In Switzerland, opendata.swiss is the go-to location for any open dataset resulting from federal, cantonal or municipal sources. From a societal and economics perspective, the portal is an important asset following the “protect private data, make use of public data” mantra, and has already led to digital innovation through the availability of many third-party applications. In this research blog post, we look at some numbers associated with the portal.
Note: This information is to be understood under the condition of approval of the DIZH by the Canton Council.
The research efforts «Can virtual reality systems help us to design software as we talk?» and «Smart Cities & Regions Services Enablement» are among the first contributions to the digitalisation initiative of the canton of Zurich. They amplify the know-how on software engineering and data-intensive Internet services bundled at the Institute for Applied Information Technology for the support of commercial applications of the following decade.
Singer.io is an open-source JSON-based data shifting (ETL: extract, transform, load) framework, designed to bring simplicity when moving data between a source and a destination service on the Internet. In this post, we present the framework as entry point into the world of SaaS-level data exchange and some associated research questions.
Auckland, New Zealand, had invited the global research and innovation community around broadly defined cloud computing topics to an established four-day double conference. The 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2019) and the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2019) happened with their respective main tracks and satellite events. The Service Prototyping Lab at Zurich University of Applied Sciences was present with a workshop, a tutorial and a presentation. This blog post summarises the contributions and the event as a whole.
Docker images have become the valuta franca in the cloud and container platform world. Although on the path to vendor-neutral standardisation (e.g. with OCI also being in Docker Hub for a year now), developers for now have settled on plain Docker as de-facto standard due to the vast ecosystem of base images and dependency images which speed up the rapid prototyping of complex scalable applications. From a production-grade DevOps perspective, a key concern is then to be assured that the containers used are of high quality, not infected by security vulnerabilities, and still containing the latest features available. In this blog post, a novel approach to visualise the situation around a particular container image is presented.
With the proliferation of hybrid cloud, cross-cloud and post-cloud environments, finding the right concepts and tools to produce mixed-technology applications and services remains challenging. At Zurich University of Applied Sciences, a course on Serverless and Cloud-native Application Development (SCAD) prepares bachelor students in computer science for facing these challenges. We argue that this is the first such lecture in Switzerland and probably even in the world. Three years after reflecting on Internet Service Prototyping teaching, this mid-semester blog post sums up the evolution of the field, explains the course design of SCAD and briefly reports on the lab results.
SPLab has been participating in two major events recently: DINAcon in Bern, the conference for digital sustainability, and the Software QS Day in Frankfurt – expanding horizons on software quality and testing. As we participated as attendee in the first and speaker in the second, this blog post summarises interesting technology trends from both.
The MAO-MAO research collaboration aims to provide metrics, analytics and quality control for microservice artefacts of all kinds, including but not limited to, Docker containers, Helm charts and AWS Lambda functions. As such, an integral part of prior research has been the various periodic data collection experiments, gathering metadata and conducting automatic code analysis.
However, the ambition of the project to collect data consistently, combined with the need for the collaborators to be able to use each other’s tools and access each other’s data, have created a need for a collaboration framework and distributed execution platform.
In response to this need, we present the first release of the MAO Orchestrator, a tool designed to run these experiments in a smart way and on a schedule, within a federated cluster across research sites. As a plus, there is nothing implementation-wise tying it to the existing assessment tools, so it is reusable for any use-case that requires collaboratively running periodic experiments.
Adaptivity and adaptability are key characteristics of modern software to cope with sometimes unpredictable changes in the environment including system and user behaviour. Modern cloud-native architectures for instance foresee the case-by-case handling of decisions – e.g. to decide whether using a provider database or hosting one yourself – at the application or workflow level based on knowledge and rules or emergent behaviour. In workflows representing data flows from connected devices, the (self-)adaptivity should be modelled and supported by context-aware systems.