CassandraCompactionExecutorBlockedTasks #

Some Cassandra compaction executor tasks are blocked - {{ $labels.cassandra_cluster }}

alert: CassandraCompactionExecutorBlockedTasks
annotations:
  description: |-
    Some Cassandra compaction executor tasks are blocked - {{ $labels.cassandra_cluster }}
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/instaclustr-cassandra-exporter/cassandracompactionexecutorblockedtasks/
  summary: Cassandra compaction executor blocked tasks (instance {{ $labels.instance
    }})
expr: cassandra_thread_pool_blocked_tasks{pool="CompactionExecutor"} > 15
for: 2m
labels:
  severity: warning

Here is a runbook for the Prometheus alert rule CassandraCompactionExecutorBlockedTasks:

Meaning #

The CassandraCompactionExecutorBlockedTasks alert is triggered when the number of blocked tasks in the Cassandra compaction executor thread pool exceeds 15. This indicates that the compaction executor is unable to process tasks efficiently, which can lead to performance issues and data inconsistencies.

Impact #

• Delayed or failed data compactions can lead to:
  • Performance degradation
  • Increased disk usage
  • Data inconsistencies
  • Potential node failures
• Prolonged blocking of compaction tasks can cause:
  • Increased memory usage
  • Node instability
  • Decreased overall cluster performance

Diagnosis #

To diagnose the issue, follow these steps:

1. Check the Cassandra cluster performance metrics to identify any bottlenecks or anomalies.
2. Verify if there are any recent changes to the cluster configuration, such as changes to the compaction strategy or thread pool settings.
3. Check the Cassandra system logs for any errors or warnings related to compaction.
4. Verify if there are any ongoing maintenance tasks, such as backups or repairs, that may be impacting compaction.
5. Check the disk usage and available disk space on each node to ensure it is not a disk-related issue.

Mitigation #

To mitigate the issue, follow these steps:

1. Investigate and address any underlying performance issues or bottlenecks in the Cassandra cluster.
2. Check if the compaction executor thread pool settings need to be adjusted to handle the workload more efficiently.
3. Consider running a manual compaction to clear any backlog of tasks.
4. Verify if there are any hotspots in the data distribution that may be causing compaction issues.
5. Consider adding more nodes to the cluster or increasing the resources (e.g., CPU, memory) of existing nodes to improve overall cluster performance.

Remember to monitor the alert and adjust the mitigation steps accordingly. If the issue persists, consider escalating to a Cassandra expert or the cluster administrator for further assistance.