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Splunk Lantern

Load balancer data

 

A load balancer is a system or device designed to distribute incoming network or application traffic across multiple servers. The primary goal of a load balancer is to ensure optimal resource utilization, maximize throughput, minimize response time, and prevent any single server from being overwhelmed. Load balancers are crucial in improving the availability and reliability of applications by ensuring seamless failover, handling traffic spikes effectively, reducing latency, and protecting backend servers.

Load balancers can operate at different layers of the OSI model:

  • Layer 4 (Transport Layer): Distributes traffic based on TCP/UDP protocols.
  • Layer 7 (Application Layer): Makes routing decisions based on application-specific data, such as HTTP headers, cookies, or URLs.

Load balancer data typically includes:

  • Web traffic distribution: A website receives heavy traffic during peak hours, such as a flash sale or a product launch
  • API gateway management: A company provides APIs for third-party developers, and traffic volume varies based on demand
  • Cloud auto-scaling: An e-commerce platform hosted in the cloud uses auto-scaling to adjust the number of servers based on demand
  • Reducing downtime during maintenance: A software application requires regular server maintenance without impacting users
  • Multi-region failover: A global SaaS platform hosts servers in multiple data centers worldwide

By using a load balancer, organizations can ensure that their applications remain performant, scalable, and fault-tolerant, making it an essential component of modern software architecture.

The Splunk Common Information Model (CIM) add-on contains an Inventory data model with fields that describe common computer infrastructure components, such as load balancers, from any data source, along with network infrastructure inventory and topology.

Before looking at documentation for specific data sources, review the Splunk Docs information on general data ingestion: