Amazon DynamoDB
Developer Guide (API Version 2012-08-10)

Logging and Monitoring in DAX

Monitoring is an important part of maintaining the reliability, availability, and performance of DynamoDB Accelerator (DAX) and your AWS solutions. You should collect monitoring data from all parts of your AWS solution so that you can more easily debug a multi-point failure, if one occurs.

Before you start monitoring DAX, you should create a monitoring plan that includes answers to the following questions:

  • What are your monitoring goals?

  • What resources will you monitor?

  • How often will you monitor these resources?

  • What monitoring tools will you use?

  • Who will perform the monitoring tasks?

  • Who should be notified when something goes wrong?

The next step is to establish a baseline for normal DAX performance in your environment, by measuring performance at various times and under different load conditions. As you monitor DAX, you should consider storing historical monitoring data. This stored data gives you a baseline from which to compare current performance data, identify normal performance patterns and performance anomalies, and devise methods to address issues.

To establish a baseline, you should, at a minimum, monitor the following items:

  • CPU utilization, so that you can determine if you might need to use a larger node type in your cluster.

  • Estimated database size and evicted size, so that you can determine if the cluster’s node type has sufficient memory to hold your working set.

  • Client connections, so that you can monitor for any unexplained spikes in connections to the cluster.

  • System errors, so that you can determine if any requests resulted in an error.