Configurable Runtime Orchestration for Dynamic Data Retrieval in Distributed Systems
2026-03-10T08:52:29Z•d530b86eb9667a8f78c57f8aa0231ec243e1bca463448772afcf5c79bbd85f99
AIReSimagentic-aiai-cluster-reliabilityapache-airflowautoscaling','kubernetes'','mas-h2'','codeco'','edge-cloud'','moavailabilityaws-step-functionscapacity-planningcustomer-360dependency-aware-schedulingdistributed-orchestrationfailover-architecturellm-enhancedlow-latencymicroservicesmulti-agent-systemsnetwork-semanticsopen-atomic-ethernetrdmaruntime-configurationsimulatortemporaluav-networksuber-ufaworkflow-orchestration
What happened
This document is an aggregated arXiv feed (multiple new submissions) covering systems and infrastructure research: a configuration-driven runtime orchestration framework for dynamic data retrieval in distributed microservice environments; AIReSim, a discrete-event simulator for large-scale AI cluster reliability and capacity planning; Uber's differentiated Failover Architecture to reduce steady-state provisioning while preserving availability; a critique of current interconnect stacks and a proposal (Open Atomic Ethernet) to resolve RDMA/link semantic fragmentation; an Agentic AI + game-theory
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- d530b86eb9667a8f78c57f8aa0231ec243e1bca463448772afcf5c79bbd85f99
- Enrichment time
- 2026-03-10T08:52:29Z
- AI-assisted enrichment
- Yes
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