Simple LLM harnesses outdiagnose hand-crafted microservice RCA agents
On 90 RCAtlas cases, simple harnesses reach PR@1 of 65–77% versus 16–53% for published agents.
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On 90 RCAtlas cases, simple harnesses reach PR@1 of 65–77% versus 16–53% for published agents.
The paper is architectural and defers measured results on LogHub and Train-Ticket to a companion study.
DiffTry repurposes microservice retries as stateless prioritization, reducing rejections from incidental and adversarial overloads.
MCRL2 augments reinforcement learning with multi-resource cross-attention representations to improve cloud microservice scheduling and load balancing.
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