Yannick Vandewalle

As Observability Engineer I'm the sole responsible for integrating and standardizing all application logs within Arcelormittal on a global scale. With over 300 applications spanning on-prem and cloud environments, I single-handedly manage 3600 log sources generating 40TB of data per month. To enable this massive scale I setup and maintain zero-fault tolerant and horizontally scalable infrastructure on Kubernetes using tools like Fluentbit, Grafana Loki, Elasticsearch and Proxy servers written in Golang. I track and monitor all logs sources via tailor made Grafana dashboards backed by Grafana Prometheus and Thanos. All infrastructure is deployed and managed via Terraform, Azure Devops pipelines and/or Argo Workflows. Next to logging, I manage the end-to-end testing of applications in Arcelormittal using Pytest, Playwright, Selenium and Prometheus. Automated e2e-tests are executed at fixed intervals using Argo Workflows. Upon each test run, all results are forwarded to Grafana Prometheus. If any errors are detected automated alerts are issued to the relevant Developers via Prometheus Alertmanager. Lastly, i'm responsible for delivering management reports. Using Python Numpy, Pandas and Scikit-Learn combined with Argo Workflows, I create automated data processing pipelines. These pipelines process all raw metric and log data and convert them into usable datasets. In turn, the datasets are converted into automated reports via Rmarkdown that are sent out to all relevant parties.

During my employment at Nipro I was responsible for developing software in Ruby On Rails that aids nurses and doctors during kidney dialysis procedures. Due to rapid growth of the product the main focus was refactoring an existing monolith codebase into a decoupled architecture with proper event handling. I was responsible for building the general design for the initial microservices, backed by Redis as a temporary store/queue for the events.

As a full stack developer at Dewaele Vastgoed I was responsible for developing an in-house real estate platform. The platform keeps track of all properties, buyers and seller within the real-estate market. The application was written using the Django Framework and Vue.js. Advanced searches were handled via Elasticsearch. The infrastructure was deployed on AWS and hosted via AWS ECS. CI/CD was handled via AWS CodePipeline and AWS CodeDeploy. Together with my colleagues, we were responsible for designing and implementing the architecture using Terraform. Due to consecutive mergers and the success of the application, it was eventually refactored from a MVC architecture into a microservice architecture.