Optimizing Distributed Tiered Data Storage Systems with DITIS
S Vasileiadis, M Paraskeva, G Savva… - Proceedings of the …, 2024 - dl.acm.org
S Vasileiadis, M Paraskeva, G Savva, A Efstathiou, ERL Filho, J Shen, L Yang, K Fu…
Proceedings of the VLDB Endowment, 2024•dl.acm.orgModern data storage systems are characterized by a distributed architecture as well as the
presence of multiple storage tiers and caches. Both system developers and operators are
challenged with the complexity of such systems as it is hard to evaluate how a configuration
change will impact the workload or system performance and identify the best configuration to
satisfy some performance objective. DITIS is a new simulator that models the end-to-end
execution of file requests on distributed tiered storage systems that addresses the …
presence of multiple storage tiers and caches. Both system developers and operators are
challenged with the complexity of such systems as it is hard to evaluate how a configuration
change will impact the workload or system performance and identify the best configuration to
satisfy some performance objective. DITIS is a new simulator that models the end-to-end
execution of file requests on distributed tiered storage systems that addresses the …
Modern data storage systems are characterized by a distributed architecture as well as the presence of multiple storage tiers and caches. Both system developers and operators are challenged with the complexity of such systems as it is hard to evaluate how a configuration change will impact the workload or system performance and identify the best configuration to satisfy some performance objective. DITIS is a new simulator that models the end-to-end execution of file requests on distributed tiered storage systems that addresses the aforementioned challenges efficiently without any costly system redeployments. The demonstration will showcase the key functionalities and benefits offered by DITIS, including (i) analyzing workload traces to understand their characteristics and the behavior of the underlying storage system; (ii) running simulations with different configurations to evaluate their impact on performance; and (iii) running optimizations over custom search spaces to find the best configuration that satisfies a given objective.

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