIQ included: a string replacement algorithm for our Native Identity change propagation feature, a scoped polymorphic solution applied to Native Identity processing, newly supported DB PostgreSQL, and fixes for strange UI behavior that ultimately originated in Hibernate. The IAI Harvester work involved more of a microservice focus, where I maintained and delivered features for a containerized Java application that was deployed to customer servers. I drove value for the IAI Harvester by adding features to the Docker image via Unix scripting, debugging large customer heap dumps coming from OutOfMemory errors, doing root cause analysis on performance/functional issues via Kibana queries, resolving complex Hibernate issues between the harvester application and customer databases, and communicating across many teams to participate in the larger microservice ecosystem.Accomplishments- IIQ: Worked with principal engineers to build large Native ID change propagation feature, including my own object-oriented designs and implementations- IIQ: Brought in PostgreSQL support which included working with QA to measure performance- IIQ: In-depth investigations into avoided UI bugs that were caused by Hibernate session issues- IAI: Resolved massive source-of-truth Hibernate configuration problem between IAI harvester application and customer IIQ DB schemas, including solution development with IIQ architect- IAI: Constantly executed root cause analysis using Kibana for a litany of customers and issues- IAI: Delivered customizable JVM settings via Docker image for customer debugging- IAI: Explained complex technical implementations on large email threads that involved high-ranking technical and non-technical employees- IAI: Served as the only engineer on the entire project for over a month while other engineers were out

North Carolina, United States

My time spent on the Agility Platform project was focused around fixing defects in the Java/Spring MVC codebase, debugging issues with scaled deployments of Agility in Docker swarms, and writing JUnit tests. Once moved to the CVA pipeline team, I worked as half of an engineering duo that delivered and maintained the CI/CD pipeline responsible for deploying applications that constituted the Customer Virtual Appliance (CVA) offering. The pipeline was managed using Python, Jenkins, Docker, Kubernetes, EC2, AWS Lambda, AWS SQS, and AWS API Gateway.Accomplishments- AP: Debugged various issues with Agility’s workflow policy engine- AP: Wrote unit tests to enhance code coverage and improve stability- AP: Worked with principal engineers on custom documentation tool known as Athena- CVA: Prototyped and delivered AWS Lambda alternative to legacy AWS deployment strategy- CVA: Developed core components of CI/CD pipeline and helped other app development teams with adoption of CI/CD practices- CVA: Implemented major rollback feature for CVA pipeline that involved atomically rolling CVA back in the event of a failure to spin up all associated containers

North Carolina, United States

I largely worked on two squads: one was responsible for catalog aggregation and search functionality across IBM’s cloud marketplace (CASA), and the other was a duo that was chartered with a POC extrapolation of the cloud marketplace search to the larger IBM.com sphere (IBM search). In delivering value for CASA, I wrote Node.js code to ingest and normalize data from external REST API’s for our NoSQL and our own REST API, handled difficult workarounds for non-performant external API’s with critical data, and wrote unit tests with Mocha, Chai, and Nock. I also heavily worked with Elasticsearch in serving our search functionality across the cloud marketplace product catalog. That search work was noticed by senior VP’s involved with IBM.com, who asked me and one other to develop a search POC for the larger IBM corpus using open source technologies.Accomplishments- CASA: Delivered i18n localization for aggregated data pulled from external catalogs- CASA: Fetched and normalized various data from external catalogs to present for our front-end team via our own REST API wrapped around a NoSQL DB- CASA: Developed solutions for non-performant REST API’s that served data critical to the marketplace- CASA: Implemented search for the cloud marketplace by utilizing hosted Elasticsearch- CASA: Developed and maintained REST API’s for page rendering and search- CASA: Created facets for filtered navigation- CASA: Overhauled the autocomplete feature to improve product suggestions and tuned search relevance based on feedback from business stakeholders- IBM Search: Operated as part of a 3-man team that delivered a POC for IBM.com served from Elasticsearch- IBM Search: Evaluated competing search solutions and provided analysis to business, including financial comparisons and technical evaluations- IBM Search: Implemented document ingestion/web crawling using Apache Nutch and Tika, as well as RabbitMQ for scalability