Performing regular monitoring activities on a Cassandra cluster
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Verify that the Cassandra cluster is in good health by performing the recommended monitoring activities on a regular basis.
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Monitor Pega alerts for the Decision Data Store (DDS) to discover the causes of performance issues and learn how to resolve them.
For more information, see Pega alerts for Cassandra. -
Review the monitoring information on the DDS service landing page. For information about accessing the DDS service landing page, see Monitoring decision management services.
On the DDS service landing page, you can capture basic and comparative data. Apart from monitoring the cluster metrics, verify that all members of the cluster provide similar performance. -
Run nodetool monitoring commands, for example, to access an overview of the cluster health, or to retrieve a list of active and pending tasks.
For more information, see Nodetool commands for monitoring Cassandra clusters. -
Analyze operating system metrics, such as IO bottlenecks or network buffer buildups, to detect problems with Cassandra nodes.
For more information, see Operating system metrics on Cassandra nodes.
- Pega alerts for Cassandra
Determine the causes of performance issues in your application and learn how to resolve them by analyzing Cassandra-related alert messages.
- Nodetool commands for monitoring Cassandra clusters
Verify the system health by using the nodetool utility. This utility comes as part of the Pega Platform deployment by default.
- Capturing Cassandra metrics
Troubleshoot issues and monitor performance of the Cassandra cluster by gathering detailed metrics.
- Monitoring Cassandra cluster health
You can secure the good health of a Cassandra cluster by monitoring the node status in Pega Platform and by running regular repair operations.
- Configuring the Cassandra cluster
Pega Platform comes with an internal Cassandra cluster to which you can connect through a Decision Data Store data set. Before connecting to the cluster through Pega Platform, perform the following steps to achieve optimal performance and data consistency across the nodes in the cluster.