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DataFlow

DataFlow is a namespaced CRD (dataflows, kind DataFlow, group dataflow.dataflow.io) for continuous data pipelines. The operator reconciles each resource into a Deployment running the processor until you delete the DataFlow.

What it does

You declare source, optional transformations, and sink in the spec. The operator:

  1. Resolves SecretRef values from Kubernetes Secrets.
  2. Writes the resolved spec to a ConfigMap.
  3. Creates or updates a Deployment with one or more processor pods.
  4. Reflects Deployment health in DataFlow.status.

The processor runs the same pipeline as DataFlowCron: read → transform → write (plus optional error sink).

flowchart LR
  DF[DataFlow CR] --> Op[Operator]
  Op --> CM[ConfigMap spec]
  Op --> Dep[Deployment]
  Dep --> Proc[Processor Pod]
  Proc --> Ext[Kafka / PostgreSQL / Trino / ClickHouse / Nessie]

When to use DataFlow

Scenario DataFlow DataFlowCron
Kafka consumer group, always on
Real-time replication
Nightly table export
Hourly batch with Slack webhook after success

See Workload Types for a full comparison.

Scheduled runs

For cron-based batch jobs and post-run triggers, use DataFlowCron instead.

API summary

Item Value
API group dataflow.dataflow.io
Resource dataflows
Kind DataFlow
Scope Namespaced

Documentation in this section

  • Spec Reference — all spec fields, CRD diagram, secrets, checkpoint, replicas
  • Lifecycle & Status — cluster objects (df-*), reconciliation, status phases, RBAC

Minimal example

apiVersion: dataflow.dataflow.io/v1
kind: DataFlow
metadata:
  name: kafka-to-postgres
spec:
  source:
    type: kafka
    config:
      brokers: [kafka:9092]
      topic: input-topic
      consumerGroup: dataflow-group
  sink:
    type: postgresql
    config:
      connectionString: "postgres://user:pass@postgres:5432/db?sslmode=disable"
      table: output_table
      autoCreateTable: true
kubectl apply -f dataflow/config/samples/kafka-to-postgres.yaml
kubectl get dataflow kafka-to-postgres
kubectl describe dataflow kafka-to-postgres

See also