Scalability Benchmarking of Cloud-Native Applications Applied to Event-Driven Microservices

Cloud-native applications constitute a recent trend for designing large-scale software systems. This thesis introduces the Theodolite benchmarking method, allowing researchers and practitioners to conduct empirical scalability evaluations of cloud-native applications, their frameworks, configurations, and deployments. The benchmarking method is applied to event-driven microservices, a specific type of cloud-native applications that employ distributed stream processing frameworks to scale with massive data volumes. Extensive experimental evaluations benchmark and compare the scalability of various stream processing frameworks under different configurations and deployments, including different public and private cloud environments. These experiments show that the presented benchmarking method provides statistically sound results in an adequate amount of time. In addition, three case studies demonstrate that the Theodolite benchmarking method can be applied to a wide range of applications beyond stream processing

How to Measure Scalability of Distributed Stream Processing Engines?

Scalability is promoted as a key quality feature of modern big data stream processing engines. However, even though research made huge efforts to provide precise definitions and corresponding metrics for the term scalability, experimental scalability evaluations or benchmarks of stream processing engines apply different and inconsistent metrics. With this paper, we aim to establish general metrics for scalability of stream processing engines. Derived from common definitions of scalability in cloud computing, we propose two metrics: a load capacity function and a resource demand function. Both metrics relate provisioned resources and load intensities, while requiring specific service level objectives to be fulfilled. We show how these metrics can be employed for scalability benchmarking and discuss their advantages in comparison to other metrics, used for stream processing engines and other software systems

Measuring urban circularity based on a territorial perspective : final report ; CIRCTER - circular economy and territorial consequences

This report provides an overview of the main findings from the different research tasks in the CIRCTER project and delivers selected policy messages with European coverage. The report provides: (Sec. 2) a territorial definition of the circular economy; (Sec. 3) insights into the available statistics on material and waste patterns and flows and their interpretation, alongside new territorial evidence on both aspects; (Sec. 4) a sectoral characterisation of the circular economy at regional level (NUTS-2), including data on turnover and jobs; (Sec. 5) key findings from the CIRCTER case studies; (Sec. 6) a systemic interpretation of the circular economy that works as a knowledge-integration mechanism for the entire report; (Sec. 7 and 8) an analysis of the most relevant circular economy policies and strategies at various territorial levels; (Sec. 8) a subset of policy recommendations focusing in particular on territorial and cohesion policies, and; (Sec. 9) suggestions for further research

Benchmarking Function Hook Latency in Cloud-Native Environments

Researchers and engineers are increasingly adopting cloud-native technologies for application development and performance evaluation. While this has improved the reproducibility of benchmarks in the cloud, the complexity of cloud-native environments makes it difficult to run benchmarks reliably. Cloud-native applications are often instrumented or altered at runtime, by dynamically patching or hooking them, which introduces a significant performance overhead. Our work discusses the benchmarking-related pitfalls of the dominant cloud-native technology, Kubernetes, and how they affect performance measurements of dynamically patched or hooked applications. We present recommendations to mitigate these risks and demonstrate how an improper experimental setup can negatively impact latency measurements.Comment: to be published in the 14th Symposium on Software Performance (SSP 2023), source code available at https://github.com/dynatrace-research/function-hook-latency-benchmarkin

Abschlussbericht KMU-innovativ: Verbundprojekt Titan Industrial DevOps Plattform für iterative Prozessintegration und Automatisierung

Unternehmensprozesse zu digitalisieren und dabei eine IT-Infrastruktur aufzubauen, ist komplex. Neue, zum Teil teure Technologien werden eingesetzt, jedoch fehlen erprobte Praktiken. Die daraus entstehende Komplexität lässt sich mit dem klassischen Projektmodell nur ungenügend adressieren. Klassische Planungen basieren auf Annahmen, die sich oft zu spät und als falsch erweisen. Mechanismen, den einmal geplanten Weg zum gesetzten Ziel zu korrigieren, bietet das traditionelle Projektmodell nur eingeschränkt. Ziel des titan-Projekts ist die Integration von Entwicklungswerkzeugen und Betriebs-Technologie in eine Software-Plattform. Kombiniert mit innovativen „Industrial DevOps“- Methoden soll die komplexe Aufgabe einer iterativen Systemintegration im industriellen Umfeld erheblich vereinfacht werden. Im titan-Projekt ist der Prototyp einer Software-Plattform entstanden, die es industriellen Anwendern erlaubt, diese Praktiken auf Problemstellungen der Digitalisierung anzuwenden. Neben Zielen wie Sicherstellung und Überprüfbarkeit von Qualität, Widerstandsfähigkeit und Skalierbarkeit ist die Eliminierung des Vendor-Lock-In ein zentraler Aspekt des Projekts. Insbesondere werden Prozessanpassungen durch die Anwender mittels Flow Based Automation ermöglicht, neue Softwareversionen und Veränderungen können am System routinemäßig in Betrieb genommen werden und domänenspezifische Komponenten können für komplexe Aufgaben genutzt und verwaltet werden. Im Rahmen einer Community wird die titan-Open-Source-Plattform weiterentwickelt. Die während des Projekts entstandenen Innovationen werden so verfeinert und in verschiedenen Bereichen angewendet. Die Erfahrungen aus Projekten fließen in die Software ein und werden innerhalb der Community verbreitet

The new critical metals database “HTMET”: High tech trace element characteristics of sulphides from base metal provinces in the variscan basement and adjacent sedimentary rocks in Germany

High tech (HT) trace elements such as germanium, gallium and indium gain rising importance in the development of innovative technologies. The database “HTMET” forms the first nationwide metal-ore database for Germany, created to visualise HT metal characteristics of base metal ores from important mining districts. Mineralogical and geochemical investigations on 478 samples and ore concentrates from 109 Pb-Zn-Cu occurrences were carried out using analytical methods with high spatial resolution and bulk sample methods. The database provides aggregated data based on 17,000 geochemical data sets, compiled information on regional infrastructure and environmental risks as well as data on innovative raw material-efficient processing techniques. Evaluation of combined data provides interactive maps revealing new potentials for specific HT metals in Germany. Differences in regional distribution of these trace elements and dependency of their concentration levels in the ore on the genetic deposit type became apparent. Sphalerite from the sediment-hosted massive sulphide (SHMS) deposit “Rammelsberg” and skarn deposits in the Erzgebirge contain elevated indium contents (median 14–119 ppm), whereas the SHMS deposit “Meggen” is poor in HT metals. Germanium forms the predominant HT trace element in colloform sphalerite of Mississippi-Valley-Type (MVT) deposits (median 29–147 ppm); in contrast, crystalline sphalerite is low in germanium in this deposit type. Sphalerite in all hydrothermal vein deposits shares a distinct enrichment in gallium (median 6–81 ppm); however, germanium and indium concentrations vary significantly depending on the metal source and fluid conditions. The Ruhrgebiet and the Schwarzwald ore veins show an enrichment in germanium (median 55–73 ppm), whilst vein sphalerite from the Erzgebirge is specialised in indium (median 33 ppm). The data demonstrate that the HT trace element inventory of the studied base metal sulphides is not only a function of the genetic ore deposit type, but is also triggered by locally variable geology such as source rock and fluid composition and organic content of the rock. Gallium seems to derive from adjacent lithologies, whereas indium and germanium may have more distant sources