fpiki

fpiki is an open‑source framework designed to support the creation, deployment, and management of data pipelines within cloud‑native environments. Developed by the data engineering team at TechNova Labs, the project first appeared in 2020 as a lightweight wrapper around Apache Airflow and Kubernetes Custom Resources. The name “fpiki” derives from “Fast, Pipeline, Integration, Knowledge, Interface,” reflecting the framework’s focus on speed, modularity, and interconnectivity of data services.

The core concept of fpiki is the Pipeline Operator, a declarative specification written in a YAML‑like syntax. Operators describe source adapters, transformation steps, and sink targets, allowing users to chain data movements across heterogeneous systems such as PostgreSQL, Apache Kafka, and Amazon S3. Underneath, fpiki translates these specifications into Kubernetes Jobs that are scheduled and scaled automatically by the cluster’s scheduler. This design keeps the operational footprint small while taking advantage of containerization for isolation and reproducibility.

fpiki includes a built‑in web UI that provides real‑time monitoring, logging, and retry capabilities. The REST API exposes programmatic access, enabling integration with existing DevOps pipelines and CI/CD workflows. The framework also ships with a set of reusable components for common tasks, such as data validation, schema enforcement, and role‑based access control.

Because fpiki is open source, it has a growing community of contributors. The project follows a regular release cycle, with major updates adding support for new data sources and improved observability features. Potential users include data scientists, ETL developers, and platform teams that require a lightweight, Kubernetes‑native tool for orchestrating data-driven workloads.