Rationale behind calling it a Flink App

Table of Contents

Comprehensive Nature

Complex Workflows: Flink jobs often represent complex workflows that include multiple stages of data processing, such as data ingestion, transformation, aggregation, and output. These workflows can be intricate and involve various interconnected operations, similar to a traditional application.
Multiple Components: A Flink job can consist of various components, such as sources, transformations, sinks, and custom functions. These components work together to perform a coherent set of tasks, much like the components of a traditional software application.

Runtime Environment: When a Flink job is deployed, it runs in a distributed environment, utilizing the Flink runtime for resource management, task scheduling, and fault tolerance. This execution context is similar to how applications run on a platform or infrastructure.
State Management: Flink supports stateful stream processing, where the state is managed and maintained across different operations and executions. Managing state adds a layer of complexity and functionality typical of applications.

Deployment: Flink jobs are deployed to a cluster, where they run continuously (in the case of streaming jobs) or as batch jobs. This deployment and operational aspect aligns more with how applications are managed and executed rather than simple scripts or tasks.
Monitoring and Maintenance: Like applications, Flink jobs require monitoring, logging, and maintenance. They often need to handle operational concerns such as scaling, updating, and fault tolerance.

Development Lifecycle: The development of Flink jobs follows a lifecycle similar to software applications, including design, coding, testing, and deployment. Developers often use IDEs, version control systems, and CI/CD pipelines, which are standard tools for application development.
Reusability and Modularity: Flink jobs can be designed to be modular and reusable. Developers can create libraries and frameworks on top of Flink to facilitate the development of multiple jobs, much like application development.

Integration with Other Systems: Flink applications often integrate with other systems and services such as databases, message queues, and cloud services. This integration is typical of applications that operate within an ecosystem of other software systems.

Clear Communication: Referring to Flink jobs as applications helps convey the complexity and importance of the work being done. It sets appropriate expectations for stakeholders about the scope and nature of the project.