Big Data Engineer
for a company that delivers a cognitive technology.
- Designing, deploying and optimizing PoC architectures, monolith or on containers, using Ansible and Python 3.
- Benchmarks for Spark and Elassandra clusters (Elassandra - a hybrid technology between Cassandra and Elasticsearch).
- Researching on Rumprun Unikernels and Docker containers and Kubernetes.
- Researching on migrating from monolith to Docker containers and Kubernetes.
- Customization of existing applications (Java and SQL programming).
- All mentioned technologies
for monitoring metrics/logging were installed, configured and/or ported to containers (and in some cases, applied performance tuning).
- For technical examples, please check a few repositories from one of my GitHub accounts
: (these repositories are not maintained anymore, and there might be existing dependencies issues).
- How to deploy services on containers using Ansible (Java and Python code) https://github.com/LorenvXn/Simple-web-server-example-ansible-and-containers
- A (sort of) GPS simulation
, using Spark streaming and MySQL (Scala, PHP and Leaflet.js) https://github.com/LorenvXn/A-wanna-be-GPS-based-on-Spark-Streaming.
- Small example of deploying a containerized architecture
on Docker containers and Rumprun Unikernels (Unikernels are considered the Library operating system for the Cloud).
Python, Bash, Jenkins, Ubuntu 16, SQL, Ansible, Terraform, Java, AWS Cloud, Spark, Kafka, Zookeeper, Confluent, StreamSets, Zeppelin, Jupyter, Docker, Kubernetes, Elassandra, Cassandra, Elasticsearch, Elastic Stack, Filebeat, Logstash, Elasticsearch, Kibana, Fluentd, Fluentbit, Grafana, InfluxDB, Prometheus, Nginx