Why security teams use a security data pipeline
Most teams start with one problem, usually SIEM cost or a migration, but once the pipeline is in place, they are able to solve lots of other security challenges too.
SIEM cost reduction · SIEM migration · SOC efficiency · Security data routing · Security data governance · AI readiness
A security data pipeline reduces SIEM costs
Most SIEMs charge by how much data you send them. A security data pipeline lets you decide what gets sent, so you pay to analyze the data your detections use and store the rest for less.
SIEM cost reduction with a security data pipeline
Who it is for
Teams facing a SIEM renewal, an ingest overage or a new high-volume source.
Where savings come from
Lower daily ingest into the SIEM.
Typical first source
Firewall or Windows event logs, which are high volume and often repetitive.
Why SIEM bills keep growing
SIEM pricing is usually tied to the volume of data ingested, or to the compute used to process it. Log volume grows every year as companies add cloud services, endpoints and SaaS apps.
Much of that volume is created by data that does not need to be sent to the SIEM. Session-end records, health checks and verbose debug fields cost the same to ingest as the events that matter. Firewall logs are often the biggest single source.
How the pipeline cuts ingest and SIEM costs
Measure
Find out which sources and event types make up most of your volume. A few sources usually account for most of it.
Map detections
List the detections you run and the fields each one needs. This tells you what has to stay in the SIEM.
Reduce
Drop events and fields no detection or investigation needs. Summarize high-volume events where a count will do.
Retain the rest
Keep a complete copy of what you took out of the SIEM in storage your team can search in place, so you can send the exact events back when an investigation needs them.
Security data pipeline case studies
Realm Security, which owns this site, builds a SOC-aware security data pipeline. Vensure Employer Solutions, a benefits and payroll provider, used Realm on FortiGate firewall logs going to Sumo Logic. A global consulting firm used Realm on Fortinet and Zscaler logs going to Microsoft Sentinel.
“This is a game-changer for budget-constrained security teams.”
Dwayne Smith, Sr. VP InfoSec and Global CISO, Vensure Employer Solutions
Vensure Employer Solutions
83%
less daily firewall log volume
$254K
saved a year in SIEM cost
Zero
detections lost
Global consulting firm
86%
less Fortinet and Zscaler log volume
Zero
detection gaps
2 days
from proof of concept to confirmed savings
Common questions
Will reducing SIEM data hurt detection?
It can if a reduction rule removes a field a detection depends on. Map your detections to the fields they use first, and only cut data no detection needs.
What happens to data that is not sent to the SIEM?
A well-run pipeline keeps a complete copy outside the SIEM, in object storage, a data lake or a managed retention layer. Check how fast you can search that copy and send the exact events back to the SIEM. Cold archives often need a restore first.
Can I do this inside my SIEM instead?
Partly. Some SIEMs now offer native tools that filter data before ingest. These tools serve only that one SIEM, and they rarely check a cut against your detections.
How much can I save?
It depends on your sources. Firewall logs often shrink the most. The calculator gives a modeled range for your source mix.
A security data pipeline makes SIEM migration easier
Changing SIEMs usually means reconnecting every source and running two systems side by side. A pipeline lets you connect sources once and feed both SIEMs until you are ready to switch.
SIEM migration with a security data pipeline
Who it is for
Teams moving between SIEMs, or adding a second SIEM or data lake.
Main benefit
No need to reconfigure every source for the new platform.
Watch out for
Detections that depend on field names from the old SIEM.
SIEM migrations are harder than they should be (without a security data pipeline)
During a SIEM migration, every data source has to be pointed at the new platform, parsed in the new format and tested and detections have to be rebuilt. Until everything is proven, both systems run in parallel and projects often stall because the collection work alone can take months.
How a security data pipeline helps
Connect sources once
Point sources at the pipeline instead of the SIEM. They stay pointed there after the migration.
Run both SIEMs in parallel
Send the same data to the old and new SIEM, each in the format it expects.
Move in stages
Shift sources, detections and teams over one at a time and compare results side by side.
Easily switch off the old SIEM
When the new platform is proven, stop sending to the old one. No source needs to change.
Common questions
Do I need a pipeline to migrate SIEMs?
No. Many teams migrate without one. A pipeline reduces the collection work and makes running two systems in parallel simpler.
What about detections?
Detections still need to be rewritten for the new SIEM’s query language. Normalizing fields in the pipeline can make that work more consistent.
How long do both SIEMs run side by side?
It varies by team and contract. A pipeline makes the parallel period easier to extend or shorten, because routing is a configuration change.
A security data pipeline improves SOC efficiency
A pipeline stops analysts losing time to messy data with inconsistent field names, missing context and noisy events.
SOC efficiency gains with a security data pipeline
Who it is for
SOC teams with many sources and a growing alert queue.
Main benefit
Consistent, enriched data for analysts and detections.
Related steps
Normalize, enrich, filter.
Bad data takes away analyst time
Vendors often name fields differently i.e one source calls it src_ip, another sourceIPAddress, a third client.address. Detection engineers write the same logic several times over, and analysts translate in their heads during investigations.
Context is often missing too. An alert might name a user or a device but the analyst has to look up who that is and whether it matters.
How a security data pipeline helps boost SOC efficiency
Normalize
Rename fields from every source to one schema, such as OCSF. Detections and searches are written once.
