29 lines
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29 lines
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<!doctype html><html lang=en dir=auto data-theme=auto><head><meta charset=utf-8><meta http-equiv=X-UA-Compatible content="IE=edge"><meta name=viewport content="width=device-width,initial-scale=1,shrink-to-fit=no"><meta name=robots content="index, follow"><title>EuroSys 2024 Digest | Publish Assistant</title><meta name=keywords content><meta name=description content="13 papers selected.
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Pronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts
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Sumer Kohli, Shreyas Kharbanda, Rodrigo Bruno, João Carreira et al.
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TL;DR — Demonstrates how carefully orchestrated checkpointing can eliminate cold-start latency in serverless runtimes, achieving near-instant hot-starts with negligible overhead.
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Serialization/Deserialization-free State Transfer in Serverless Workflows
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Fangming Lu, Xingda Wei, Zhuobin Huang, Rong Chen 0001 et al.
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TL;DR — Eliminates the dominant serialization cost in serverless function chaining by enabling direct in-memory state passing, yielding large end-to-end latency reductions."><meta name=author content="Publish Assistant"><link rel=canonical href=https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/digests/eurosys-2024/><link crossorigin=anonymous href=/vincent/publish-assistant/assets/css/stylesheet.d72f07832e13c592b3edba91680bfe70f01daac396179bcace0ac36e8e0494c6.css integrity="sha256-1y8Hgy4TxZKz7bqRaAv+cPAdqsOWF5vKzgrDbo4ElMY=" rel="preload stylesheet" as=style><link rel=icon href=https://pub.sqrt.fr/vincent/publish-assistant/favicon.ico><link rel=icon type=image/png sizes=16x16 href=https://pub.sqrt.fr/vincent/publish-assistant/favicon-16x16.png><link rel=icon type=image/png sizes=32x32 href=https://pub.sqrt.fr/vincent/publish-assistant/favicon-32x32.png><link rel=apple-touch-icon href=https://pub.sqrt.fr/vincent/publish-assistant/apple-touch-icon.png><link rel=mask-icon href=https://pub.sqrt.fr/vincent/publish-assistant/safari-pinned-tab.svg><meta name=theme-color content="#2e2e33"><meta name=msapplication-TileColor content="#2e2e33"><link rel=alternate hreflang=en href=https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/digests/eurosys-2024/><noscript><style>#theme-toggle,.top-link{display:none}</style><style>@media(prefers-color-scheme:dark){:root{--theme:rgb(29, 30, 32);--entry:rgb(46, 46, 51);--primary:rgb(218, 218, 219);--secondary:rgb(155, 156, 157);--tertiary:rgb(65, 66, 68);--content:rgb(196, 196, 197);--code-block-bg:rgb(46, 46, 51);--code-bg:rgb(55, 56, 62);--border:rgb(51, 51, 51);color-scheme:dark}.list{background:var(--theme)}.toc{background:var(--entry)}}</style></noscript><script>localStorage.getItem("pref-theme")==="dark"?document.querySelector("html").dataset.theme="dark":localStorage.getItem("pref-theme")==="light"?document.querySelector("html").dataset.theme="light":window.matchMedia("(prefers-color-scheme: dark)").matches?document.querySelector("html").dataset.theme="dark":document.querySelector("html").dataset.theme="light"</script><meta property="og:url" content="https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/digests/eurosys-2024/"><meta property="og:site_name" content="Publish Assistant"><meta property="og:title" content="EuroSys 2024 Digest"><meta property="og:description" content="13 papers selected.
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Pronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts Sumer Kohli, Shreyas Kharbanda, Rodrigo Bruno, João Carreira et al.
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TL;DR — Demonstrates how carefully orchestrated checkpointing can eliminate cold-start latency in serverless runtimes, achieving near-instant hot-starts with negligible overhead.
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Serialization/Deserialization-free State Transfer in Serverless Workflows Fangming Lu, Xingda Wei, Zhuobin Huang, Rong Chen 0001 et al.
