Intelligent Filtering
Filters low-value data before it reaches Splunk, reducing ingest volume and costs.
SIEM Optimization
Better Data Into Splunk, Less of It, With the Flexibility to Send It Anywhere
Every mature Splunk deployment faces escalating ingest costs and declining data quality. Cribl Stream addresses both challenges by functioning as an intelligent pipeline between your data sources and Splunk.
Deployed together, Cribl Stream and Splunk create a security analytics architecture that scales predictably, performs efficiently, and produces higher-quality detections than either platform operating independently.
Integrated architecture designed to reduce Splunk costs while improving detection quality.
The Operational Reality
Addressing escalating costs and declining data quality simultaneously
IVI designs Splunk and Cribl Stream as an integrated architecture — not as separate projects that happen to share the same data destination.
The Challenge
Every mature Splunk deployment faces two interconnected challenges: escalating ingest costs and declining data quality. These problems compound each other, and addressing one without the other leaves significant operational value unrealized.
Splunk's ingest-based licensing creates predictable cost pressure as environments expand
Logs arrive in verbose, inconsistently field-named formats that consume volume without analytical value
Detection rules fail because data doesn't match expected field structures
Alert triage is inefficient due to lack of contextual enrichment
Integrated Cribl Stream + Splunk Architecture
Cribl Stream functions as an intelligent pipeline between your data sources and Splunk, creating a security analytics architecture optimized for both cost and quality.
CIM Normalization
Normalizes field naming and log formats to Common Information Model standards.
Event Enrichment
Enriches events with contextual data for faster triage and more precise detections.
Multi-Destination Routing
Routes different data streams to appropriate destinations at optimal volume.
Implementation Process
Six-phase approach to deploying integrated Cribl Stream and Splunk architecture.
1
Security Data Assessment
Map current data environment, volumes, formats, and identify optimization opportunities.
2
Joint Architecture Design
Design integrated Cribl Stream pipeline and Splunk configuration for your use cases.
3
Pipeline Deployment & Migration
Deploy Cribl Stream, build pipelines, and migrate sources with validation at each step.
What You Get
Complete security data architecture with quantified cost reduction and improved detection capabilities.
Deployed Cribl Stream Environment
Production-validated pipeline configuration with filtering, transformation, and routing rules.
Splunk Ingest Reduction Documentation
Before/after volume analysis by source with projected license cost impact quantified.
CIM-Compliant Data Pipeline
Normalized, enriched data from all sources enabling ES correlation without custom field mapping.
Operational Outcomes
- Splunk ingest volume can be reduced by 30-60% in most environments
- CIM-normalized data enabling ES correlation searches without custom field mapping
- Event enrichment reducing analyst triage time and improving detection precision
- Multi-destination routing enabling platform flexibility without source reconfiguration
Ideal Fit
- Organizations with Splunk facing active ingest cost pressure or upcoming license renewal
- Teams deploying Splunk who want ingest optimization designed into the architecture
- Environments with data quality problems: missing fields, inconsistent naming, unreliable detection rules
- Organizations building mature security operations requiring a high-quality data foundation
Architectural Comparison
Direct Splunk Ingest vs. Cribl Stream-Optimized Pipeline
The fundamental question is whether you address the data problem in Splunk or before Splunk.
Direct Splunk Ingest
Traditional Approach
Address data quality through Splunk-side field extractions, transforms, and props configuration.
Best Fit
Small environments under 50GB/day where ingest cost is not a primary concern.
Tradeoffs
Consumes compute resources at query time, doesn't reduce ingest volume, every event counts against license regardless of value.
Recommended
Cribl Stream Pipeline
Optimized Architecture
Pre-ingest filtering, transformation, and normalization reduces both volume and computational work.
Best Fit
Organizations at 50GB/day and above where Splunk ingest cost is a budget conversation.
Tradeoffs
Additional infrastructure component to manage, but typically pays for itself within first license renewal cycle.
IVI Recommendation
Recommended for most enterprise Splunk deployments facing cost or data quality challenges.
Why IVI
Purpose-built capabilities for integrated SIEM optimization
End-to-End Security Data Architecture
We design the complete data architecture driven by your detection use cases and compliance requirements.
Comprehensive Design
Data sources, Cribl Stream pipeline design, Splunk ingest architecture, and secondary destinations designed as integrated system.
Use Case Driven
Architecture optimized for your specific detection requirements, not abstract volume minimization goals.
Quantified Cost Impact
We quantify ingest reduction before production cutover using Cribl Stream's throughput analytics.
Before/After Analysis
Document exact volume reduction by source with projected license cost impact for renewal negotiations.
Business Case Development
Three years of pipeline analytics builds strong case for significantly lower licensing at renewal.
Related Resources
Related Resources
Review related solution pages, supporting materials, and additional resources that help explain where this solution fits and how it can be applied.
FAQs
Frequently Asked Questions
Common questions about Splunk and Cribl Stream integration.
We're in a 3-year Splunk contract with no early exit. What's the value of Cribl Stream today?
Two immediate benefits: data quality improvement through better-normalized, enriched data in Splunk improves detection quality and search performance. Second, business case development — Cribl Stream's pipeline analytics quantify your ingest reduction precisely, giving you the data needed to negotiate meaningful reduction at your next renewal.
Can Cribl Stream send data to both Splunk and a cloud data lake simultaneously?
Yes, this is one of Cribl Stream's most valuable use cases. We design pipelines that send high-value security events to Splunk for real-time analytics while routing all events to an S3 data lake for compliance retention. This satisfies retention requirements at storage cost rather than SIEM cost.
We use Splunk ITSI as well as Splunk ES. Does the Cribl Stream architecture support both?
Yes, ITSI and ES operate on the same Splunk platform and benefit from the same data quality improvements. CIM normalization improves ES detection while the same normalized infrastructure telemetry supports ITSI service health KPIs and glass table visualizations.
How much ingest reduction can we expect from Cribl Stream?
Splunk ingest volume can typically be reduced by 30-60% in most environments, though exact reduction depends on your current data sources and quality. We quantify the specific reduction for your environment using Cribl Stream's preview mode before production cutover.
Does Cribl Stream impact Splunk search performance?
Cribl Stream improves Splunk search performance by delivering CIM-normalized, enriched data that requires less computational work at query time. The pipeline processing happens once in Cribl Stream, while the Splunk performance benefit is persistent across all searches.
What happens to our existing Splunk detection content during migration?
We develop and tune Splunk Enterprise Security content against the CIM-normalized, enriched data that the Cribl Stream pipeline delivers. We validate that correlation searches produce expected results on production data before enabling alerting, ensuring continuity of your security operations.