Enrich
Add user, asset and threat-intelligence details to events before they arrive, so the context is already there.
Filter noise
Remove duplicate and routine events so alert queues and searches contain less clutter.
One event, before and after
Raw firewall log
date=2026-09-11 time=10:42:07 devname="fw-edge-01" type="traffic" subtype="forward" action="close" srcip=10.2.4.17 dstip=142.250.72.14 proto=1 service="PING" sentbyte=84 user="j.smith@example.com"
Normalized, redacted and enriched
{
"time": "2026-09-11T10:42:07Z",
"activity": "Network traffic: session closed",
"src_endpoint.ip": "10.2.4.17",
"dst_endpoint.ip": "142.250.72.14",
"connection.protocol": "icmp",
"actor.user.email": "j•••@example.com",
"actor.user.department": "Finance",
// routine event: routed to data lake only
}
Common questions
What is OCSF?
The Open Cybersecurity Schema Framework, an open standard for security event fields. Many pipelines can convert data to it.
Does enrichment slow data down?
Enrichment adds a small amount of processing per event. Check how any product you evaluate handles lookups at your volumes.
A security data pipeline routes data to the right tool
Different tools need different data. A pipeline routes each stream, or part of a stream, to the right destination from one place, so you do not build point-to-point integrations.
Data routing with a security data pipeline
Who it is for
Teams running more than one security tool or storage tier.
Main benefit
One place to decide where every event goes.
Common pattern
Full copy to a data lake, trimmed stream to the SIEM.
What happens to data without a pipeline?
Without a pipeline, each source sends data to each tool separately which makes it hard to add or disconnect tools.
Security data pipeline routing benefits
Tiered storage
Send detection-relevant data to the SIEM and a full copy to low-cost storage.
Tool-specific streams
Send endpoint events to XDR and identity events to an identity threat tool.
Regional routing
Keep data from each region in storage located in that region.
Replay
Send stored data back into the SIEM when an investigation needs it.
Common questions
Can one event go to several destinations?
Yes. The pipeline can copy an event to several destinations and shape each copy differently.
Does routing change the source?
No. Sources send to the pipeline once. Routing rules change in the pipeline only.
A security data pipeline makes compliance easier
Security logs often carry personal and regulated data which needs to be processes and stored differently. A pipeline lets you control where that data goes and mask what should not travel, with one policy across every source.
Compliance with a security data pipeline
Who it is for
Teams with privacy, residency or compliance requirements.
Main benefit
Sensitive values are masked before they reach downstream tools.
Related steps
Redact, route, retain.
Security data and compliance
Logs often contain email addresses, IP addresses, user names and sometimes far more sensitive values that need regulatory compliant handling.
How the pipeline helps orgs stay compliant
Redact
Mask, hash or remove sensitive fields in transit, before any destination stores them.
Route by policy
Send regulated data only to approved destinations and regions.
Retain with purpose
Keep data for as long as your policy requires, in the storage your policy allows.
Record what went where
Keep a record of which rules applied to which data, ready for audits.
Realm example
Realm Privacy Guard uses Realm Clarity AI to find sensitive data in logs, such as health records and card numbers. Privacy Guard masks those fields in stream, with rules that can differ per destination and wait in a pending state until your team approves them. Authorized investigators can retrieve unredacted values from Realm Data Haven.
Common questions
Does redaction affect detections?
It can if a detection relies on the value you mask. Hashing keeps values consistent for matching while hiding the original.
Is a pipeline enough for compliance?
No single tool makes you compliant. A pipeline is one control that helps you apply data handling rules consistently.
Getting security data ready for AI
AI SOC tools and agents are only as good as the data they can reach. Many of them query the SIEM and data lakes where the data already sits. A security data pipeline decides what lands in those places, in what shape and with what context.
At a glance
Who it is for
Teams adopting AI SOC tools, copilots or agents.
Main benefit
Consistent, enriched data that AI tools can reason over.
Related steps
Normalize, enrich, redact, route.
Why AI tools struggle with raw logs
An AI tool reading raw logs meets the same problems an analyst does. Field names are inconsistent, context is missing and there is a lot of noise. It also costs more to run when it processes data it does not need.
Sensitive data is another concern. Teams need to know what personal data an AI tool receives.
How the pipeline helps
One schema
Normalized fields let an AI tool compare events across sources without guessing what each field means.
Context attached
Enriched events carry user, asset and threat-intelligence details, so the tool does not have to look them up.
Less noise
Filtering routine events out of the SIEM lowers processing cost. Keep those events searchable, so agents can still reach them.
Controlled exposure
Redact personal data and route only approved streams to AI tools.
Common questions
Do I need a pipeline to use an AI SOC tool?
No. The tool will work with whatever data it receives. A pipeline improves that data and controls what the tool sees.
Can a pipeline feed AI tools and a SIEM at the same time?
Yes. Routing can send one stream to the SIEM and a differently shaped stream to an AI tool.
Curious? Start a free 7-Day Data Assessment
Try a pipeline on real data from your environment. Realm’s free 7-Day Data Assessment starts with one of your log sources, usually firewall logs. Realm checks every cut against the detections you run. In about a week you get a report on what is safe to cut and what it would save, with detection coverage shown before and after. There is no commitment.