Which Splunk component performs indexing and responds to search requests from the search head?

There are three types of components in Splunk. And understanding each of them will help you familiarize yourself with the entire data pipeline stages. These components include Splunk Forwarder, Splunk indexer and search head each performing specific tasks in the data search process.

Splunk Forwarder

It’s the Splunk component that is used for collecting the logs. For instance, remote forwarders will be the most effective component if you need to collect logs from any remote machine. And the component is independent of Splunk’s main instances.

Installing such forwarders in several devices, they’ll forward log data to Splunk Indexer for processing and storage. If you want to perform real-time data analysis, we can use Splunk forwarders for this purpose.

When you install Splunk forwards on multiple machines, you’ll be able to collect valuable data in real time for analysis purposes. Unlike traditional data monitoring tools, Splunk forwarded is quite effective as it consumes less CPU memory, about 1-2%. The advantage of the

Splunk Indexer

The Splunk Indexer component is used for indexing and storing data from the forwarder. It transforms incoming data into events, storing them in indexes to enhance the search operation speed and efficiency. If the data comes from a universal forwarder, it will be parsed before indexing.

When parsing data, the process eliminates unwanted data to make the process more accurate. However, data coming from a heavy forwarder is only indexed. During the data indexing, the Splunk component index the data, thus creating several files. The files may be

  • Indexes pointing to raw data (tsidx files)
  • Compressed raw data

The files are stored in sets of directories known as buckets. To be more precise, Splunk processes incoming data to enhance search and analysis. The various ways through which it enhances data search include

  • Separate data streams into individual and searchable events
  • Create and identify timestamps
  • Extract fields like host source and sourcetype
  • Carryout user identifying actions on input data, including writing new/modified keys, filtering unwanted events, identifying custom fields, routing events to specified servers/events and masking sensitive data.

The indexing process is also referred to as event processing, and the other benefit of Splunk indexer is its ability to replicate data, in other words, known as index replication. During index replication or indexer clustering, there is no room for data loss as Splunk retains copies of indexed data that can be used later if something goes wrong. An indexer cluster is a group of indexer components designed for data replication, and it can be helpful if you need to duplicate your data.

Splunk Search Head

The Splunk search head component provides a graphical user interface for various operations. In simple terms, it’s used for interacting with Splunk. It’s possible to search or query the data stored in the Splunk indexer simply by keying in the search word, and the expected result will be displayed as the output.

During the initial state, it’s possible to install search heads with other components on the same server or separate servers. However, there isn’t a separate installation file for the Splunk search head. So, you can enable the splunkweb service on the Splunk server to activate the search head.

The Splunk instance can be a search peer and a search head. The function of the search head is to perform a search but not an index, and this type of search head is known as a dedicated search head.

On the other hand, search peer not only respond to search requests from other search heads but also performs indexing. The search head sends a search request to multiple indexers or searches peers that perform searches on their indexes. Afterward, the search head combines the collected results and sends them to the user. This kind of data search is known as distributed searching, the fastest method.

Search head clusters coordinate the search activities of the search heads, allocate jobs considering the current load, then ensues the search has access to a similar set of data objects.

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