Couchbase is an open source, distributed, NoSQL document-oriented database that is designed for scalability, performance, and availability. It is one of the most popular NoSQL databases and is used in many enterprises for web, mobile, and IoT applications.
The prerequisites for monitoring Couchbase with Netdata are to have Couchbase and Netdata installed on your system.
Netdata auto discovers hundreds of services, and for those it doesn’t turning on manual discovery is a one line configuration. For more information on configuring Netdata for Couchbase monitoring please read the collector documentation.
You should now see the Couchbase section on the Overview tab in Netdata Cloud already populated with charts about all the metrics you care about.
Netdata has a public demo space (no login required) where you can explore different monitoring use-cases and get a feel for Netdata.
Quota percentage used is a metric that tracks the amount of memory used by all databases and buckets within Couchbase, relative to the total quota available to the cluster. This metric should be monitored to ensure that the cluster is not becoming over-utilized and that it is able to scale properly when necessary.
Ops per second is a metric that tracks the number of requests to the cluster per second, including both read and write operations. This metric should be monitored to ensure that the cluster is performing optimally. If this metric is too low, it may be indicative of a bottleneck on the cluster, whereas if it is too high, it may indicate that the cluster is overloaded.
Disk fetches is a metric that tracks the number of requests made to the hard drive for data retrieval. This metric should be monitored to ensure that the hard drive is not becoming a bottleneck, as too many disk fetches can lead to slow system performance.
Item count is a metric that tracks the total number of items (documents, records, files, etc.) stored in the cluster. This metric should be monitored to ensure that the cluster is not becoming over-utilized and that it is able to scale properly when necessary. High item counts may also indicate that the cluster is inefficiently storing data, which can lead to increased disk fetches and slower performance.
Disk used stats is a metric that tracks the total amount of disk space used by the cluster. This metric should be monitored to ensure that the cluster is not becoming over-utilized, as too much disk space can lead to slower system performance. Additionally, monitoring this metric can help to ensure that the cluster is able to scale properly when necessary, as disk space needs to be available for new data.
Data used is a metric that tracks the total amount of data stored in the cluster. This metric should be monitored to ensure that the cluster is not becoming over-utilized, as too much data can lead to slower system performance. Additionally, monitoring this metric can help to ensure that the cluster is able to scale properly when necessary, as data needs to be available for new items.
Memory used is a metric that tracks the amount of memory used by all databases and buckets within Couchbase, relative to the total quota available to the cluster. This metric should be monitored to ensure that the cluster is not becoming over-utilized and that it is able to scale properly when necessary. Monitoring this metric can also help to identify and troubleshoot any memory-related issues.
The memory used metric measures the amount of memory used by each CouchDB bucket. This metric can be used to monitor the memory usage of CouchDB buckets, identify any potential memory capacity issues, and take corrective action.
Number of active non-resident items is a metric that tracks the number of items stored in memory that are not actively being used by the cluster. This metric should be monitored to ensure that the cluster is not wasting resources by storing items in memory that are not actively being used. High numbers may indicate that the cluster is not efficiently storing items in memory, which can lead to slower system performance.
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