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Roadmap

Features

Below is a non-exhaustive list of potential features for future releases (presented in no particular order):

  • Provide state-of-the-art stream processing autoscaling algorithms out of the box. A good first candidate is DS2.
  • Provide simple autoscaling algorithms (e.g., HPA) out of the box.
  • Support additional native-Kubernetes Resources that implement the Scale Sub-resource. This would allow users to scale any native Kubernets framework, e.g., Numaflow.
  • Integrate scale strategies into the KTA Kubernetes Operator (cf. HPA workload stabilization).
  • Monitor changes in stream processing application and reconcile state back to the desired state of KTA.

Tasks

Below is a non-exhaustive list of potential tasks (work items that do not introduce a new feature but, e.g., improve user experience) for future releases (presented in no particular order):

  • Publish the KTA Python SDK to PyPI.
  • Provide helm charts.
  • Improve error handling (robustness).
  • Simplify Flink deployment (e.g., automated job graph retrieval from task manager).
  • Refine SDK and API design.
  • Introduce website versioning.