Design a pipeline orchestration system on Kubernetes

Q: Design a pipeline orchestration system on Kubernetes

This question evaluates a candidate's ability to design scalable, highly available pipeline and workflow orchestration systems on Kubernetes, emphasizing DAG-based scheduling, containerized task execution, retry and failure handling, multi-tenant RBAC, and observability.

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Question

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Design a pipeline/workflow orchestration system (similar to a DAG-based scheduler) that runs workloads on Kubernetes.

Functional requirements

Users can define pipelines as DAGs of tasks (task dependencies).
Tasks run as containerized jobs on Kubernetes.
Support scheduling (cron / interval), ad-hoc runs, and manual retries.
Track task/run states (queued, running, success, failed, cancelled).
Provide logs per task and basic UI/API to view pipeline status.
Retry policy, timeouts, and failure notifications.

Non-functional requirements

Multi-tenant support (teams/namespaces) and RBAC.
Scale to many concurrent runs (e.g., thousands of tasks/minute).
High availability of control plane.
Handle worker/pod failures and scheduler restarts.
Observability: metrics, tracing, structured logs.

Constraints / assumptions

You can assume Kubernetes is available.
You can choose the storage, queue, and execution model.

Describe the high-level architecture, core components, data model, and how you handle scheduling, execution, retries, and failure recovery.

Design a pipeline orchestration system on Kubernetes

Quick Overview

Functional requirements

Non-functional requirements

Constraints / assumptions

Solution

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