To upgrade or not to upgrade

Dumitraş, Tudor; Narasimhan, Priya; Tilevich, Eli

doi:10.1145/1869459.1869530

Cited by 20 publications

References 20 publications

(24 reference statements)

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Analyzing Software Updates: Should You Build a Dynamic Updating Infrastructure?

Gharaibeh

Rajan

Chang

2011

Fundamental Approaches to Software Engineering

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Abstract. The ability to adapt software systems to fix bugs, add/change features without restarting is becoming important for many domains including but not limited to finance, social networking, control systems, etc. Fortunately, many ideas have begun to emerge under the umbrella term "dyanamic updating" to solve this problem. Dynamic updating is critical to address certain software evolution needs. Dynamic updating literature evaluates such systems in terms of coverage (i.e. what type of code changes are supported) and performance. However, we do not have a technique to analyze whether certain updating solution, based on its costs and benefits, is suitable for an application.In this paper, we present a quantitative analysis model to fill this gap. Our model is parameterized and it can be instantiated with application-specific valuation functions. Given the software evolution history of the application under consideration, our model allows rigorous comparisons of the value of different software updating schemes (e.g. online vs. offline). We illustrate our model using two case studies inspired from the the evolution history of Xerces XML parser library and Apache httpd web server. Other case studies and evaluation examples are presented in our technical report [Gharaibeh, Rajan and Chang 09]. The proposed analysis scheme can serve system architects in evaluating their current updating scheme. For example, to audit the system's value during previous development cycles and whether a different updating scheme will generate higher value.

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Analyzing Software Updates: Should You Build a Dynamic Updating Infrastructure?

Gharaibeh

Rajan

Chang

2011

Fundamental Approaches to Software Engineering

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Quantifying Failure Risk of Version Switch for Rolling Upgrade on Clouds

Sun

Bass

Fekete

et al. 2014

2014 IEEE Fourth International Conference on Big Data and Cloud Computing

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Rolling upgrade is an industry technique for online dynamic software update. A rolling upgrade updates a small number of instances in an old version to a new version at a time and the operation is repeated in a wave rolling until all of the instances have been upgraded. In many cases, the software needs to avoid interactions between different versions. One common simple approach is to make instances version aware, and then a version switch point can be chosen to deactivate the old service and activate the new service. On a Cloud platform, upgrades can be implemented simply through replacing old virtual machine instances with ones in new versions, and during the process of rolling upgrade various failures may present. If an instance fails, a new instance has to be launched from the backup images, which in most software systems are in an old version and cannot be simply replaced to a new version if the new software and the new service have not been stable for the sake of reliability and stability. Thus the progress of the rolling upgrade is not guaranteed, and indeed the number of upgraded instances can sometimes decrease. We aim to determine the probability that, after switching the versions at a selected point, the number of working instances may sometime fall below the amount needed for a desired Quality of Service. In this paper, we stochastically quantify the risk with a family of discrete Markov chains (DTMC). The evaluation in both Amazon Web Service (AWS) and simulation reveals that our technique can well predict the risks after given version switch points.

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