# Portfolio-driven Resource Management for Transient Cloud Servers

## TL;DR

This paper introduces a portfolio-based approach for managing transient cloud servers, enabling applications to reduce costs and revocation risks by optimally combining different server types.

## Contribution

The paper proposes server portfolios modeled on financial principles, and implements ExoSphere to make applications more resilient and cost-effective on transient cloud servers.

## Key findings

- Achieves 80% cost savings over on-demand servers
- Reduces revocation risk significantly
- Enables popular parallel applications to be transiency-aware

## Abstract

Cloud providers have begun to offer their surplus capacity in the form of low-cost transient servers, which can be revoked unilaterally at any time. While the low cost of transient servers makes them attractive for a wide range of applications, such as data processing and scientific computing, failures due to server revocation can severely degrade application performance. Since different transient server types offer different cost and availability tradeoffs, we present the notion of server portfolios that is based on financial portfolio modeling. Server portfolios enable construction of an "optimal" mix of severs to meet an application's sensitivity to cost and revocation risk. We implement model-driven portfolios in a system called ExoSphere, and show how diverse applications can use portfolios and application-specific policies to gracefully handle transient servers. We show that ExoSphere enables widely-used parallel applications such as Spark, MPI, and BOINC to be made transiency-aware with modest effort. Our experiments show that allowing the applications to use suitable transiency-aware policies, ExoSphere is able to achieve 80\% cost savings when compared to on-demand servers and greatly reduces revocation risk compared to existing approaches.