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19/08/2026 3:41 pm
TL;DR: SIEM pain is often a data-governance problem, not a logging problem: upstream normalization, schema ownership, and selective ingestion can reduce cost, limit vendor lock-in, and preserve detection value, according to Axoflow. The practical shift is to treat the security data pipeline as a control plane for telemetry, not a dumping ground for compliance retention.
NHIMG editorial — based on content published by Axoflow: Breaking Free from Vendor Lock-in: Cutting Splunk Ingestion Costs with a Security Data Pipeline
By the numbers:
- Data reduction tools can achieve 30-50% reduction, but only after teams understand the source data well enough to make security-relevant filtering decisions.
Questions worth separating out
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.
Q: When does schema normalisation become a lock-in risk for security teams?
A: Schema normalisation becomes lock-in risk when detection logic, parser rules, and dashboards are built around a SIEM-specific model and cannot move without major rework.
Q: What do security teams get wrong about log reduction tools?
A: They often expect automatic savings without first understanding the source data.
Practitioner guidance
- Implement upstream schema ownership Define a canonical security schema outside the SIEM and map source systems into it before data reaches analytics.
- Tier retention by investigative value Separate hot, warm, and cold retention based on how often identity, privilege, and detection teams actually query the data.
- Tune reduction rules by source risk For each log source, document which fields are essential for investigations and which can be dropped safely.
What's in the full article
Axoflow's full article covers the operational detail this post intentionally leaves for the source:
- Concrete examples of how to move from raw log ingestion to upstream classification and normalisation
- Practical guidance on reducing ingestion volume without losing the events needed for investigations
- Discussion of schema portability and how vendor-specific models create long-term rework
- Operational trade-offs involved in long-term retention, cold storage, and queryability
👉 Read Axoflow's analysis of Splunk ingestion costs and security data pipeline design →
Splunk ingestion costs and schema lock-in: what teams should change?
Explore further
19/08/2026 4:20 pm
Security telemetry is now a governance problem, not just a storage problem. When organisations treat the SIEM as the place where data is fixed, shaped, and retained, they also turn telemetry quality into a downstream tax. That tax affects visibility into identity abuse, privilege misuse, and NHI behaviour because investigation quality depends on the structure of the data before it reaches the search layer. Practitioners should treat telemetry governance as part of security architecture, not a back-office logging task.
A question worth separating out:
Q: What should teams do first before extending log retention for years?
A: They should calculate the full storage footprint, then decide which event classes truly justify long-term retention. For identity and security teams, the key question is whether the data will be searched, correlated, or only preserved for compliance. If it will not support a real use case, it should not be stored at premium cost.
👉 Read our full editorial: Security data pipelines can cut Splunk ingest costs and lock-in
