Speaker:

Ana Klimovic

Talk Title:

Unlocking True Elasticity in the Cloud with Dandelion

Date and Location:

Friday, October 24, 2025

3–4 p.m.

BA 7231

There is no registration required to attend this event in person. However, seating is limited, so arriving early is recommended.

Abstract:

Resource elasticity is fundamental to cloud computing. The more quickly a cloud platform can allocate resources to match the demand of each user request as it arrives, the less resources need to be pre-provisioned to meet performance requirements. However, even serverless platforms — which can boot sandboxes in 10s to 100s of milliseconds — are not sufficiently elastic to avoid over-provisioning expensive resources. A key obstacle for true elasticity is that today’s cloud platforms are stuck retrofitting system software designed for a more traditional execution model of cloud computing based on long-running virtual machines that provide each user application with a POSIX-like interface. While providing a POSIX interface was important in the early days of cloud computing to ease migration from on premise clusters, today's developers design cloud-native applications, in which user-defined computations interact with a variety of cloud services (e.g. storage, AI inference, data analytics engines) over REST APIs. In this talk, I will present Dandelion: a cloud platform that achieves high elasticity by rethinking the interface between applications and the cloud. Users express Dandelion applications as DAGs of pure compute functions and HTTP-based communication functions. This enables Dandelion to securely execute user-defined compute functions in lightweight sandboxes that cold start in hundreds of microseconds, since executing pure functions does not require initializing a POSIX environment. Dandelion makes it practical to boot a sandbox on-demand for each request, decreasing performance variability by orders of magnitude compared to Firecracker and reducing committed memory by over 50%. We will discuss the implications of true elasticity for cloud applications like interactive data analytics and emerging agentic AI workflows. 

Biography:

Ana Klimovic is an Assistant Professor in the Systems Group of the Computer Science Department at ETH Zurich. Her research interests span operating systems, computer architecture, and their intersection with machine learning. Ana's work focuses on computer system design for large-scale applications such as cloud computing services, data analytics, and machine learning. Before joining ETH in August 2020, Ana was a Research Scientist at Google Brain and completed her Ph.D. in Electrical Engineering at Stanford University.