HyperFlux is presented, a commodity-KVM ultralight VM substrate that makes a VM's parallelism width (the number of physical cores backing it) elastic at runtime, and it is shown that HyperFlux can move a core across VMs in merely 13$\mu$s, even when forcibly reclaiming it from a busy donor, orders of magnitude faster than vCPU hot-plug.
Abstract
Serverless platforms commonly colocate many diverse workloads, each in a fast-booting, memory-lean virtual machine (VM), to improve deployment density. Overprovisioning each VM for its peak protects tail latency during traffic bursts but hurts density; maintaining high density while effectively protecting tail latency requires the infrastructure to be able to shift physical cores, at a microsecond timescale, to whichever latency-sensitive VM is bursting and reclaim them as the burst subsides. No VM substrate delivers this: conventional VMs resize a guest's cores only through a millisecond-scale vCPU hot-plug path, Firecracker fixes a VM's core count at boot, and the ultralight VMs that boot fastest drop multicore execution entirely. We present HyperFlux, a commodity-KVM ultralight VM substrate that makes a VM's parallelism width (the number of physical cores backing it) elastic at runtime. We show that HyperFlux can move a core across VMs in merely 13$\mu$s, even when forcibly reclaiming it from a busy donor, orders of magnitude faster than vCPU hot-plug. A HyperFlux VM incurs only a 3.2MB memory footprint and can cold-boot in 1.37ms, on par with the fastest-booting ultralight VMs, while uniquely supporting multicore parallelism. Under colocation, it can reduce high-priority VMs'tail latency by up to 10x under high load compared to static core-sharing with Firecracker and Cloud Hypervisor, and deliver a lower and more stable tail latency compared to using cgroup and vCPU hot-plug under changing load bursts.
Dedicated VMs provide near bare-metal performance through CPU pinning, interrupt passthrough, and idle passthrough. In conventional deployments, however, these optimizations lock physical cores to individual VMs and prevent CPU sharing. In one of the world's largest cloud platforms, 74% of Dedicated VMs average below 1...
Yun Wang, Xing-Guo Jia, Ben Luo et al.· Proceedings of the ACM SIGOP...· 0 citations
For serverless applications, it is the de facto standard to use virtual machines (VMs) to ensure that each customer's workload is properly isolated from others. However, VMs and Virtual Machine Managers (VMMs) separately incur a high overhead in terms of startup latency and computation due to OS duplication and device...
Jonathan Klimt, Sarah Simon, Martin Kröning et al.· Proceedings of the 14th Work...· 0 citations
MRT generates memory restoration templates from the learned sequence of pages that incur page faults during a warm start and uses them to bulk-restore pages using Intel's In-Memory Analytics Accelerator (IAA), avoiding costly on-demand faults.
Aravinda Prasad, S. Subramoney, Sandeep Kumar et al.· Proceedings of the 4th Works...· 0 citations
Confidential serverless computing is rapidly emerg- ing as a critical paradigm for application domains requiring strong confidentiality guarantees, such as healthcare, finance, and machine learning. To enable this paradigm in untrusted cloud environments, Confidential Virtual Machines (CVMs) provide isolation by encryp...
PANEM is presented, a lightweight event-driven heuristic model that has guided four generations of commercial server-core development at Ampere Computing and shows that a calibrated, contention-aware abstraction can deliver practical predictive value for industrial design-space exploration at simulation costs similar t...
Framework and runtime selection for containerized microservices are usually guided by request-level benchmarks, yet deployment-facing costs often dominate operational expenditure in Kubernetes environments. This study empirically evaluates four such infrastructure characteristics: container image size, startup time, id...
Matej Šarić, Aleksander Radovan, D. Kučak· Applied Sciences· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.