Large-scale Measurement and Analysis of Cloud Service Reliability

Given the growth and our increasing reliance on cloud services, it is crucial that we have a better understanding of the reliability of cloud services. Today, a cloud service is composed of a complex array of building blocks and any of the building blocks can fail. Prior empirical studies on cloud reliability have mostly focused on a limited set of cloud services and a few building blocks, and fail to capture a broader view of the reliability of cloud services. Overcoming the above limitations requires data about failure incidents in a large number of diverse cloud services. We leverage the fact that today's cloud services publicly expose detailed information about failure incidents on the web. By crawling such publicly available incident reports, we conduct the first large-scale measurement study of the reliability of 152 cloud services, covering over 11,000 incidents over a period of up to 3 years. Our analysis of a diverse set of cloud services provides a better understanding of their failure rates, the different types of failures they experience, their recovery time from failures, and their availability. We also investigate other factors that may contribute to a service's reliability, such as maintenance, provider faults and security incidents.

Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...