# Using CloudWatch to monitor DB instance performance in Neptune
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You can use CloudWatch metrics in Neptune to monitor what is happening on your DB instances and keep track of the query queue length as observed by the database. The following metrics are particularly useful:
+ **`CPUUtilization`**   –   Shows the percentage of CPU utilization.
+ **`VolumeWriteIOPs`**   –   Shows the average number of disk I/O writes to the cluster volume, reported at 5-minute intervals.
+ **`MainRequestQueuePendingRequests`**   –   Shows the number of requests waiting in the input queue pending execution.

You can also find out how many requests are pending on the server by using the [Gremlin query status endpoint](gremlin-api-status.md) with the `includeWaiting` parameter. This will give you the status of all waiting queries.

The following indicators can help you adjust your Neptune provisioning and query strategies to improve efficiency and performance:
+ Consistent latency, high `CPUUtilization`, high `VolumeWriteIOPs` and low `MainRequestQueuePendingRequests` together show that the server is actively engaged processing concurrent write requests at a sustainable rate, with little I/O wait.
+ Consistent latency, low `CPUUtilization`, low `VolumeWriteIOPs` and no `MainRequestQueuePendingRequests` together show that you have excess capacity on the primary DB instance for processing write requests.
+ High `CPUUtilization` and high `VolumeWriteIOPs` but variable latency and `MainRequestQueuePendingRequests` together show that you are sending more work than the server can process in a given interval. Consider creating or resizing batch requests so as to do the same amount of work with less transactional overhead and/or scaling the primary instance up to increase the number of query threads capable of processing write requests concurrently.
+ Low `CPUUtilization` with high `VolumeWriteIOPs` mean that query threads are waiting for I/O operations to the storage layer to complete. If you see variable latencies and some increase in `MainRequestQueuePendingRequests`, consider creating or resizing batch requests so as to do the same amount of work with less transactional overhead.