Viewing Statistics for Siddhi Applications

This displays the latency of the selected Siddhi application. Latency is the time taken to complete processing a single event in the event flow.

This allows you to assess the performance of the selected Siddhi application.

If the latency of the Siddhi application is too high, check the Siddhi queries and rewrite them to optimise performance.

This shows the overall throughput of a selected Siddhi application over time.

This allows you to assess the performance of the selected Siddhi application.

• If the throughput of a Siddhi application varies greatly overtime, investigate reasons for any slumps in the throughput (e.g., errors in the deployment of the application).

• If the throughput of the Siddhi application is lower than expected, investigate reasons, and take corrective action to improve the throughput (e.g., check the Siddhi queries in the application and rewrite them with best practices to achieve greater efficiency in the processing of events.

This displays the memory usage (In MB) of a selected Siddhi application over time.

This allows you to monitor the memory consumption of individual Siddhi applications.

If there are major fluctuations in the memory consumption of a Siddhi application, investigate the reasons (e.g., Whether the Siddhi application has been inactive at any point of time).

This displays the queries defined in the Siddhi file of the application.

This allows you to check the queries of the Siddhi application if any further investigations are needed based on the observations of its latency, throughput and the memory consumption.

Edit the Siddhi file if any changes that can improve the performance of the Siddhi application are identified.
For detailed instructions to write a Siddhi application, see Creating a Siddhi Application. |
For detailed information about the Siddhi logic, see the Siddhi Query Guide.

This displays the graphical view for queries defined in the Siddhi file of the application.

This allows you to check the flow of the queries of the Siddhi application in the graphical way.

Edit the Siddhi file if any changes that can improve the performance of the Siddhi application are identified.

This table displays performance statistics related to dfferent components within a selected Siddhi application (e.g., queries). The columns displayed are as follows:

• Type: The type of the Siddhi application component to which the information displayed in the row applies. The component type can be queries, streams, tables, windows and aggregations. For more information, see Siddhi Application Overview - Common components of a Siddhi application.

• Name: The name of the Siddhi component within the application to which the information displayed in the row apply.

• Metric Type: The metric type for which the statistics are displayed. This can be either the latency (in milliseconds), throughput the number of events per second), or the amount of memory consumed (in bytes). The metric types based on which the performance of a Siddhi component is measured depends on the component type.

• Attribute: The attribute to which the given value applies.

• Value: The value for the metric type given in the row.

This allows you to carry out a detailed analysis of the performance of a selected Siddhi application and identify components that have a negative impact on the overall performance of the Siddhi application.

Identify the componets in a Siddhi application that have a negative impact on the performance, and rewrite them to improve performance. To understand Siddhi concepts in order to rewrite the components, see the Siddhi Query Guide.