Pending task metrics for reads
Pending tasks for the following metrics indicate I/O contention, and can manifest in degrading read performance.
Read requests pending
The number of read requests that have arrived into the cluster but are waiting to be handled. During low or moderate read load, you should see 0 pending read operations (or at most a very low number). A continuous high number of pending reads signals a need for more capacity in your cluster or to investigate disk I/O contention. Pending reads can also indicate an application design that is not accessing data in the most efficient way possible.
Read repair tasks pending
The number of read repair operations that are queued and waiting for system resources in order to run. The optimal number of pending read repairs is 0 (or at most a very small number). A value greater than 0 indicates that read repair operations are in I/O contention with other operations. If this graph shows high values for pending tasks, this may suggest the need to run a node repair to make nodes consistent. Or, for column families where your requirements can tolerate a certain degree of stale data, you can lower the value of the column family parameter read_repair_chance.
An upper bound of the number of compactions that are queued and waiting for system resources in order to run. This is a worst-case estimate. The compactions pending metric is often misleading. An unrealistic, high reading often occurs. The optimal number of pending compactions is 0 (or at most a very small number). A value greater than 0 indicates that read operations are in I/O contention with compaction operations, which usually manifests itself as declining read performance. This is usually caused by applications that perform frequent small writes in combination with a steady stream of reads. If a node or cluster frequently displays pending compactions, that is an indicator that you may need to increase I/O capacity by adding nodes to the cluster. You can also try to reduce I/O contention by reducing the number of insert/update requests (have your application batch writes for example), or reduce the number of SSTables created by increasing the memtable size and flush frequency on your column families.