
Revolutionizing AIOps: Why eBPF-Powered Thread-Level Insights Are the Future of Root Cause Analysis
eBPF SREAgent rootcause
Explore the latest technology trends, best practices, and industry insights to fuel your technical growth journey.
eBPF SREAgent rootcause
In the world of AI-driven software engineering, product differentiation often emerges from the problems being solved rather than the technologies being used. This divergence is evident in both the AI coding and SRE domains.
Over the past two years, large language models (LLMs) have begun to land in the observability space. Projects like ITBench SRE Agent and OpenDerisk are exploring automated Root Cause Analysis (RCA): feeding metrics, traces, and logs from distributed systems into a model that infers “which host, which service, which call chain” is most likely the root cause.
Root cause analysis has always been the hardest part of incident response. Traditional observability tools often drown engineers in data without clear direction. Syncause combines AI reasoning with eBPF-powered causal signals to cut through the noise, helping teams restore services faster and with greater confidence.
The AI Agent Market will expand to USD 42.7 billion by 2030 according to the latest research by MarkNtel Advisors. AI Agents are widely predicted to be the next big wave, and we’re already seeing them applied in Observability and DevOps—especially for incident management and root cause analysis (RCA). Since we’re also building a product in this space, this article is both our research notes and an open conversation with the community.
Over the past few months, we’ve been working on something new: an AI Agent designed to help SRE and DevOps teams diagnose incidents more efficiently.
Observability was meant to empower engineering teams with clarity and speed. Yet in 2025, many organizations find themselves drowning in tools, overwhelmed by noise, and facing rising costs.
eBPF SREAgent rootcause