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Reducing your infrastructure footprint

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Reducing your infrastructure footprint and allocated resources, you can maximize your investment in Splunk software and achieve cost savings. However, you want to maintain equivalent performance while doing so, or even improve performance. The strategies provided in this pathway will help you accomplish these goals and reduce the total cost of ownership of Splunk Enterprise. You can work through them sequentially or in any order that suits your currently level of progress in compliance.

This article is part of the Reduce Costs Outcome. For additional pathways to help you succeed with this outcome, click here to see the Reduce Costs overview.

Reducing Your Infrastructure Footprint
Pages: 7
  • Choosing between Splunk Enterprise deployment methodologies
    Selecting the correct deployment methodology for Splunk Enterprise directly impacts performance, scalability, and the ability to meet specific business requirements. This article looks at a few key considerations when choosing between a single-instance deployment or a distributed deployment.
  • Sizing your Splunk architecture
    There are three main considerations for proper sizing of architecture: data volume, hardware, and storage. This article details how to choose the right solutions for each of these considerations.
  • Creating efficient searches and dashboards for cost reduction
    Optimizing searches and dashboards in the Splunk platform not only improves performance but also contributes to reducing the total cost of ownership.
  • Implementing best practices for workload management
    By implementing best practices for workload management, organizations can maximize resource utilization, enhance user experience, and drive cost savings.
  • Improving data onboarding with props.conf configurations
    By ensuring that all source types have the required props.conf definitions and stanzas, companies can improve index and search performance through more accurate data parsing. This improvement leads to more efficient data analysis.
  • Optimizing Splunk knowledge bundles
    This article provides guidelines to help you optimize the size of your knowledge bundles, which are collections of configurations and knowledge objects, to achieve the right balance between functionality and performance.
  • Complying with the Splunk Common Information model
    By aligning raw data to the consistent fields and data models in the Common Information Model, you create a normalized data environment that amplifies the efficiency of the Splunk platform, making it quicker and more intuitive for users to pinpoint crucial insights.