Machine Learning Interference Modelling for Cloud-native Applications

Modern cloud-native applications use microservice architecture patterns, where fine granular software components are deployed in lightweight containers that run inside cloud virtual machines. To utilize resources more efficiently, containers belonging to different applications are often co-located on the same virtual machine. Co-location can result in software performance degradation due to interference among components competing for resources. In this thesis, we propose techniques to detect and model performance interference. To detect interference at runtime, we train Machine Learning (ML) models prior to deployment using interfering benchmarks and show that the model can be generalized to detect runtime interference from different types of applications. Experimental results in public clouds show that our approach outperforms existing interference detection techniques by 1.35%-66.69%. To quantify the intereference impact, we further propose a ML interference quantification technique. The technique constructs ML models for response time prediction and can dynamically account for changing runtime conditions through the use of a sliding window method. Our technique outperforms baseline and competing techniques by 1.45%-92.04%. These contributions can be beneficial to software architects and software operators when designing, deploying, and operating cloud-native applications

Problems and restrictions in the management of digitization projects at large companies

 The paper has the following chapters: the need for a good result from the cost-benefit analysis, multi-disciplinary elements in the management of digitization projects, knowledge management in digitization projects, ethical issues – restrictions in digitization projects, natural opposition to change of organization. The use of cost-benefit analysis has the following moments of use: before its launch or choosing the option to carry out the project, if the need for a project for which there are several implementation options has been established by other methods. In digitization projects, one of the concepts used more and more is that of smart infrastructure. Recent management talks about the fact that systems are much more important now than before. One of the problems with current systems is connection.In the case of digitization projects, there are also components that aim only at acquiring the skills necessary for new technological systems or work procedures. In their case, there are many elements already established in the field of education. One of these is the relationship between the importance given to certain knowledge and its usefulness.The process of globalization has extended internationally the regulation of the ethics of certain professions, including in the field of ITC and project management in large companies. The professional ethics as restriction of digitization projects are applicable not only to multinational companies, but to all those operating in a global market.Staff confidence in the usefulness of digitization projects must aim for maximum capacity. Digitization can be conceived as a solution to increase the revenue of the companies as a financial sources to motivate the staff.