The cybersecurity threat landscape has fundamentally changed. Attackers have become stealthier, more strategic, and increasingly reliant on automation and AI. Yet, many organizations—particularly MSPs and MSSPs supporting small and mid-market businesses—are still relying on security tools priced and architected for a different era.
One of the biggest constraints holding back effective threat detection and response? Volume-based data ingestion models—a staple of traditional SIEMs that charge by events per second (EPS) or gigabytes of data stored.
While once a reasonable way to measure consumption, today, this pricing model has become a barrier to visibility, compliance, and security outcomes.
Modern cyberattacks are rarely loud or immediate. Threat actors increasingly use “low and slow” tactics to evade detection—moving laterally, testing defenses, and exfiltrating data in small, undetectable drips over time.
But when organizations are charged based on the volume of ingested data, they’re often forced to make hard decisions: Which logs do we retain? Which telemetry gets filtered? Which endpoints aren’t worth the cost of monitoring?
The result? Blind spots.
This is exactly what modern attackers are counting on.
There’s no shortage of tools offering AI-powered threat detection. But here’s the truth: AI is only as good as the data it sees.
Machine learning thrives on behavioral baselines, anomaly detection, and cross-domain correlation. If endpoint logs are limited, user behavior isn’t captured, or network activity is filtered—AI loses the ability to detect the nuanced patterns behind modern attacks.
Consider insider threats. Or credential misuse that unfolds over weeks. Or subtle signs of data exfiltration. These aren’t the kinds of threats that generate EPS spikes or flashy alerts. They emerge slowly, often requiring multiple data points to connect the dots.
Limiting data for cost reasons doesn’t just reduce noise. It cuts off the signals that matter most.
From GDPR to PCI DSS, HIPAA to CCPA, today’s compliance frameworks require more than just best-effort security—they demand comprehensive, auditable data retention and analysis.
But when every gigabyte costs more, organizations often trim logs to stay within budget. That introduces real risk:
For MSPs and MSSPs managing compliance on behalf of clients, this risk is magnified. And when security and compliance are pitted against cost constraints, no one wins.
Here’s the paradox of volume-based security pricing: The moment you need full visibility—during an incident—is often when costs spike the most.
A DDoS attack, ransomware outbreak, or malware propagation event can generate a surge in logs across network, endpoint, and cloud systems. But if that surge pushes an organization over its licensed EPS or storage limit?
They face a tough choice: accept exorbitant overage fees or suppress logs and lose visibility—right when every second and every signal counts.
For MSPs and MSSPs responsible for maintaining service level agreements and incident response capabilities, this is an unacceptable trade-off.
Security leaders know that real protection requires continuous visibility, behavioral analytics, and context-aware detection. However, traditional pricing structures actively discourage these best practices.
That’s why more organizations are exploring alternatives to volume-based ingestion models. Pricing strategies that align to users, assets, or infrastructure coverage—rather than data volume—allow for:
These models don’t just reduce complexity—they empower better outcomes by removing artificial limits on data collection and analysis.
MSPs and MSSPs have a tough job. They’re expected to deliver enterprise-grade cybersecurity for clients who are price-sensitive, compliance-bound, and often under attack.
To do that well, they need tools and platforms that encourage full visibility, not penalize it. They need analytics engines that thrive on data, not struggle with gaps. And they need pricing models that scale with their business, not against it.
The fight against modern threat actors doesn’t leave room for data rationing. Visibility can’t be optional. And log suppression can’t be part of your playbook.
If your security posture is being shaped more by licensing models than by risk strategy, it might be time to reconsider your approach.
Modern threats require modern visibility. And that starts with removing the cost barriers to collecting the data that matters most.
