After you log in to the CS management console, the Overview page is displayed. Alternatively, you can click Overview in the left navigation pane to switch to this page.

Once you have jobs created, the Overview page will show you:

• Total Price
• Job Price
• Cluster Price
• Job Status
• Cluster Status
  

  Details for these items are only displayed after jobs are created.

• Get Started with CS

  Use a sample template [Ecosystem]DIS-CS-DIS_SAMPLE_TEMPLATE to create a Flink streaming SQL job with DIS streams serving as both the source and sink streams. Click Get Started to create CS jobs with a sample template.

• How CS Works?

  This area illustrates how CS works. For details, see the Cloud Stream Service Getting Started Guide.

• Typical Application Scenarios
  • DIS-CS-DIS

    DIS streams serve as both the data source and output channel. You need to first enable DIS and prepare data sources and output channels. This scenario mainly involves real-time stream processing.

    Sample template: [Ecosystem]DIS-CS-DIS_SAMPLE_TEMPLATE

  • DIS-CS-SMN

    DIS serves as the data source and CS outputs the job result to a specific SMN topic. You need to first enable DIS to create a DIS stream as the data source, create an SMN topic, and add a mobile phone or email subscription. This scenario mainly involves real-time alarming.

    Sample template: [Ecosystem]DIS-CS-SMN_SAMPLE_TEMPLATE

  • DIS-CS-CloudTable

    DIS serves as the data source and CS outputs the job result to CloudTable. You need to first enable DIS to create a DIS stream as the data source and enable CloudTable. This scenario mainly involves real-time data importing into databases.

    Sample template: [Ecosystem]DIS-CS-CloudTable_SAMPLE_TEMPLATE

  • Kafka-CS-Kafka

    Kafka serves as both the data source and data output channel. You need to create a Kafka cluster first and establish a VPC peering connection between the Kafka cluster and the CS cluster. This scenario mainly involves access to CS from your owned Kafka clusters.

    Sample template: [Ecosystem]Kafka-CS-Kafka_SAMPLE_TEMPLATE

  • IoT

    IoT or edge devices upload data to DIS or other cloud storage services. CS reads data from DIS, analyzes data streams (including fault detection, data cleansing, statistical analysis, warning, and more), and makes the analysis result persistent or reports alarms in real time.

    Sample templates: [IoT]CAR-OVERSPEED-WARNING_SAMPLE_TEMPLATE, [IoT]YAW-WARNING_SAMPLE_TEMPLATE, [IoT]FENCE-WARNING_SAMPLE_TEMPLATE, [IoT]FAKE_LICENSED_CAR_DETECT_SAMPLE_TEMPLATE, and [IoT]WARNING-INHIBITION_SAMPLE_TEMPLATE

  For details about how to interconnect CS with other cloud services, see the Cloud Stream Service Stream Ecosystem Development Guide.

  For details about job template operations, see Job Template.