TIDAL recovers temporal phase signals from LLM-derived semantics of provisioning metadata to enable complementary CVD placement, reducing overload frequency by 79.1% on production traces.
The power of prediction: Microservice auto scaling via workload learning,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Flare proposes routing microservice spike load selectively to serverless while keeping steady load on VMs, with claimed minimal integration changes.
citing papers explorer
-
TIDAL: Recovering Temporal Phase for Cloud Block Storage Placement from LLM-Derived Semantics
TIDAL recovers temporal phase signals from LLM-derived semantics of provisioning metadata to enable complementary CVD placement, reducing overload frequency by 79.1% on production traces.
-
Flare: Leveraging Serverless Elasticity to Absorb Microservice Load Spikes
Flare proposes routing microservice spike load selectively to serverless while keeping steady load on VMs, with claimed minimal integration changes.