For example, if you have a large number of users, you can add extra search heads to better service the users. You can add components to each tier as necessary to support greater demands on that tier. ![]() To ensure high availability and simplify horizontal scaling, you can deploy multiple search heads in search head clusters. ![]() To ensure high data availability and protect against data loss, or just to simplify the management of multiple indexers, you can deploy multiple indexers in indexer clusters.Ī search head interacts with users, directs search requests to a set of indexers, and merges the results back to the user. The indexer also searches the indexed data in response to search requests from a search head. The indexer transforms the data into events and stores the events in an index. Forwarders usually require minimal resources, allowing them to reside lightly on the machine generating the data.Īn indexer indexes incoming data that it usually receives from a group of forwarders. It also describes the functions that each component performs.Ī forwarder consumes data and then forwards the data onwards, usually to an indexer. This table lists the processing components and the tiers that they occupy. Splunk Enterprise components and processing tiers These specialized instances are known as "components". You can, for example, create a deployment with many instances that reside on the data input tier and only ingest data, several other instances that reside on the indexer tier and index the data, and one instance that resides on the search management tier and manages searches. In a typical distributed deployment, each Splunk Enterprise instance performs a specialized task and resides on one of three processing tiers corresponding to the main processing functions: This is known as a "distributed deployment". To support larger environments where data originates on many machines, where you need to process large volumes of data, or where many users need to search the data, you can scale the deployment by distributing Splunk Enterprise instances across multiple machines. A single-instance deployment can be useful for testing and evaluation purposes and might serve the needs of department-sized environments. In small deployments, one instance of Splunk Enterprise handles all aspects of processing data, from input through indexing to search. It ingests data from files, the network, or other sources.ĭepending on your needs, you can deploy Splunk Enterprise as a single instance, or you can create deployments that span multiple instances, ranging from just a few to hundreds or even thousands of instances.Splunk Enterprise performs three main functions as it processes data: As long as the machine that generates the data is a part of your network, Splunk Enterprise can collect the data from anywhere, whether the data is local, remote, or in the cloud. 이전글 db connect App - jar 파일 확인 21.12.Splunk Enterprise indexes data from the servers, applications, databases, network devices, and virtual machines that make up your IT infrastructure.$SPLUNK_HOME/etc/apps/splunk_archiver/java-bin/jars/*.$SPLUNK_HOME/bin/jars/vendors/libs/splunk-library-javalogging-*.jar.Splunk Enterprise Amazon Machine Image (AMI) See Removing Log4j from Splunk Enterprise section below ![]() See Removing Log4j from Splunk Enterprise below for guidance on unsupported versions. Splunk Enterprise (including instance types like Heavy Forwarders)Īll supported non-Windows versions of 8.1.x and 8.2.x only if DFS is used.
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