Once you login to the status dashboard, the worker nodes that are already added to the Status Dashboard are displayed as shown in the following example:
Adding a worker to the dashboard
If no workers are displayed, you can add worker nodes for which you want to view the status by following the procedure below:
- Click ADD NEW WORKER.
This opens the following dialog box.
- Enter the following information in the dialog box and click ADD WORKER to add a gadget for the required worker in the Worker Overview page.
- In the Host parameter, enter the host ID of the worker node you want to add.
- In the Port parameter, enter the port number of the worker node you want to add.
The following basic details are displayed for each node.
- CPU Usage: The CPU resources consumed by the SP node out of the available CPU resources in the machine in which it is deployed is expressed as a percentage.
- Memory Usage: The memory consumed by the node as a percentage of the total memory available in the system.
- Load Average:
- Siddhi Apps: The total number of Siddhi applications deployed in the node.
Viewing status details
The following is a list of sections displayed in the Worker Overview page to provide information relating to the status of worker nodes.
The worker nodes that are clustered together in a high-availability deployment are displayed under the relevant cluster ID in the Status Dashboard (e.g., under
This allows you to determine the following:
|Description||This section displays statistics for SP servers that operate as single node setups.|
|Purpose||This allows you to compare the performance of single nodes agaisnt each other.|
Nodes that cannot be reached
|Description||When a node is newly added to the Status dashboard and it is unavailable, it is displayed as shown in the above example.|
|Purpose||This allows you to identify nodes that cannot be reached at specific hosts and ports.|
Nodes that are currently unavailable
|Description||When a node that could be viewed previously is no longer available, its status is displayed in red as shown in the example above. The status displayed for such nodes is applicable for the last time at which the node had been reachable.|
|Purpose||This allows you to identify previously available nodes that have become unreachable.|
Nodes for which metrics is disabled
|Description||When a node for which metrics is disabled is added to the Status dashboard, you can view the number of active and inactive Siddhi applications deployed in it. However, you cannot view the CPU usage, memory usage and the load average.|
|Purpose||This allows you to identify nodes for which metrics is not enabled.|
|Recommended Action||Enable metrics for the required nodes to view statistics about their status in the Status Dashboard. For instructions to enable metrics, see Monitoring the Stream Processor - Configuring the Status Dashboard.|
Nodes with JMX reporting disabled
|Description||When a node with JMX reporting disabled is added to the Status dashboard, you can view the number of active and inactive Siddhi applications deployed in it. However, you cannot view the CPU usage, memory usage and the load average.|
|Purpose||This allows you to identify nodes for which JMX reporting is disabled|
|Recommended Action||Enable JMX reporting for the required nodes to view statistics about their status in the Status Dashboard. For instructions to enable JMX reporting, see Monitoring the Stream Processor - Configuring the Status Dashboard.|
|Description||This dispalys the change that has taken taken place in the CPU usage, memory usage and the load average of nodes since the status was last viewed in the status dashboard. Positive changes are indicated in green (e.g., a decrease in the CPU usage in the above example), and egative changes are indicated in red (an increase in the memory usage and the load average in the above example).|
|Purpose||This allows you to view a summary of the performance trends of your SP clusters and single nodes.|
|Recommended Action||Based on the performance trend observed, add more resources to your SP clusters/single nodes to handle more events, or shutdown one or more nodes if there is excess resources.|