Microsoft Fabric data pipeline and offline deployment of container applications

As project lead, data/software architect and developer, I implemented a Python data pipeline for operational events and time-series data, together with a procedure for offline deployment of a container application.

Source data was ingested through APIs, validated and transferred to a Microsoft Fabric lakehouse with Delta tables. Tests for data quality, repeatable processing and error handling accompanied implementation. Deployment and monitoring were automated.

A deployment procedure was developed for a container application in an isolated environment. Images and dependencies were prepared with versioning and delivered through a local registry. Installation, updates and rollback were tested without external network access and documented in the operations manual.

Result: Built a data pipeline with a Fabric lakehouse and quality checks, and implemented documented offline deployment for container applications.