io/aurora_respond_to_client - Amazon Aurora
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The io/aurora_respond_to_client event occurs when a thread is waiting to return a result set to a client.

Supported engine versions

This wait event information is supported for the following engine versions:

  • Aurora MySQL version 2

In versions before version 2.07.7, 2.09.3, and 2.10.2, this wait event erroneously includes idle time.


The event io/aurora_respond_to_client indicates that a thread is waiting to return a result set to a client.

The query processing is complete, and the results are being returned back to the application client. However, because there isn't enough network bandwidth on the DB cluster, a thread is waiting to return the result set.

Likely causes of increased waits

When the io/aurora_respond_to_client event appears more than normal, possibly indicating a performance problem, typical causes include the following:

DB instance class insufficient for the workload

The DB instance class used by the DB cluster doesn't have the necessary network bandwidth to process the workload efficiently.

Large result sets

There was an increase in size of the result set being returned, because the query returns higher numbers of rows. The larger result set consumes more network bandwidth.

Increased load on the client

There might be CPU pressure, memory pressure, or network saturation on the client. An increase in load on the client delays the reception of data from the Aurora MySQL DB cluster.

Increased network latency

There might be increased network latency between the Aurora MySQL DB cluster and client. Higher network latency increases the time required for the client to receive the data.


We recommend different actions depending on the causes of your wait event.

Identify the sessions and queries causing the events

You can use Performance Insights to show queries blocked by the io/aurora_respond_to_client wait event. Typically, databases with moderate to significant load have wait events. The wait events might be acceptable if performance is optimal. If performance isn't optimal, then examine where the database is spending the most time. Look at the wait events that contribute to the highest load, and find out whether you can optimize the database and application to reduce those events.

To find SQL queries that are responsible for high load
  1. Sign in to the Amazon Web Services Management Console and open the Amazon RDS console at

  2. In the navigation pane, choose Performance Insights.

  3. Choose a DB instance. The Performance Insights dashboard is shown for that DB instance.

  4. In the Database load chart, choose Slice by wait.

  5. At the bottom of the page, choose Top SQL.

    The chart lists the SQL queries that are responsible for the load. Those at the top of the list are most responsible. To resolve a bottleneck, focus on these statements.

For a useful overview of troubleshooting using Performance Insights, see the Amazon Database Blog post Analyze Amazon Aurora MySQL Workloads with Performance Insights.

Scale the DB instance class

Check for the increase in the value of the Amazon CloudWatch metrics related to network throughput, such as NetworkReceiveThroughput and NetworkTransmitThroughput. If the DB instance class network bandwidth is being reached, you can scale the DB instance class used by the DB cluster by modifying the DB cluster. A DB instance class with larger network bandwidth returns data to clients more efficiently.

For information about monitoring Amazon CloudWatch metrics, see Viewing metrics in the Amazon RDS console. For information about DB instance classes, see Aurora DB instance classes. For information about modifying a DB cluster, see Modifying an Amazon Aurora DB cluster.

Check workload for unexpected results

Check the workload on the DB cluster and make sure that it isn't producing unexpected results. For example, there might be queries that are returning a higher number of rows than expected. In this case, you can use Performance Insights counter metrics such as Innodb_rows_read. For more information, see Performance Insights counter metrics.

Distribute workload with reader instances

You can distribute read-only workload with Aurora replicas. You can scale horizontally by adding more Aurora replicas. Doing so can result in an increase in the throttling limits for network bandwidth. For more information, see Amazon Aurora DB clusters.

Use the SQL_BUFFER_RESULT modifier

You can add the SQL_BUFFER_RESULT modifier to SELECT statements to force the result into a temporary table before they are returned to the client. This modifier can help with performance issues when InnoDB locks aren't being freed because queries are in the io/aurora_respond_to_client wait state. For more information, see SELECT Statement in the MySQL documentation.