Best practices for using Neptune metrics
To identify performance issues caused by insufficient resources and other common bottlenecks, you can monitor the metrics available for your Neptune DB cluster.
Monitor performance metrics on a regular basis to gather data about the average, maximum, and minimum values for a variety of time ranges. This helps identify when performance is degraded. Using this data, you can set Amazon CloudWatch alarms for particular metric thresholds so you are alerted if they are reached.
When you set up a new DB cluster and get it running with a typical workload, try to capture the average, maximum, and minimum values of all of the performance metrics at a number of different intervals (for example, one hour, 24 hours, one week, two weeks). This gives you an idea of what is normal. It helps to get comparisons for both peak and off-peak hours of operation. You can then use this information to identify when performance is dropping below standard levels, and can set alarms accordingly.
See Monitoring Neptune Using Amazon CloudWatch for information about how to view Neptune metrics.
The following are the most important metrics to start with:
BufferCacheHitRatio — The percentage of requests that are served by the buffer cache. Cache misses add significant latency to query execution. If the cache hit ratio is below 99.9% and latency is an issue for your application, consider upgrading the instance type to cache more data in memory.
CPU utilization — Percentage of computer processing capacity used. High values for CPU consumption might be appropriate, depending on your query-performance goals.
Freeable memory — How much RAM is available on the DB instance, in megabytes. Neptune has its own memory manager, so this metric may be lower than you expect. A good sign that you should consider upgrading your instance class to one with more RAM is if queries often throw out-of-memory exceptions.
The red line in the Monitoring tab metrics is marked at 75% for CPU and Memory Metrics. If instance memory consumption frequently crosses that line, check your workload and consider upgrading your instance to improve query performance.
