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91	Hybrid Cloud Migration Challenges. A case study at King Boronin, Mikhail January 2020 (has links) Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not ready to fully exploit the benefits of this environment, and adapting them to this environment is a non-trivial task.Therefore, many organizations consider a gradual process of moving to the cloud with Hybrid Cloud architecture. In this paper, the author is making an effort of analyzing particular enterprise case in cloud migration topics like cloud deployment, cloud architecture and cloud management.This paper aims to identify, classify, and compare existing challenges in cloud migration, illustrate approaches to resolve these challenges and discover the best practices in cloud adoption and process of conversion teams to the cloud. cloud migration hybrid cloud microservices devops on-premise to cloud cloud architecture cloud infrastructure live migration kubernetes cloud providers private public cloud Information Systems, Social aspects
92	Container Orchestration : the Migration Path to Kubernetes Andersson, Johan, Norrman, Fredrik January 2020 (has links) As IT platforms grow larger and more complex, so does the underlying infrastructure. Virtualization is an essential factor for more efficient resource allocation, improving both the management and environmental impact. It allows more robust solutions and facilitates the use of IaC (infrastructure ascode). Many systems developed today consist of containerized microservices. Considered the standard of container orchestration, Kubernetes is the natural next step for many companies. But how do we move on from previous solutions to a Kubernetes cluster? We found that there are not a lot of detailed enough guidelines available, and set out to gain more knowledge by diving into the subject - implementing prototypes that would act as a foundation for a resulting guideline of how it can be done. virtualization container docker docker compose container orchestration kubernetes ansible terraform internet of things deployment scaling migration patterns rancher helm infrastructure as code Computer and Information Sciences Data- och informationsvetenskap Computer Sciences Datavetenskap (datalogi) Software Engineering Programvaruteknik Information Systems
93	An Empirical Study on AI Workflow Automation for Positioning / En empirisk undersökning om automatiserat arbetsflöde inom AI för positionering Jämtner, Hannes, Brynielsson, Stefan January 2022 (has links) The maturing capabilities of Artificial Intelligence (AI) and Machine Learning (ML) have resulted in increased attention in research and development on adopting AI and ML in 5G and future networks. With the increased maturity, the usage of AI/ML models in production is becoming more widespread, and maintaining these systems is more complex and likely to incur technical debt when compared to standard software. This is due to inheriting all the complexities of traditional software in addition to ML-specific ones. To handle these complexities the field of ML Operations (MLOps) has emerged. The goal of MLOps is to extend DevOps to AI/ML and therefore speed up development and ease maintenance of AI/ML-based software, by, for example, supporting automatic deployment, monitoring, and continuous re-training of models. This thesis investigates how to construct an MLOps workflow by selecting a number of tools and using these to implement a workflow. Additionally, different approaches for triggering re-training are implemented and evaluated, resulting in a comparison of the triggers with regards to execution time, memory and CPU consumption, and the average performance of the Machine learning model. MLOps ML AI Machine Learning Artificial Intelligence Radio Antenna Positioning MLOps Maturity Levels Radio Access Network RAN Kubeflow KServe DVC Data Version Control MinIO Kubernetes Kind Docker Computer Sciences Datavetenskap (datalogi)

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