l Massive concurrent requests: If a Redis instance receives a large number of concurrent requests, especially read and write requests, the CPU load increases. If the volume of requests exceeds the processing capacity of the Redis instance, CPU usage reaches 100%.
l Excessive data: If the Redis instance stores a large amount of data, the CPU usage increases during some complex operations or large-scale reads/writes. For example, the system consumes many CPU resources when performing large-scale key scanning, sorting, aggregation operations, or persistence of massive data.
l Non-optimal command operations: Some Redis command operations may increase CPU usage. For example, run the SCAN command to perform a full key scan, or run the SORT command to sort a large data set. These operations consume many CPU resources on large data sets and increase CPU usage.
l Lock contention: If a Redis instance uses a distributed lock or custom lock mechanism, a heavy load will be generated on the CPU when multiple threads or clients compete for the same lock. In lock contention, threads are switched over and compete for resources, which increases CPU usage.
l Improper configuration: If the Redis parameters are configured incorrectly, for example, a small value for the maximum number of connections or an improper cache size, the Redis instance may fail to process requests effectively, leading to high CPU usage.