If you've already explored the practical steps for implementing a security data fabric, the next step is knowing what to look for in a solution. Whether evaluating a security data fabric platform or reassessing your current logging architecture, asking the right questions upfront will help you avoid wasted time, surprise costs, and brittle integrations. These questions help security teams identify solutions that deliver long-term maintainability, cost-efficiency, and operational alignment.
1) How long will it take to deploy, and who needs to be involved?
Some SIEMs and data pipeline tools require extensive professional services, months of planning, or dedicated developers to set up filtering and routing logic. If you’re working with a lean security team, that lift may be unsustainable.
Look for platforms designed for deployment and maintenance by security engineers, not just data pipeline specialists. A strong solution should allow you to connect sources, define destinations, and apply routing rules without writing custom code or creating a full-blown project team.
Pro Tip: A straightforward, low-effort process for connecting log sources, applying filters, and routing data is a good indicator of long-term usability. If a platform makes these tasks feel complex or resource-intensive, it may add operational overhead over time.
2) Will we have to build and maintain filtering logic ourselves?
Solutions that rely heavily on regular expressions, custom scripts, or log parsing templates often break when a source changes format or behavior. Maintaining those rules is a hidden time cost that only grows with every additional source or use case.
Instead, look for platforms that offer built-in normalization, preconfigured filtering templates, and a UI-driven experience for tuning log flows. This helps reduce reliance on tribal knowledge and aligns your routing logic with actual detection and compliance needs. For a closer look at how smart filtering and routing logic can improve signal quality and reduce SIEM costs, explore our breakdown on how a security data fabric helps streamline detection .
Pro Tip: Ask to see how filtering logic is created and updated. If it’s regex in YAML, consider how that scales when you have 50+ log sources to manage.
3) What’s the ongoing maintenance overhead?
Log pipelines don’t fail loudly; they fail silently. Missed logs, dropped events, or broken integrations often go unnoticed until something critical is missing during an incident.
Make sure the platform includes:
Solutions that monitor their health and proactively flag issues can save hours during an investigation or audit.
Pro Tip: Ask how the platform alerts you when logs from a key source stop arriving, or when a destination fails to ingest. If there isn’t a clear answer to this question or a built-in mechanism, it may be a sign that the platform relies too heavily on manual oversight.
4) Is the platform secure and compliant?
Any system that touches your security telemetry must follow rigorous security and privacy standards. If you’re moving log processing to a third party or cloud service, ensure they are:
Make sure the platform includes:
You should also confirm that the platform doesn’t store sensitive logs beyond what’s necessary for routing or monitoring.
Pro Tip: Ask where log data is processed and stored, how long it’s retained, and whether it’s used for internal analytics. Security data should stay in your control.
5) Does it integrate cleanly with our existing stack?
You likely already have dozens of log-producing tools, firewalls, endpoints, cloud accounts, identity providers, and multiple destinations like a SIEM, XDR, MDR, or archive. You shouldn’t have to build every integration yourself.
Look for solutions with broad out-of-the-box support for popular sources and destinations, and flexible options for custom connectors.
Pro Tip: Check whether new integrations require software agents or custom development. Lightweight connectors or agentless ingestion can save time and avoid footprint bloat.
6) What’s the true cost to run it now and 12 months from now?
Finally, make sure you understand the total cost of ownership. That includes:
Look for solutions with broad out-of-the-box support for popular sources and destinations, and flexible options for custom connectors.
In most cases, a good security data fabric should pay for itself quickly by cutting SIEM ingestion volume by 40–70% . But only if it’s deployed efficiently and used to re-route your data.
Pro Tip: Model your top 3 log sources and estimate cost savings from filtering or rerouting. If the platform doesn’t help you visualize or simulate ROI, ask why not.
Security teams can use these questions to define an architecture that fits their team’s size, skill set, and compliance requirements. This framework is meant to help security teams gain more control over data flows, reduce log volume and costs, and maintain strong detection coverage. To see how Realm.Security supports this approach, request a demo and explore what the platform can do for your environment.