Intel Corporation

Teck Joo Goh

Kshitij Arun Doshi

Ravi L Sahita

Andrew J Herdrich

Rameshkumar G Illikkal

Andrzej Kuriata

David M Durham

Mohan J Kumar

Baiju V Patel

Qian Li

Ravishankar Iyer

Michael Lemay

Sara S Baghsorkhi

Jr-Shian Tsai

Vadim Sukhomlinov

Alexander Bachmutsky

Mingqiu Sun

Ian M Steiner

Mona Vij

Slawomir Putyrski

Jeffrey D Chamberlain

Nilesh K Jain

Eric Dahlen

Mohammad R Haghighat

Mingwei Zhang

Amin Firoozshahian

Yeluri Raghuram

Dmitry Babokin

Anil Rao

Krishna Bhuyan

Leeor Peled

Samuel Ortiz

Anjo Lucas Vahldiek-Oberwagner

Haidong Xia

Harshad S Sane

Areg Melik-Adamyan

Wenhui Shu

Michael Prinke

Anup Mohan

Daniel Richins

Mihai Daniel Dodan

Dharmisha Ketankumar Doshi

Dayeol Lee

Jinshi Chen

Mourad Cherfaoui

Wenyong Huang

Long Cui

Anna Drewek-Ossowicka

Mihai-Daniel Dodan

Various approaches to efficiently allocating and utilizing hardware resources in data centers while maintaining compliance with a service level objective (SLO) specified for a computational workload is translated into a hardware-level SLO to facilitate direct enforcement by the hardware processor, e.g., using a feedback control loop or model-based mapping of the hardware-level SLO to allocations of microarchitecture resources of the processor. In some embodiments, a computational model of the hardware behavior under resource contention is used to predict the application performance (e.g., as measured in terms of the hardware-level SLO) to be expected under certain contention scenarios. Scheduling of workloads among the compute nodes within the data center may be based on such predictions. In further embodiments, configurations of microservices are optimized to minimize hardware resources while meeting a specified performance goal.

Efficient resource allocation for service level compliance

In function-as-a-service (FaaS) environments, a client makes use of a function executing within a trusted execution environment (TEE) on a FaaS server. Multiple tenants of the FaaS platform may provide functions to be executed by the FaaS platform via a gateway. Each tenant may provide code and data for any number of functions to be executed within any number of TEEs on the FaaS platform and accessed via the gateway. Additionally, each tenant may provide code and data for a single surrogate attester TEE. The client devices of the tenant use the surrogate attester TEE to attest each of the other TEEs of the tenant and establish trust with the functions in those TEEs. Once the functions have been attested, the client devices have confidence that the other TEEs of the tenant are running on the same platform as the gateway.

Scalable attestation for trusted execution environments

Embodiments of systems, apparatuses and methods provide enhanced function as a service (FaaS) to users, e.g., computer developers and cloud service providers (CSPs). A computing system configured to provide such enhanced FaaS service include one or more controls architectural subsystems, software and orchestration subsystems, network and storage subsystems, and security subsystems. The computing system executes functions in response to events triggered by the users in an execution environment provided by the architectural subsystems, which represent an abstraction of execution management and shield the users from the burden of managing the execution. The software and orchestration subsystems allocate computing resources for the function execution by intelligently spinning up and down containers for function code with decreased instantiation latency and increased execution scalability while maintaining secured execution. Furthermore, the computing system enables customers to pay only when their code gets executed with a granular billing down to millisecond increments.

Function as a service (FaaS) system enhancements

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Saratoga, CA, United States of America

Teck Joo Goh