Confluent

Infrastructure

Neotask gives you conversational control over your entire Confluent Cloud infrastructure -- OpenClaw manages Kafka topics, Flink pipelines, connectors, and TableFlow so your data streams never stall.

What You Can Do

Running real-time data infrastructure is complex. Neotask handles the operational overhead so your data engineers focus on architecture, not console clicking.

Kafka Topic Management

Create topics, adjust configurations, tag them for governance, and search by name or tag. Produce and consume messages for debugging. Your agent manages the full topic lifecycle across clusters.

Flink Pipeline Operations

Create Flink SQL statements, monitor their health, diagnose issues, and inspect table schemas. When a pipeline breaks at 2am, your agent can check statement exceptions and surface the root cause without waking anyone up.

Connector Management

Deploy and manage connectors that move data between Kafka and external systems. Create new connectors, check their status, and delete broken ones -- all through conversation.

TableFlow and Catalog

Bridge your Kafka topics to your lakehouse with TableFlow. Create, update, and manage catalog integrations that keep your data warehouse in sync with your event streams.

Every action runs autonomously or requires your approval -- you decide.

Try Asking

  • "Create a new Kafka topic called 'order-events' with 12 partitions in the production cluster"
  • "Show me all Flink statements that are in an unhealthy state and what exceptions they're throwing"
  • "List all connectors in the staging environment and show which ones are failing"
  • "Tag the 'customer-pii' topic with 'sensitive-data' and 'gdpr-covered'"
  • "Produce a test message to the 'payment-events' topic to verify the pipeline is flowing"
  • "Create a TableFlow topic that syncs our order data to the Snowflake catalog integration"
  • "What topics exist in the production cluster that contain PII tags?"
  • "Delete the broken S3 sink connector and recreate it with the corrected configuration"

    • Pro Tips

  • Tag topics consistently for governance -- agents can search by tag during compliance reviews, making PII audits fast.
  • Use Flink statement health checks as a scheduled automation to catch pipeline issues before they impact downstream consumers.
  • When debugging connector issues, ask for both config and status together to see the full picture.
  • TableFlow catalog integrations bridge Kafka and your lakehouse -- manage them alongside topics for end-to-end pipeline visibility.
  • Enable approval gates for production topic creation and deletion to prevent accidental data loss.
  • Consume messages from a topic during debugging to verify data format and content without writing consumer code.

    • Works Well With