Data Pipeline
  • Data Pipeline
    • About Data Pipeline
    • Design Philosophy
    • Low Code Visual Authoring
    • Real-time and Batch Orchestration
    • Event based Process Orchestration
    • ML and Data Ops
    • Distributed Compute
    • Fault Tolerant and Auto-recovery
    • Extensibility via Custom Scripting
  • Getting Started
    • Homepage
      • List Pipelines
      • Create
        • Creating a New Pipeline
          • Adding Components to Canvas
          • Connecting Components
            • Events [Kafka and Data Sync]
          • Memory and CPU Allocations
        • Creating a New Job
          • Job Editor Page
          • Task Components
            • Readers
              • HDFS Reader
              • MongoDB Reader
              • DB Reader
              • S3 Reader
              • Azure Blob Reader
              • ES Reader
              • Sandbox Reader
            • Writers
              • HDFS Writer
              • Azure Writer
              • DB Writer
              • ES Writer
              • S3 Writer
              • Sandbox Writer
              • Mongodb Writer
              • Kafka Producer
            • Transformations
          • PySpark Job
          • Python Job
      • List Jobs
      • List Components
      • Delete Orphan Pods
      • Scheduler
      • Data Channel
      • Cluster Event
      • Trash
      • Settings
    • Pipeline Workflow Editor
      • Pipeline Toolbar
        • Pipeline Overview
        • Pipeline Testing
        • Search Component in Pipelines
        • Push Pipeline (to VCS/GIT)
        • Pull Pipeline
        • Full Screen
        • Log Panel
        • Event Panel
        • Activate/Deactivate Pipeline
        • Update Pipeline
        • Failure Analysis
        • Pipeline Monitoring
        • Delete Pipeline
        • Pipeline Component Configuration
        • Pipeline Failure Alert History
      • Component Panel
      • Right-side Panel
    • Testing Suite
    • Activating Pipeline
    • Monitoring Pipeline
    • Job Monitoring
  • Components
    • Adding Components to Workflow
    • Component Architecture
    • Component Base Configuration
    • Resource Configuration
    • Intelligent Scaling
    • Connection Validation
    • Readers
      • S3 Reader
      • HDFS Reader
      • DB Reader
      • ES Reader
      • SFTP Stream Reader
      • SFTP Reader
      • Mongo DB Reader
        • MongoDB Reader Lite (PyMongo Reader)
        • MongoDB Reader
      • Azure Blob Reader
      • Azure Metadata Reader
      • ClickHouse Reader (Docker)
      • Sandbox Reader
      • Azure Blob Reader
    • Writers
      • S3 Writer
      • DB Writer
      • HDFS Writer
      • ES Writer
      • Video Writer
      • Azure Writer
      • ClickHouse Writer (Docker)
      • Sandbox Writer
      • MongoDB Writers
        • MongoDB Writer
        • MongoDB Writer Lite (PyMongo Writer)
    • Machine Learning
      • DSLab Runner
      • AutoML Runner
    • Consumers
      • SFTP Monitor
      • MQTT Consumer
      • Video Stream Consumer
      • Eventhub Subscriber
      • Twitter Scrapper
      • Mongo ChangeStream
      • Rabbit MQ Consumer
      • AWS SNS Monitor
      • Kafka Consumer
      • API Ingestion and Webhook Listener
    • Producers
      • WebSocket Producer
      • Eventhub Publisher
      • EventGrid Producer
      • RabbitMQ Producer
      • Kafka Producer
      • Synthetic Data Generator
    • Transformations
      • SQL Component
      • Dateprep Script Runner
      • File Splitter
      • Rule Splitter
      • Stored Producer Runner
      • Flatten JSON
      • Email Component
      • Pandas Query Component
      • Enrichment Component
      • Mongo Aggregation
      • Data Loss Protection
      • Data Preparation (Docker)
      • Rest Api Component
      • Schema Validator
    • Scripting
      • Script Runner
      • Python Script
        • Keeping Different Versions of the Python Script in VCS
    • Scheduler
  • Custom Components
  • Advance Configuration & Monitoring
    • Configuration
      • Default Component Configuration
      • Logger
    • Data Channel
    • Cluster Events
    • System Component Status
  • Version Control
  • Use Cases
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  1. Getting Started
  2. Homepage

Data Channel

Data Chanel shows the health of the Kafka Brokers.

PreviousSchedulerNextCluster Event

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This page is to check the state of the Kafka Brokers.

The pipelines use the Kafka topics as a communication channel to pass info between components. it is crucial for the functionality of the pipeline that brokers are up and running.

Please Note: The green indicator in status shows the broker is up and running; if it is red then the broker is down.

Check out the below-given workflow to understand the steps to access the Data Channel option.

Data Channel page.