Agile Scalability Engineering: The ScrumScale Method

While agile methods have had a great uptake and impact in software engineering, managing non‑functional qualities still seems to be a challenge. We focus on the scalability of software systems and how this critical quality can be managed and controlled, while still benefiting from the advantages of an agile process. Scalability is a property of a system that must be carefully designed in to avoid potential disastrous behavior when load and work fluctuate. Through a collaboration with and a case study at the largest Norwegian public portal operator, Altinn, we have proposed and tested additions to the Scrum process framework. With our approach named ScrumScale, scalability concerns may be identified and related to user stories. The roles in a Scrum project can collaborate without adding more ceremony than strictly necessary. The paper provides an overview of the ScrumScale method and lessons learned from Altinn.publishedVersio

3rd workshop on hot topics in cloud computing performance (HotCloudPerf'20):Performance variability

The organizers of the Third Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf 2020) are delighted to welcome you to the workshop proceedings as part of the ICPE conference companion. The HotCloudPerf 2020 workshop is a full-day workshop on Tuesday, April 21, taking place jointly with WOSP-C as part of the ICPE conference week in Edmonton, Canada. Each year, the workshop chooses a focus theme to explore; for 2020, the theme is "Performance variability of cloud datacenters and the implications of such phenomena on application performance" Cloud computing is emerging as one of the most profound changes in the way we build and use IT. The use of global services in public clouds is increasing, and the lucrative and rapidly

Quantifying cloud performance and dependability:Taxonomy, metric design, and emerging challenges

In only a decade, cloud computing has emerged from a pursuit for a service-driven information and communication technology (ICT), becoming a significant fraction of the ICT market. Responding to the growth of the market, many alternative cloud services and their underlying systems are currently vying for the attention of cloud users and providers. To make informed choices between competing cloud service providers, permit the cost-benefit analysis of cloud-based systems, and enable system DevOps to evaluate and tune the performance of these complex ecosystems, appropriate performance metrics, benchmarks, tools, and methodologies are necessary. This requires re-examining old system properties and considering new system properties, possibly leading to the re-design of classic benchmarking metrics such as expressing performance as throughput and latency (response time). In this work, we address these requirements by focusing on four system properties: (i) elasticity of the cloud service, to accommodate large variations in the amount of service requested, (ii) performance isolation between the tenants of shared cloud systems and resulting performance variability, (iii) availability of cloud services and systems, and (iv) the operational risk of running a production system in a cloud environment. Focusing on key metrics for each of these properties, we review the state-of-the-art, then select or propose new metrics together with measurement approaches. We see the presented metrics as a foundation toward upcoming, future industry-standard cloud benchmarks

Effect of non-pharmaceutical interventions in the early phase of the COVID-19 epidemic in Saudi Arabia

Non-pharmaceutical interventions have been widely employed to control the COVID-19 pandemic. Their associated effect on SARS-CoV-2 transmission have however been unequally studied across regions. Few studies have focused on the Gulf states despite their potential role for global pandemic spread, in particular in the Kingdom of Saudi Arabia through religious pilgrimages. We study the association between NPIs and SARS-CoV-2 transmission in the Kingdom of Saudi Arabia during the first pandemic wave between March and October 2020. We infer associations between NPIs introduction and lifting through a spatial SEIR-type model that allows for inferences of region-specific changes in transmission intensity. We find that reductions in transmission were associated with NPIs implemented shortly after the first reported case including Isolate and Test with School Closure (region-level mean estimates of the reduction in R0 ranged from 25–41%), Curfew (20–70% reduction), and Lockdown (50–60% reduction), although uncertainty in the estimates was high, particularly for the Isolate and Test with School Closure NPI (95% Credible Intervals from 1% to 73% across regions). Transmission was found to increase progressively in most regions during the last part of NPI relaxation phases. These results can help informing the policy makers in the planning of NPI scenarios as the pandemic evolves with the emergence of SARS-CoV-2 variants and the availability of vaccination