eBPF Replaces "User-Space Agents": Designing Runtime Security Observability for Clients in 2026

On May 19, 2026, InfoQ published Kernel-Level Ground Truth: Why eBPF is Replacing User-Space Agents for Security Observability. eBPF (extended Berkeley Packet Filter) is a sandbox that allows small programs to be safely injected into the Linux kernel, enabling direct observation of system calls, network traffic, and file operations from kernel space. As a result, it is resilient against bypassing, disabling, and tampering—weaknesses of traditional user-space EDR and security agents (such as CrowdStrike, SentinelOne, and Sysdig)—and has rapidly emerged as a next-generation runtime monitoring foundation that limits performance overhead to around 1% to 3%.

For teams supporting production security for mid-market clients through custom development, this means architecting solutions to fill "the blind spots of user-space EDR" is becoming the new competitive frontier. Following our earlier coverage of deployment-focused eBPF adoption in GitHub eBPF Deployment Safety DevOps, transitioning security observability to eBPF is moving into the mainstream. This article outlines the key considerations when designing eBPF runtime security observability and SOC integration in client engagements.

Why eBPF Is Replacing "User-Space EDR"

In short, eBPF provides the path closest to ideal security observability: undetectable by monitored targets, impervious to bypass, and lightweight.

Three Structural Shifts Driven by eBPF

Shift 1: From "Commercial EDR Dominance" to "eBPF + Commercial Hybrid"

Historically, production runtime monitoring was the exclusive domain of CrowdStrike, SentinelOne, and Carbon Black. With the maturation of eBPF tools like Cilium Tetragon, Falco, and Pixie, a hybrid architecture combining core observability via eBPF with advanced threat analytics via commercial tools has become a practical reality. This also directly leads to substantial reductions in EDR licensing fees.

Shift 2: From "Single Cloud" to "Unified Cloud and On-Premises Observability"

Because eBPF is a kernel feature, the exact same instrumentation code runs across AWS, GCP, Azure, on-premises Linux, and Kubernetes. In custom development engagements, it can be proposed as a "unified observability foundation for hybrid and multi-cloud environments." This achieves its full potential when paired with AWS Interconnect Multi-Cloud Custom Development.

Shift 3: From "Siloed Security" to "Unified Security, Performance, and Cost Observability"

eBPF can collect security events, performance profiles, and resource costs across the same instrumentation layer. In client development, we architect "unified security, performance, and FinOps observability" by pairing it with Pyroscope (Continuous Profiling Custom Development).

Five Phases of Designing eBPF Runtime Security Observability + SOC Integration for Clients

Phase 1: Current state assessment (2 weeks)

• Inventory of existing EDR and security agents
• Linux kernel version verification (5.10+ recommended)
• Assessing the scale of Kubernetes and container environments
• Confirming integration feasibility with existing SIEM / SOC vendors
• Organizing security requirements (PCI, SOC 2, ISMS)

Phase 2: eBPF Stack Design (1 to 2 Weeks)

• Detection layer: Cilium Tetragon / Falco
• Network observability: Cilium / Pixie
• Performance integration: Pyroscope / Parca
• Export destinations: OpenTelemetry → SIEM (Splunk / Wazuh / Elastic)
• Ruleset design (aligned with CIS Benchmark and MITRE ATT&CK)
• Division of responsibilities with commercial EDR

Phase 3: Phased Rollout (3 to 5 Weeks)

• Deployment to test environments + performance evaluation
• Tuning detection rules (reducing false positives)
• Phased production rollout
  • Week 1: Development environment
  • Week 2: Staging
  • Weeks 3–4: Production canary → Full production
• Parallel operation with existing EDR → Phased replacement

Phase 4: SOC Integration + 24/7 Monitoring (2 to 3 Weeks)

• Aggregating alerts into SIEM
• Severity-based notification rules (PagerDuty / Slack / Email)
• Incident response runbooks
• Monthly threat report formatting
• Agreeing on escalation criteria with client SOC

Phase 5: Monthly operational reviews (ongoing)

• Detection counts / false positive rate / mean response time
• Kernel program and ruleset updates
• Tracking new MITRE ATT&CK TTPs
• Re-measuring performance overhead
• Submitting threat reports to client SOC

Standard technology stack set for custom development

Which projects need this and which do not

Six clauses to include in client contracts

Client ROI Projection (Assuming 80 Nodes / 3 Clusters / Existing EDR Usage)

Even when converting audit compliance hours at 8,000 yen per hour, the vast majority of cost benefits stem from reduced EDR licensing fees and incident losses. Because the design and implementation costs of transitioning to a hybrid architecture vary significantly based on environment scale (cluster counts, node counts, SIEM integration scope), it is prudent to plug your own figures into this model to estimate the payback period upfront.

Five common pitfalls

Pitfall 1: "Canceling Commercial EDR Immediately After Introducing eBPF"

While eBPF excels at foundational observability, commercial EDR holds an advantage in advanced threat analysis and threat intelligence. A phased hybrid approach leading to partial replacement is the pragmatic strategy.

Pitfall 2: Deploying Without Checking Kernel Versions

eBPF requires Linux 5.10+ for stable, comprehensive functionality. Older kernels (like CentOS 7 or RHEL 7) introduce numerous limitations, so implementation should proceed alongside an OS upgrade plan.

Pitfall 3: Running with Public Default Rulesets

The public default rules in Falco and Tetragon tend to produce elevated false positives. Tuning tailored to the client's environment is necessary, with the initial one to two months focused on reducing false positives.

Pitfall 4: Settling for Merely Ingesting Logs into SIEM

Simply piping eBPF events into a SIEM yields little value if the SOC lacks a triage structure to act on detections. Integrate SOC alignment and operational runbooks into the initial architecture.

Pitfall 5: Postponing Performance Validation

Although eBPF overhead is generally low, it can become noticeable under specific workloads (high QPS, massive syscall volumes). Make load testing prior to production rollout mandatory.

90-day action plan

Summary — The Era Where "Kernel-Level Ground Truth" Becomes Standard

Runtime security observability powered by eBPF delivers "kernel-level ground truth" that transcends the limits of user-space EDR to mid-market enterprises. For teams supporting production security through custom development, an integrated approach encompassing eBPF stack architecture, hybrid commercial EDR integration, SOC collaboration, and monthly reviews is becoming the industry standard.

The approach to architecting an eBPF observability foundation and executing a phased migration from existing EDR varies entirely depending on kernel versions, cluster scale, and existing SIEM and SOC frameworks. Whether your concerns involve "ballooning EDR license costs," "improving observability precision in container environments," or "unifying multi-cloud security monitoring," we provide custom estimates based on your environment. Please feel free to reach out through our contact form.

Sources

• Kernel-Level Ground Truth: Why eBPF is Replacing User-Space Agents for Security Observability（InfoQ）
• GitHub eBPF Deployment Safety DevOps Custom Development (GH Media)
• Continuous Profiling for Clients with Pyroscope 2 (GH Media)
• AWS Interconnect Multi-Cloud Custom Development (GH Media)
• Productizing AI Security Audit Services (GH Media)