What is Metrics Data? ( Part – 1 )
About Metrics Data:
A metric is also a form of data only, but it focuses only on the values/numbers. These values are the indicators based on time and may have some more dimensions. Each value in your metric dataset is known as a metric data point. A single metric data point can have a timestamp along with multiple indicators and multiple dimensions.
Handling metrics data in Splunk:
Splunk can handle the metrics data very gracefully; you get the option of creating custom ‘metrics index’ to store metrics data. ‘Metrics index’ type is optimized for the storage and retrieval of metric data.
Additionally, Splunk has got some metric-specific commands like mstats, msearch etc. that you can use only for the metric data points.
We will try to cover about these metric-specific commands in our upcoming posts.
Sources of metrics data:
Almost all the hosts, appliances, devices etc. that build up your IT infrastructure are capable of generating metrics data, even some modules from the databases, web servers, sensors etc. can generate metrics data.
Splunking the metrics data :
The Splunk uses a metric collection framework of agents and APIs to gather and stream high-volume metrics data to its platform. Most importantly Splunk supports line metric protocols such as “collectd” and “StatsD”.
The streaming and ingestion of metrics data to the splunk platform happens in a similar way as that of the event data. The forwarders use the collection framework to ingest metric data and securely forward it to the Splunk indexers where it gets stored in the metrics index. The Splunk metric ingestion pipeline can transform your data at indexing time so that it conforms to the protocols of well-structured metrics, even it allows you to transform your event data to metrics data using its “log-to-metrics” feature.
Additionally, there are certain commands such as ‘mcollect’ and ‘meventcollect’ that allow you to convert the results of event data searches or streaming events into metric data points at the search time.
We hope you enjoyed the post.
To know more about the metrics data collection click here.