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pith:2026:COR2NDBQOMBX6YUYCLO5UXQDFL
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Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety

Jon Crowcroft, Muhammad Bilal, Ruizhi Wang, Schahram Dustdar, Xiaolong Xu

Operational reliability in LLM-based NetOps and AIOps comes from the machinery around the model rather than the model itself.

arxiv:2605.12729 v1 · 2026-05-12 · cs.NI · cs.AI · cs.CR

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Claims

C1strongest claim

Operational reliability does not come chiefly from the model itself. It depends on the machinery around the model.

C2weakest assumption

That a consistent pattern appears across work on telemetry query recommendation, diagnosis, root-cause analysis, configuration synthesis, change planning, and limited self-healing that can be usefully organized around the hierarchy of autonomy, tool scope, evidence traces, and assurance contracts.

C3one line summary

A literature survey organizing LLM agent work for NetOps and AIOps around autonomy hierarchies, workflow evaluation, and safety contracts.

References

170 extracted · 170 resolved · 1 Pith anchors

[1] A general approach to network configuration analysis, 2015
[2] Header space analysis: Static checking for networks, 2012
[3] VeriFlow: Verifying Network-Wide invariants in real time, 2013
[4] N. R. Murphy, B. Beyer, C. Jones, and J. Petoff,Site Reliability Engineering: How Google Runs Production Systems. O’Reilly Media, 2016. 44 2016
[5] N. Forsgren, J. Humble, and G. Kim,Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations. IT Revolution Press, 2018 2018
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First computed 2026-05-18T03:09:49.272596Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

13a3a68c3073037f629812ddda5e032ac2f14d94565f1176f84cbe7d0623ab36

Aliases

arxiv: 2605.12729 · arxiv_version: 2605.12729v1 · doi: 10.48550/arxiv.2605.12729 · pith_short_12: COR2NDBQOMBX · pith_short_16: COR2NDBQOMBX6YUY · pith_short_8: COR2NDBQ
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/COR2NDBQOMBX6YUYCLO5UXQDFL \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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