Splunk Core Components
Splunk is a powerful platform for analyzing machine data, data that machines emit in great volumes but which is seldom used effectively. Machine data is already important in the world of technology and is becoming increasingly important in the world of business.
The first place that Splunk took hold, naturally, was the datacenter, which is awash in machine data. Splunk became popular with system administrators, network engineers, and application developers as an engine to quickly understand (and increase the usefulness of) machine data.
In most computing environments, many different systems depend on each other. Monitoring systems send alerts after something goes wrong. For example, the key web pages of a site may depend on web servers, application servers, database servers, file systems, load balancers, routers, application accelerators, caching systems, and so on. When something goes wrong in one of these systems, say a database, alarms may start sounding at all levels, seemingly at once. When this happens, a system administrator or application specialist must find the root cause and fix it.
Because almost everything we do is assisted in some way by technology, the information collected about each of us has grown dramatically. Many of the events recorded by servers actually represent behavior of customers or partners. Splunk customers figured out early on that web server access logs could be used not only to diagnose systems but also to better understand the behavior of the people browsing a website.
Splunk does something that no other product can: efficiently capture and analyze massive amounts of unstructured, time-series textual machine data. Although IT departments generally start out using Splunk to solve technically esoteric problems, they quickly gain insights valuable elsewhere in their business.
One of the common characteristics of machine data is that it almost always contains some indication of when the data was created or when an event described by the data occurred. Given this characteristic, Splunk’s indexes are optimized to retrieve events in time-series order. If the raw data does not have an explicit timestamp, Splunk assigns the time at which the event was indexed by Splunk to the events in the data or uses other approximations, such as the time the file was last modified or the timestamp of previous events. The only other requirement is that the machine data be textual, not binary, data. All these features will be covered in Mindmajix Splunk Training in detail.