Topic starter
19/08/2026 3:41 pm
TL;DR: Upstream normalisation, selective ingestion, and schema ownership can cut Splunk spend and reduce lock-in, Axoflow says. Security data pipelines shift telemetry governance before indexing, preserving detection value while easing parser debt and migration pressure.
Editorial analysis by NHI Mgmt Group, based on content published by Axoflow: “Breaking Free from Vendor Lock-in: Cutting Splunk Ingestion Costs with a Security Data Pipeline”.
Key questions
Q: Why do vendor-specific schemas create lock-in in security data pipelines?
A: Because detections, field mappings, and workflows get built around one platform’s data model, so changing SIEMs means rebuilding operational logic as well as ingestion.
Q: What breaks when log reduction is done without source knowledge?
A: Teams drop events that look noisy but later turn out to be important for investigation, detection, or compliance.
Q: How should security teams reduce SIEM ingestion costs without losing detection value?
A: Teams should move collection, classification, and normalisation upstream so the SIEM receives only the data needed for detection and investigation.
Practitioner guidance
- Define upstream telemetry ownership Assign clear ownership for collection, classification, and normalization before events reach the SIEM, with documented decision rights for each source type.
- Move schema normalization out of the SIEM Normalize high-value sources into a vendor-agnostic schema before indexing so detections are not rewritten when analytics tooling changes.
- Set reduction rules by investigative value Classify events by forensic usefulness, compliance need, and detection relevance before dropping volume from noisy sources.
Bottom line: The core problem is not only Splunk cost but the governance model that allows raw telemetry to be treated as a dumping ground.
Glossary terms: Security data pipeline, Vendor Lock-In, Telemetry Optimisation, Vendor-Neutral Schema
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This topic was modified 1 day ago by NHI Mgmt Group
19/08/2026 4:20 pm
Security telemetry has become a governance domain, not just an engineering feed. The article’s central point is that SIEM cost pressure usually reflects weak control over what data enters the analytics layer and why. That shifts the decision surface from log retention alone to upstream classification, ownership, and reduction. Practitioners should treat telemetry intake as a governed control plane, not as a passive transport problem.
A few things that frame the scale:
- 28% of secrets incidents now originate outside code repositories, in Slack, Jira, and Confluence, and are 13% more likely to be categorised as critical than code-based leaks, according to the State of Secrets Sprawl 2026.
A question worth separating out:
Q: What should teams do when repeated parser fixes become routine?
A: Treat recurring parser work as a design failure, not an operations habit. Repeated schema drift means the ingestion layer lacks durable source knowledge, so engineers keep redoing the same translation work. Standardize parsing once, encode source semantics in the pipeline, and free analysts to focus on threats instead of regex maintenance.
👉 Read our full editorial: Security data pipelines can cut Splunk ingest costs and lock-in