Linnix
eBPF observability that predicts failures before they happen
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I kept missing incidents until it was too late. By the time my monitoring alerted me, servers/nodes were already unrecoverable.So I built Linnix. It watches your Linux systems at the kernel level using eBPF and tries to catch problems before they cascade into outages.The idea is simple: instead of alerting you after your server runs out of memory, it notices when memory allocation patterns look weird and tells you "hey, this looks bad."It uses a local LLM to spot patterns. Not trying to build AGI here - just pattern matching on process behavior. Turns out LLMs are actually pretty good at this.Example: it flagged higher memory consumption over a short period and alerted me before it was too late. Turned out to be a memory leak that would've killed the process.Quick start if you want to try it: docker pull ghcr.io/linnix-os/cognitod:latest docker-compose up -d Setup takes about 5 minutes. Everything runs locally - your data doesn't leave your machine.The main difference from tools like Prometheus: most monitoring parses /proc files. This uses eBPF to get data directly from the kernel. More accurate, way less overhead.Built it in Rust using the Aya framework. No libbpf, no C - pure Rust all the way down. Makes the kernel interactions less scary.Current state: - Works on any Linux 5.8+ with BTF - Monitors Docker/Kubernetes containers - Exports to Prometheus - Apache 2.0 licenseStill rough around the edges. Actively working on it.Would love to know: - What kinds of failures do you wish you could catch earlier? - Does this seem useful for your setup?GitHub: https://github.com/linnix-os/linnixHappy to answer questions about how it works.
HN · launched Nov 11, 2025 · 21 upvotes (top 30%) · 1 view
Niche: software observability platforms · 89 launches, 0 in the last 7 days ▼ -100% · Explore this niche →
Category and tags
- Horizontal
- Observability & eval
- Developer
- AI feature
- Commercial product
Visit website ↗ Source listing ↗
More like this: all 89 launches in software observability platforms →
Could you build this?
No Writing eBPF kernel probes for system-level telemetry and building low-latency predictive outage detection requires deep Linux kernel internals, systems programming, and high-throughput time-series analysis.
What it would actually take: The product requires writing C-based eBPF programs loaded via libbpf or Aya into the Linux kernel to trace low-level events (syscalls, scheduler latency, page faults, TCP retransmits) with minimal CPU overhead. A native userspace daemon (written in Rust or Go) processes the perf/ring buffers, aggregates metrics, and feeds high-frequency telemetry into an anomaly detection engine trained on pre-failure kernel metrics. It requires deep Linux kernel systems expertise, eBPF verifier navigation, and high-performance real-time streaming architectures.
Discussion
6 comments analyzed.
Competitors mentioned: Prometheus, Cloudflare's Prometheus exporter for eBPF
Concerns raised: Documentation appears AI-generated without human review/editing, AI part is experimental and hit-or-miss depending on model, Not production-tested at scale, Running inference on CPU without GPU or API reliability, Unclear how thoroughly software has been reviewed and tested
Feature requests: Real-world examples with performance numbers under load
Competitors
Other products that read as similar to this one : 201 launches clear the similarity bar, closest 8 shown.
Attention rank: #83 of 202 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 12 days after the earliest competitor.
- Cerberus · hn · 2025-12-20 · 12 upvotes · similarity 0.58
- DOOM in the kernel, or fibers in eBPF · hn · 2026-09-09 · 53 upvotes · similarity 0.53
- Dsnitch · hn · 2026-09-06 · 5 upvotes · similarity 0.47
- Deft-Intruder · hn · 2025-11-25 · 6 upvotes · similarity 0.46
- Torrix, self hosted, LLM Observability,(no Postgres, no Redis) · hn · 2026-05-13 · 74 upvotes · similarity 0.45
- Lumina · hn · 2026-01-25 · 6 upvotes · similarity 0.45
- BetterDB · hn · 2026-01-23 · 6 upvotes · similarity 0.43
- AIOStack · hn · 2026-01-14 · 9 upvotes · similarity 0.42
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