Pika is a persistent huge storage service, compatible with the vast majority of redis interfaces (details), including string, hash, list, zset, set and management interfaces.
The prerequisites for monitoring Pika with Netdata are to have Pika 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 Pika monitoring please read the collector documentation.
You should now see the Pika 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.
This metric is the number of connections accepted by Pika, which is an important indicator of the overall usage of the system. Monitoring the number of accepted connections can help to identify trends in usage patterns and quickly identify any sudden spikes or drops in usage. It can also help to identify any potential issues with the server such as a misconfigured firewall or an overloaded server.
This metric is the number of clients currently connected to Pika. It is a good indicator of the overall usage of the system and can help to identify trends in usage patterns. By monitoring this metric, it is possible to quickly identify any sudden spikes or drops in usage and take appropriate action if needed.
This metric is the amount of memory used by Pika. This metric can help identify any potential memory leaks or other issues related to memory usage. By monitoring this metric it is possible to ensure that the system is running efficiently and that any potential issues are identified and addressed in a timely manner.
This metric is the number of replicas connected to Pika. It is important to monitor this metric in order to ensure that the replicas are healthy and that the system is running optimally. Monitoring this metric can also help to identify any potential issues with the replication process, such as slow performance or data inconsistency.
This metric is the number of commands processed by Pika. This metric can help identify any potential bottlenecks in the system. By monitoring this metric it is possible to ensure that the system is operating at optimal performance and to identify any potential issues that need to be addressed.
This metric is the number of calls made to commands processed by Pika. This metric can help identify any potential bottlenecks in the system. By monitoring this metric it is possible to ensure that the system is operating at optimal performance and to identify any potential issues that need to be addressed.
This metric is the number of keys stored in the strings database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys that have expired in the strings database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of invalid keys stored in the strings database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys stored in the hashes database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys that have expired in the hashes database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of invalid keys stored in the hashes database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys stored in the lists database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys that have expired in the lists database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of invalid keys stored in the lists database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys stored in the zsets database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys that have expired in the zsets database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of invalid keys stored in the zsets database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys stored in the sets database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of keys that have expired in the sets database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the number of invalid keys stored in the sets database. This metric can help identify any potential issues with key expiration or invalid keys. By monitoring this metric it is possible to ensure that the system is running efficiently and any potential issues are identified and addressed in a timely manner.
This metric is the amount of time that Pika has been running. This metric can help identify any potential issues with the system. By monitoring this metric it is possible to ensure that the system is running as expected and that any potential issues are quickly identified and addressed.