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Software engineers have a wide variety of tools and techniques that can help them improve the quality of their code, but still, a lot of bugs remain undetected. In this paper we build on the idea that if a particular fragment of code is…

Solving the software dependency issue under the HPC environment has always been a difficult task for both computing system administrators and application scientists. This work would like to tackle the issue by introducing the modern…

Much has been said about observability in system theory and control; however, it has been recently that observability in complex networks has seriously attracted the attention of researchers. This paper examines the state-of-the-art and…

Data-driven predictive control (DPC) has been studied and used in various scenarios, since it could generate the predicted control sequence only relying on the historical input and output data. Recently, based on cloud computing,…

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face challenges when applying BBO methods to their problems at hand…

Recent developments in the commercial open source community have catalysed the use of Linux containers for scalable deployment of web-based applications to the cloud. Scientific software can be containerized with dependencies, configuration…

Observability, in cloud native systems, is the capability to continuously generate and discover actionable insights, based on signals from the system under observation. How do you know what insights are the most useful ones? What signals…

The use of container technology has skyrocketed during the last few years, with Docker as the leading container platform. Docker's online repository for publicly available container images, called Docker Hub, hosts over 3.5 million images…

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, engineering, physics, and experimental design. However, it remains a challenge for users to apply BBO methods to their problems at hand…

Enterprise IT is currently facing the challenge of coordinating the management of complex, multi-component applications across heterogeneous cloud platforms. Containers and container orchestrators provide a valuable solution to deploy…

Docker images are used to distribute and deploy cloud-native applications in containerised form. A container engine runs them with separated privileges according to namespaces. Recent studies have investigated security vulnerabilities and…

In this paper, we present a novel fault injection system called ChaosOrca for system calls in containerized applications. ChaosOrca aims at evaluating a given application's self-protection capability with respect to system call errors. The…

Given the rapid improvement of the detectors at high-energy physics experiments, the need for real-time data monitoring systems has become imperative. The significance of these systems lies in their ability to display experiment status,…

Comparative evaluation of several systems is a recurrent task in researching. It is a key step before deciding which system to use for our work, or, once our research has been conducted, to demonstrate the potential of the resulting model.…

Software developers are faced with the issue of either adapting their programming model to the execution model (e.g. cloud platforms) or finding appropriate tools to adapt the model and code automatically. A recent execution model which…

The explosion of data and its ever increasing complexity in the last few years, has made MLOps systems more prone to failure, and new tools need to be embedded in such systems to avoid such failure. In this demo, we will introduce crucial…

Query optimizers are essential components of relational database management systems that directly impact query performance as they transform input queries into efficient execution plans. While users can obtain the final execution plan using…

Planning under partial observability is an essential capability of autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides a powerful framework for planning under partial observability problems, capturing the…

Machine Learning Operations (MLOps) is becoming a highly crucial part of businesses looking to capitalize on the benefits of AI and ML models. This research presents a detailed review of MLOps, its benefits, difficulties, evolutions, and…

In an era of rapid climate change and its adverse effects on food production, technological intervention to monitor pollinator conservation is of paramount importance for environmental monitoring and conservation for global food security.…