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TL;DR — Eliminates the dominant serialization cost in serverless function chaining by enabling direct in-memory state passing, yielding large end-to-end latency reductions."><meta property="og:locale" content="en_us"><meta property="og:type" content="article"><meta property="article:section" content="cloud-edge"><meta property="article:published_time" content="2024-01-01T00:00:00+00:00"><meta property="article:modified_time" content="2024-01-01T00:00:00+00:00"><meta name=twitter:card content="summary"><meta name=twitter:title content="EuroSys 2024 Digest"><meta name=twitter:description content="13 papers selected.
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Pronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts Sumer Kohli, Shreyas Kharbanda, Rodrigo Bruno, João Carreira et al.
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TL;DR — Demonstrates how carefully orchestrated checkpointing can eliminate cold-start latency in serverless runtimes, achieving near-instant hot-starts with negligible overhead.
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Serialization/Deserialization-free State Transfer in Serverless Workflows Fangming Lu, Xingda Wei, Zhuobin Huang, Rong Chen 0001 et al.
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TL;DR — Eliminates the dominant serialization cost in serverless function chaining by enabling direct in-memory state passing, yielding large end-to-end latency reductions."><script type=application/ld+json>{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Edge and Cloud Systems","item":"https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/"},{"@type":"ListItem","position":2,"name":"Digests","item":"https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/digests/"},{"@type":"ListItem","position":3,"name":"EuroSys 2024 Digest","item":"https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/digests/eurosys-2024/"}]}</script><script type=application/ld+json>{"@context":"https://schema.org","@type":"BlogPosting","headline":"EuroSys 2024 Digest","name":"EuroSys 2024 Digest","description":"13 papers selected.\nPronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts Sumer Kohli, Shreyas Kharbanda, Rodrigo Bruno, João Carreira et al.\nTL;DR — Demonstrates how carefully orchestrated checkpointing can eliminate cold-start latency in serverless runtimes, achieving near-instant hot-starts with negligible overhead.\nSerialization/Deserialization-free State Transfer in Serverless Workflows Fangming Lu, Xingda Wei, Zhuobin Huang, Rong Chen 0001 et al.\nTL;DR — Eliminates the dominant serialization cost in serverless function chaining by enabling direct in-memory state passing, yielding large end-to-end latency reductions.\n","keywords":[],"articleBody":"13 papers selected.\nPronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts Sumer Kohli, Shreyas Kharbanda, Rodrigo Bruno, João Carreira et al.\nTL;DR — Demonstrates how carefully orchestrated checkpointing can eliminate cold-start latency in serverless runtimes, achieving near-instant hot-starts with negligible overhead.\nSerialization/Deserialization-free State Transfer in Serverless Workflows Fangming Lu, Xingda Wei, Zhuobin Huang, Rong Chen 0001 et al.\nTL;DR — Eliminates the dominant serialization cost in serverless function chaining by enabling direct in-memory state passing, yielding large end-to-end latency reductions.\nSplitFT: Fault Tolerance for Disaggregated Datacenters via Remote Memory Logging Xuhao Luo, Ramnatthan Alagappan, Aishwarya Ganesan\nTL;DR — Proposes a principled fault-tolerance design for disaggregated datacenters that exploits the new memory-compute split to recover from failures with low overhead.\nPuddles: Application-Independent Recovery and Location-Independent Data for Persistent Memory Suyash Mahar, Mingyao Shen, TJ Smith, Joseph Izraelevitz et al.\nTL;DR — Provides transparent crash consistency and data relocation for persistent memory without requiring application changes, easing adoption of PM-backed storage.