Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systems

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1. Verfasser: Bindschaedler, Laurent
Format: Preprint
Veröffentlicht: 2026
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author Bindschaedler, Laurent
author_facet Bindschaedler, Laurent
contents Microreboot enables fast recovery by restarting only the failing component, but in modern microservices naive restarts are unsafe: dense dependencies mean rebooting one service can disrupt many callers. Autonomous remediation agents compound this by actuating raw infrastructure commands without safety guarantees. We make microreboot practical by separating planning from actuation: a three-agent architecture (diagnosis, planning, verification) proposes typed remediation plans over a seven-action ISA with explicit side-effect semantics, and a small microkernel validates and executes each plan transactionally. Agents are explicitly untrusted; safety derives from the ISA and microkernel. To determine where restart is safe, we infer recovery boundaries online from distributed traces, computing minimal restart groups and ordering constraints. On industrial traces (Alibaba, Meta) and DeathStarBench with fault injection, recovery-group inference runs in 21 ms at P99; typed actuation reduces agent-caused harm by 95% in simulation and achieves 0% harm online. The primary value is safety, not speed: LLM inference overhead increases TTR for services with fast auto-restart.
format Preprint
id arxiv_https___arxiv_org_abs_2604_09963
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systems
Bindschaedler, Laurent
Distributed, Parallel, and Cluster Computing
Artificial Intelligence
Software Engineering
C.4; D.4.5
Microreboot enables fast recovery by restarting only the failing component, but in modern microservices naive restarts are unsafe: dense dependencies mean rebooting one service can disrupt many callers. Autonomous remediation agents compound this by actuating raw infrastructure commands without safety guarantees. We make microreboot practical by separating planning from actuation: a three-agent architecture (diagnosis, planning, verification) proposes typed remediation plans over a seven-action ISA with explicit side-effect semantics, and a small microkernel validates and executes each plan transactionally. Agents are explicitly untrusted; safety derives from the ISA and microkernel. To determine where restart is safe, we infer recovery boundaries online from distributed traces, computing minimal restart groups and ordering constraints. On industrial traces (Alibaba, Meta) and DeathStarBench with fault injection, recovery-group inference runs in 21 ms at P99; typed actuation reduces agent-caused harm by 95% in simulation and achieves 0% harm online. The primary value is safety, not speed: LLM inference overhead increases TTR for services with fast auto-restart.
title Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systems
topic Distributed, Parallel, and Cluster Computing
Artificial Intelligence
Software Engineering
C.4; D.4.5
url https://arxiv.org/abs/2604.09963