SoftSKU: Optimizing Server Architectures for Microservice Diversity @Scale

The variety and complexity of microservices in warehouse- scale data centers has grown precipitously over the last few years to support a growing user base and an evolving product portfolio. Despite accelerating microservice diversity, there is a strong requirement to limit diversity in underlying s...

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Published in2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA) pp. 513 - 526
Main Authors Sriraman, Akshitha, Dhanotia, Abhishek, Wenisch, Thomas F.
Format Conference Proceeding
LanguageEnglish
Published ACM 01.06.2019
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ISSN2575-713X
DOI10.1145/3307650.3322227

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Abstract The variety and complexity of microservices in warehouse- scale data centers has grown precipitously over the last few years to support a growing user base and an evolving product portfolio. Despite accelerating microservice diversity, there is a strong requirement to limit diversity in underlying server hardware to maintain hardware resource fungibility, preserve procurement economies of scale, and curb qualification/test overheads. As such, there is an urgent need for strategies that enable limited server CPU architectures (a.k.a "SKUs") to provide performance and energy efficiency over diverse microservices. To this end, we first undertake a comprehensive characterization of the top seven microservices that run on the compute-optimized data center fleet at Facebook. Our characterization reveals profound diversity in OS and I/O interaction, cache misses, memory bandwidth utilization, instruction mix, and CPU stall behavior. Whereas customizing a CPU SKU for each microservice might be beneficial, it is prohibitive. Instead, we argue for "soft SKUs", wherein we exploit coarse-grain (e.g., boot time) configuration knobs to tune the platform for a particular microservice. We develop a tool, μSKU, that automates search over a soft-SKU design space using A/B testing in production and demonstrate how it can obtain statistically significant gains (up to 7.2% and 4.5% performance improvement over stock and production servers, respectively) with no additional hardware requirements.
AbstractList The variety and complexity of microservices in warehouse- scale data centers has grown precipitously over the last few years to support a growing user base and an evolving product portfolio. Despite accelerating microservice diversity, there is a strong requirement to limit diversity in underlying server hardware to maintain hardware resource fungibility, preserve procurement economies of scale, and curb qualification/test overheads. As such, there is an urgent need for strategies that enable limited server CPU architectures (a.k.a "SKUs") to provide performance and energy efficiency over diverse microservices. To this end, we first undertake a comprehensive characterization of the top seven microservices that run on the compute-optimized data center fleet at Facebook. Our characterization reveals profound diversity in OS and I/O interaction, cache misses, memory bandwidth utilization, instruction mix, and CPU stall behavior. Whereas customizing a CPU SKU for each microservice might be beneficial, it is prohibitive. Instead, we argue for "soft SKUs", wherein we exploit coarse-grain (e.g., boot time) configuration knobs to tune the platform for a particular microservice. We develop a tool, μSKU, that automates search over a soft-SKU design space using A/B testing in production and demonstrate how it can obtain statistically significant gains (up to 7.2% and 4.5% performance improvement over stock and production servers, respectively) with no additional hardware requirements.
Author Dhanotia, Abhishek
Sriraman, Akshitha
Wenisch, Thomas F.
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Snippet The variety and complexity of microservices in warehouse- scale data centers has grown precipitously over the last few years to support a growing user base and...
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StartPage 513
SubjectTerms Computer architecture
Data centers
Hardware
Microservice
Microservice architectures
Portfolios
Procurement
Production
resource fungibility
Servers
Social networking (online)
soft SKU
Testing
Title SoftSKU: Optimizing Server Architectures for Microservice Diversity @Scale
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