\nEnoki: High Velocity Linux Kernel Scheduler Development Samantha Miller, Anirudh Kumar, Tanay Vakharia, Ang Chen 0001 et al.\nTL;DR — Enables safe, rapid iteration on Linux CPU schedulers by isolating scheduling logic in user space while keeping kernel integration, dramatically lowering the development barrier.\nTransparent Multicore Scaling of Single-Threaded Network Functions Lei Yan 0003, Yueyang Pan, Diyu Zhou, George Candea et al.\nTL;DR — Automatically parallelizes unmodified single-threaded network functions across cores with correctness guarantees, delivering near-linear throughput scaling without code changes.\nHoda: a High-performance Open vSwitch Dataplane with Multiple Specialized Data Paths Heng Pan, Peng He 0003, Zhenyu Li 0001, Pan Zhang et al.\nTL;DR — Redesigns the Open vSwitch dataplane with multiple specialized fast paths, achieving significant throughput improvements for cloud virtual networking.\nSmartNIC Security Isolation in the Cloud with S-NIC Yang Zhou 0008, Mark Wilkening, James Mickens, Minlan Yu\nTL;DR — Introduces hardware-enforced security isolation for SmartNIC offload tasks in multi-tenant clouds, preventing cross-tenant attacks without sacrificing offload performance.\nFinding Correctness Bugs in eBPF Verifier with Structured and Sanitized Program Hao Sun 0021, Yiru Xu, Jianzhong Liu, Yuheng Shen et al.\nTL;DR — Systematically uncovers verifier logic bugs that can silently allow unsafe eBPF programs to execute in the kernel, with a structured fuzzing approach validated on the Linux eBPF verifier.\nCSAL: the Next-Gen Local Disks for the Cloud Yanbo Zhou, Erci Xu, Li Zhang, Kapil Karkra et al.\nTL;DR — Describes a production cloud local-disk system that replaces raw NVMe with a software-defined layer to deliver better performance, reliability, and operational flexibility at hyperscale.\nVolley: Accelerating Write-Read Orders in Disaggregated Storage Shaoxun Zeng, Xiaojian Liao, Hao Guo, Youyou Lu\nTL;DR — Addresses write-read ordering hazards in disaggregated storage by pipelining acknowledgements with read-side tracking, substantially reducing tail latency without weakening durability.\nErlang: Application-Aware Autoscaling for Cloud Microservices Vighnesh Sachidananda, Anirudh Sivaraman\nTL;DR — Leverages application-level call-graph semantics to make autoscaling decisions that are both faster and more accurate than black-box reactive policies, cutting SLO violations in microservice deployments.\nAutomatic Root Cause Analysis via Large Language Models for Cloud Incidents Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang 0006 et al.\nTL;DR — Demonstrates an LLM-driven pipeline for automated cloud-incident root cause analysis deployed at Microsoft Azure, showing strong recall and significant reduction in on-call engineer effort.\n","wordCount":"538","inLanguage":"en","datePublished":"2024-01-01T00:00:00Z","dateModified":"2024-01-01T00:00:00Z","author":{"@type":"Person","name":"Publish Assistant"},"mainEntityOfPage":{"@type":"WebPage","@id":"https://pub.sqrt.fr/vincent/publish-assistant/cloud-edge/digests/eurosys-2024/"},"publisher":{"@type":"Organization","name":"Publish Assistant","logo":{"@type":"ImageObject","url":"https://pub.sqrt.fr/vincent/publish-assistant/favicon.ico"}}}</script></head><body id=top><header class=header><nav class=header-nav><div class=logo><a href=https://pub.sqrt.fr/vincent/publish-assistant/ accesskey=h title="Publish Assistant (Alt + H)">Publish Assistant</a>
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<svg class="sun" width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><circle cx="12" cy="12" r="5"/><line x1="12" y1="1" x2="12" y2="3"/><line x1="12" y1="21" x2="12" y2="23"/><line x1="4.22" y1="4.22" x2="5.64" y2="5.64"/><line x1="18.36" y1="18.36" x2="19.78" y2="19.78"/><line x1="1" y1="12" x2="3" y2="12"/><line x1="21" y1="12" x2="23" y2="12"/><line x1="4.22" y1="19.78" x2="5.64" y2="18.36"/><line x1="18.36" y1="5.64" x2="19.78" y2="4.22"/></svg></button></div></div><ul id=menu class=menu><li><a href=/vincent/publish-assistant/cloud-edge/venues/ title=Venues><span>Venues</span></a></li><li><a href=/vincent/publish-assistant/cloud-edge/calendar/ title=Calendar><span>Calendar</span></a></li><li><a href=/vincent/publish-assistant/cloud-edge/digests/ title=Digests><span class=active>Digests</span></a></li></ul></nav></header><main class=main><article class=post-single><header class=post-header><nav class=breadcrumbs role=navigation aria-label=Breadcrumb><a href=/vincent/publish-assistant/cloud-edge/digests/>Digests</a>
