Splunk is a popular software platform used for searching, analysing, and visualising machine-generated data. It provides real-time insights into operational data, security events, and business metrics. Splunk's architecture consists of various components that work together to ingest, index, and process data

1. Splunk is a popular software platform used for searching, analysing, and visualising
machine-generated data. It provides real-time insights into operational data, security events,
and business metrics. Splunk's architecture consists of various components that work
together to ingest, index, and process data. Here is an overview of the Splunk architecture:
1. Data Sources: Splunk can collect data from a wide range of sources, including logs,
metrics, events, and other machine-generated data. It supports data ingestion from
systems, applications, network devices, sensors, and more. Data can be received
through various methods such as file monitoring, network inputs, APIs, and
forwarders.
2. Forwarders: Splunk forwarders are lightweight agents installed on the data source
machines. They collect and send data to the Splunk indexing tier for further
processing. Forwarders can compress, encrypt, and filter data before transmitting it
to the indexing tier.
3. Indexers: The indexing tier receives data from forwarders and performs the indexing
process. Indexers store and manage indexed data, allowing for fast and efficient
search operations. They parse incoming data, extract fields, and create an index that
enables quick searching and analysis.
4. Indexes: Splunk indexes are the repositories where data is stored. The indexed data
is organised into buckets, which are time-based partitions for efficient search and
retrieval. Indexing is performed based on predefined configurations that define how
the data is parsed and processed.
5. Search Head: The search head is the user interface of Splunk, where users interact
with the system to search, analyse, and visualise data. It provides a web-based
interface and a powerful search language that allows users to query the indexed
data, create dashboards, and generate reports.
6. Search Head Clustering (optional): In larger deployments, multiple search heads can
be clustered to provide scalability, high availability, and load balancing. Clustering
allows for distributed search capabilities and fault tolerance.
7. Deployment Server (optional): The deployment server is responsible for managing
the configuration and distribution of Splunk components across the environment. It
simplifies the administration and ensures consistent configurations across multiple
instances.
8. Forwarder Management: Splunk provides tools for managing and configuring
forwarders in a centralised manner. These tools allow administrators to deploy,
update, and monitor forwarders across distributed systems.
9. Splunk Apps and Add-ons: Splunk has a rich ecosystem of apps and add-ons that
extend its functionality. Apps provide pre-built dashboards, reports, and workflows for
specific use cases like security, IT operations, or business analytics. Add-ons provide
integration with external systems, data sources, or specialised processing.

2. 10. Splunk Cloud (optional): Splunk also offers a cloud-based service called Splunk
Cloud, where the entire Splunk infrastructure is hosted and managed by Splunk. This
allows organisations to leverage Splunk's capabilities without managing the
underlying infrastructure.
It's important to note that Splunk's architecture can be highly flexible and scalable, allowing
organisations to tailor the deployment to their specific needs and requirements.