Troubleshoot high CPU utilization on an ApsaraDB for Redis instance

Search for and disable commands that cause high CPU utilization

Commands that consume a large amount of CPU resources have a time complexity of O(N) or higher. In most cases, a command with a higher time complexity consumes more CPU resources. This increases CPU utilization. For more information about the time complexity of each command, visit the Redis official website.

If ApsaraDB for Redis runs commands that consume a large amount of CPU resources, pending requests are piled up in the queue due to single-threading. This slows down the response of applications. In some cases, an ApsaraDB for Redis instance may be overwhelmed by pending requests. An application may be disconnected due to these requests timing out. In addition, requests may be directly forwarded to backend databases and cause a cache avalanche.

1. Use the performance monitoring feature to identify the time period during which CPU utilization is high. For more information, see Query monitoring data.
2. Use the following methods to identify the commands that consume a large amount of CPU resources:
   • Audit logs record modification and deletion operations that are performed on ApsaraDB for Redis instances. You can query audit logs to analyze the commands and trends within a specific time period. This allows you to identify the commands that consume a large amount of CPU resources. For more information, see Query audit logs.

     

   • Slow logs record commands that run longer than the specified threshold. You can identify commands that consume a large amount of CPU resources based on the statements and durations that are recorded in slow logs. For more information, see Query slow logs.

     

     Note The amount of time that is taken to execute a statement is measured in microseconds.
3. Assess and disable commands that cause a high risk or consume a large amount of CPU resources, such as FLUSHALL, KEYS, and HGETALL. For more information, see Disable high-risk commands.
4. Optimize your application. For example, do not frequently sort data.
5. Optional:Use one of the following methods to modify the instance based on your business requirements:
   • Change the architecture of the instance to read/write splitting to distribute commands or applications that consume a large amount of CPU resources. For more information about the read/write splitting architecture, see Read/write splitting instances.
   • Change the instance into a performance-enhanced instance and use the multi-threading feature of performance-enhanced instances to lower the CPU utilization of the instance. For more information about performance-enhanced instances, see Performance-enhanced instances.
   Note For more information about how to change the architecture and series type of an instance, see Change the configurations of an instance.

Optimize hotkeys

Issue:

A cluster instance or a read/write splitting instance is used. For more information about cluster instances and read/write splitting instances, see Cluster master-replica instances and Read/write splitting instances. The CPU utilization is high on some data nodes in the instance.

Solution:

• Enable the proxy query cache feature. After you enable this feature, proxy nodes cache the request and response data of hotkeys. If a proxy node receives a duplicate request during the validity period of the cached data, the proxy node directly returns a response to the client without the need to interact with backend data shards. This helps prevent skewed requests caused by hotkeys that receive a large number of read requests. For more information, see Use proxy query cache to address issues caused by hotkeys.
  Note This feature is supported only by performance-enhanced instances of the ApsaraDB for Redis Enhanced Edition (Tair) in the cluster architecture. For more information about performance-enhanced instances and cluster instances, see Performance-enhanced instances and Cluster master-replica instances.
• Analyze the slow logs and audit logs of corresponding nodes, and then check the hotkeys on each node. This way, you can resolve the issue or slightly decrease CPU utilization. For more information, see Use the real-time key statistics feature.

Optimize short-lived connections

Issue:

Connections are frequently established to an ApsaraDB for Redis instance. As a result, a large amount of resources of the ApsaraDB for Redis instance are consumed. In this case, CPU utilization is high, the number of established connections is large, and the queries per second (QPS) does not reach the expected value.

Solution:

• Change short-lived connections into persistent connections. For example, create a JedisPool connection pool. For more information, see Jedis client.
• Change the instance into a performance-enhanced instance to optimize the processing of short-lived connections. For more information about performance-enhanced instances, see Performance-enhanced instances.

Disable AOF persistence

Issue:

By default, append-only file (AOF) persistence is enabled for ApsaraDB for Redis instances. If an ApsaraDB for Redis instance runs with heavy loads, frequent AOF operations may increase CPU utilization.

Solution:

Disable AOF persistence if this does not adversely affect your business. In addition, you can back up the Redis data during off-peak hours or during the maintenance window to minimize the impact.

Optimize proxy node connections and the use of pipelines

Issue:

The performance trends of a cluster instance or read/write splitting instance are displayed in the ApsaraDB for Redis console. The CPU utilization of proxy nodes is unevenly distributed, and large differences exist between the maximum and minimum CPU utilization.

Solution:

1. Use the performance trends feature to check whether connection usage is evenly distributed. For more information, see Performance trends.
2. Perform the following operations based on whether connection usage is evenly distributed:
   • If connection usage is evenly distributed, restart the client or proxy node where business applications are deployed to redistribute connections.
   • If connection usage is unevenly distributed, this uneven distribution is usually caused by a large scale of pipeline or batch operations, you can decrease the scale of the corresponding operations. For example, you can separate one operation into multiple operations.

Evaluate the service performance

The preceding methods are used to optimize the performance of your instance. If the average CPU utilization still exceeds 50% during normal business operations, the instance may have a performance bottleneck.

To resolve this issue, first check for commands and requests from application hosts that may degrade the instance performance. If such commands or requests exist, you must optimize your business system. If no such commands or requests are found but the CPU utilization is still high, we recommend that you upgrade the instance specifications to ensure business stability. You can also upgrade the instance to a cluster instance or read/write splitting instance. For more information about how to upgrade an instance, see Change the configurations of an instance.