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<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="feather feather-chevron-right"><polyline points="9 18 15 12 9 6"/></svg></nav><h1 class="post-title entry-hint-parent">EuroSys 2024 Digest</h1><div class=post-meta><span title='2024-01-01 00:00:00 +0000 UTC'>January 1, 2024</span> · <span>Publish Assistant</span></div></header><div class="post-content md-content"><p>13 papers selected.</p><hr><h3 id=pronghorn-effective-checkpoint-orchestration-for-serverless-hot-starts>Pronghorn: Effective Checkpoint Orchestration for Serverless Hot-Starts<a hidden class=anchor aria-hidden=true href=#pronghorn-effective-checkpoint-orchestration-for-serverless-hot-starts>#</a></h3><p><em>Sumer Kohli, Shreyas Kharbanda, Rodrigo Bruno, João Carreira <em>et al.</em></em></p><p><strong>TL;DR</strong> — Demonstrates how carefully orchestrated checkpointing can eliminate cold-start latency in serverless runtimes, achieving near-instant hot-starts with negligible overhead.</p><hr><h3 id=serializationdeserialization-free-state-transfer-in-serverless-workflows>Serialization/Deserialization-free State Transfer in Serverless Workflows<a hidden class=anchor aria-hidden=true href=#serializationdeserialization-free-state-transfer-in-serverless-workflows>#</a></h3><p><em>Fangming Lu, Xingda Wei, Zhuobin Huang, Rong Chen 0001 <em>et al.</em></em></p><p><strong>TL;DR</strong> — Eliminates the dominant serialization cost in serverless function chaining by enabling direct in-memory state passing, yielding large end-to-end latency reductions.</p><hr><h3 id=splitft-fault-tolerance-for-disaggregated-datacenters-via-remote-memory-logging>SplitFT: Fault Tolerance for Disaggregated Datacenters via Remote Memory Logging<a hidden class=anchor aria-hidden=true href=#splitft-fault-tolerance-for-disaggregated-datacenters-via-remote-memory-logging>#</a></h3><p><em>Xuhao Luo, Ramnatthan Alagappan, Aishwarya Ganesan</em></p><p><strong>TL;DR</strong> — Proposes a principled fault-tolerance design for disaggregated datacenters that exploits the new memory-compute split to recover from failures with low overhead.</p><hr><h3 id=puddles-application-independent-recovery-and-location-independent-data-for-persistent-memory>Puddles: Application-Independent Recovery and Location-Independent Data for Persistent Memory<a hidden class=anchor aria-hidden=true href=#puddles-application-independent-recovery-and-location-independent-data-for-persistent-memory>#</a></h3><p><em>Suyash Mahar, Mingyao Shen, TJ Smith, Joseph Izraelevitz <em>et al.</em></em></p><p><strong>TL;DR</strong> — Provides transparent crash consistency and data relocation for persistent memory without requiring application changes, easing adoption of PM-backed storage.</p><hr><h3 id=enoki-high-velocity-linux-kernel-scheduler-development>Enoki: High Velocity Linux Kernel Scheduler Development<a hidden class=anchor aria-hidden=true href=#enoki-high-velocity-linux-kernel-scheduler-development>#</a></h3><p><em>Samantha Miller, Anirudh Kumar, Tanay Vakharia, Ang Chen 0001 <em>et al.</em></em></p><p><strong>TL;DR</strong> — Enables safe, rapid iteration on Linux CPU schedulers by isolating scheduling logic in user space while keeping kernel integration, dramatically lowering the development barrier.</p><hr><h3 id=transparent-multicore-scaling-of-single-threaded-network-functions>Transparent Multicore Scaling of Single-Threaded Network Functions<a hidden class=anchor aria-hidden=true href=#transparent-multicore-scaling-of-single-threaded-network-functions>#</a></h3><p><em>Lei Yan 0003, Yueyang Pan, Diyu Zhou, George Candea <em>et al.