Splunk 101

A software platform designed for searching, monitoring, analyzing, and visualizing machine-generated data. Splunk uses a query language called SPL (Search Processing Language) to perform searches and data analysis.

Types

• Splunk Enterprise: For on-premises deployments
• Splunk Cloud: A cloud-hosted version
• Splunk Light: A lighter version for small to medium-sized businesses. EOL June 4, 2021

How Splunk works?

Data Collection

• Splunk agents or forwarders are deployed on source systems (such as servers, network devices, applications, etc.) to collect data. These agents can monitor log files, capture network traffic, or access other data sources.
• Data can also be ingested directly via APIs, scripts, or other integration methods.

Data Ingestion and Indexing

• Collected data is sent to the central Splunk instance(s), which can be a Splunk Enterprise server or a Splunk Cloud instance.
• Splunk indexes the incoming data in a format optimized for quick searching and retrieval. Data is broken down into events, making it easy to query and analyze.

Data Parsing

• Splunk uses predefined or custom configurations called “parsers” to extract structured information from the raw data. Parsers are essential for breaking down logs and other data into meaningful fields for analysis.

Storage

• Indexed data is stored in a distributed and compressed format, allowing for efficient storage and retrieval. Splunk automatically manages data retention policies, allowing users to specify how long data should be retained.

Search and Analysis

• Users interact with Splunk through a web-based interface or command-line interface to run searches and queries using the Search Processing Language (SPL).
• Splunk’s search engine processes queries in real-time, searching across indexed data, and returning relevant results quickly.
• Users can perform ad-hoc searches, create saved searches, and use advanced analytics functions to gain insights into the data.

Visualization and Reporting

• Splunk provides tools to create interactive dashboards, charts, and reports to visualize data. Users can customize these visualizations to monitor specific metrics or trends.
• Alerts and notifications can be configured to trigger actions when predefined conditions are met.

Machine Learning and AI

• Splunk offers machine learning capabilities to automate anomaly detection, predictive analysis, and trend forecasting. This is particularly valuable for identifying security threats and optimizing operations.

Data Forwarding and Integration

• Splunk can forward specific data or events to external systems or third-party tools for further processing or action.

Data Security and Access Control

• Splunk provides robust security features, including role-based access control (RBAC) and encryption, to protect sensitive data and control user access.

Scaling and High Availability

• Splunk can be scaled horizontally by adding more servers or nodes to handle increasing data volumes and user loads. High availability configurations ensure system reliability.

Maintenance and Management

• Splunk administrators perform routine maintenance tasks, monitor system health, and configure data inputs, indexers, and search heads to optimize performance and ensure data integrity.