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July 15, 2026ACM SIGOPS Operating Systems Review

Agentic Workflows are Serverless Applications, so deploy them that way!

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Authors

IDIan DoughertyNLNatalie LambertYWYi-Xiang Wang

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Overview

Survey identifies latency issues in serverless AI workloads, proposing tailored deployment strategies.

Key Points

  • The aim is to explore the suitability of AI workloads for serverless applications and propose solutions for efficiency.
  • Survey current state of serverless hosting for large language models (LLMs)
  • Analyze startup latency and model initialization
  • Propose deployment scheme and pre-warming policies for agentic workloads
  • Model loading and initialization processes lead to significant startup latency.
  • Agentic AI workloads are not well defined within the serverless framework.
  • Proposed pre-warming policies reduce idle resource footprint and improve startup times.

Cite This Study

Dougherty et al. (2026) studied this question.

synapsesocial.com/papers/6a57239488b21df8754804b5https://doi.org/10.1145/3830422.3830426
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Demystifying Serverless Computing for AI Workloads: Architectures, Challenges, and Optimization Strategies2025
  2. 2Serverless Solution Architecture for AI-Powered Cloud-Native Applications2026
  3. 3Secured Artificial Intelligence Based Face Anti-spoofing Detection Model via Serverless Architecture and SaaS Based Cloud Platform2024
  4. 4Deploying AI-Based Applications with Serverless Computing in 6G Networks: An Experimental Study2024
  5. 5Event-Driven AI Workflows in Serverless Computing: Enabling Real-Time Data Processing and Decision-Making2024 · 2 citations