</em></em></p><p><strong>TL;DR</strong> — Automatically parallelizes unmodified single-threaded network functions across cores with correctness guarantees, delivering near-linear throughput scaling without code changes.</p><hr><h3 id=hoda-a-high-performance-open-vswitch-dataplane-with-multiple-specialized-data-paths>Hoda: a High-performance Open vSwitch Dataplane with Multiple Specialized Data Paths<a hidden class=anchor aria-hidden=true href=#hoda-a-high-performance-open-vswitch-dataplane-with-multiple-specialized-data-paths>#</a></h3><p><em>Heng Pan, Peng He 0003, Zhenyu Li 0001, Pan Zhang <em>et al.</em></em></p><p><strong>TL;DR</strong> — Redesigns the Open vSwitch dataplane with multiple specialized fast paths, achieving significant throughput improvements for cloud virtual networking.</p><hr><h3 id=smartnic-security-isolation-in-the-cloud-with-s-nic>SmartNIC Security Isolation in the Cloud with S-NIC<a hidden class=anchor aria-hidden=true href=#smartnic-security-isolation-in-the-cloud-with-s-nic>#</a></h3><p><em>Yang Zhou 0008, Mark Wilkening, James Mickens, Minlan Yu</em></p><p><strong>TL;DR</strong> — Introduces hardware-enforced security isolation for SmartNIC offload tasks in multi-tenant clouds, preventing cross-tenant attacks without sacrificing offload performance.</p><hr><h3 id=finding-correctness-bugs-in-ebpf-verifier-with-structured-and-sanitized-program>Finding Correctness Bugs in eBPF Verifier with Structured and Sanitized Program<a hidden class=anchor aria-hidden=true href=#finding-correctness-bugs-in-ebpf-verifier-with-structured-and-sanitized-program>#</a></h3><p><em>Hao Sun 0021, Yiru Xu, Jianzhong Liu, Yuheng Shen <em>et al.</em></em></p><p><strong>TL;DR</strong> — Systematically uncovers verifier logic bugs that can silently allow unsafe eBPF programs to execute in the kernel, with a structured fuzzing approach validated on the Linux eBPF verifier.</p><hr><h3 id=csal-the-next-gen-local-disks-for-the-cloud>CSAL: the Next-Gen Local Disks for the Cloud<a hidden class=anchor aria-hidden=true href=#csal-the-next-gen-local-disks-for-the-cloud>#</a></h3><p><em>Yanbo Zhou, Erci Xu, Li Zhang, Kapil Karkra <em>et al.</em></em></p><p><strong>TL;DR</strong> — Describes a production cloud local-disk system that replaces raw NVMe with a software-defined layer to deliver better performance, reliability, and operational flexibility at hyperscale.</p><hr><h3 id=volley-accelerating-write-read-orders-in-disaggregated-storage>Volley: Accelerating Write-Read Orders in Disaggregated Storage<a hidden class=anchor aria-hidden=true href=#volley-accelerating-write-read-orders-in-disaggregated-storage>#</a></h3><p><em>Shaoxun Zeng, Xiaojian Liao, Hao Guo, Youyou Lu</em></p><p><strong>TL;DR</strong> — Addresses write-read ordering hazards in disaggregated storage by pipelining acknowledgements with read-side tracking, substantially reducing tail latency without weakening durability.</p><hr><h3 id=erlang-application-aware-autoscaling-for-cloud-microservices>Erlang: Application-Aware Autoscaling for Cloud Microservices<a hidden class=anchor aria-hidden=true href=#erlang-application-aware-autoscaling-for-cloud-microservices>#</a></h3><p><em>Vighnesh Sachidananda, Anirudh Sivaraman</em></p><p><strong>TL;DR</strong> — Leverages application-level call-graph semantics to make autoscaling decisions that are both faster and more accurate than black-box reactive policies, cutting SLO violations in microservice deployments.</p><hr><h3 id=automatic-root-cause-analysis-via-large-language-models-for-cloud-incidents>Automatic Root Cause Analysis via Large Language Models for Cloud Incidents<a hidden class=anchor aria-hidden=true href=#automatic-root-cause-analysis-via-large-language-models-for-cloud-incidents>#</a></h3><p><em>Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang 0006 <em>et al.</em></em></p><p><strong>TL;DR</strong> — Demonstrates an LLM-driven pipeline for automated cloud-incident root cause analysis deployed at Microsoft Azure, showing strong recall and significant reduction in on-call engineer effort.</p></div><footer class=post-footer><ul class=post-tags></ul><nav class=paginav><a class=prev 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