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BA: Challenges and Opportunities of AIOps Solutions

Designing a successful system for cloud maintenance and ensuring resiliency is challenging due to the complex nature of modern cloud systems. Resiliency is defined as the ability of a cloud platform to recover quickly and continue operating even after a component failure. Over the recent years, AIOps (Artificial Intelligence Operations) has exploded as a new area of software solutions supporting system administrators and DevOps engineers in this challenging task. AIOps refers to multi-layered technology platforms that automate and enhance IT operations by monitoring the system, analysing the collected data, finding problematic behaviors and selecting automatic repair workflows. AIOps platforms heavily depend on data analytics and machine learning technologies.

This thesis focuses on creating a survey about challenges and possible opportunities for AIOps. This includes the analysis of the current players (e.g. Moogsoft) in this field and information about the overall market. Furthermore, the needs and expectations of system administrators should be evaluated in order to show the demand for AIOps solutions.

If this topic sounds interesting to you, please send an email to . Please add background information (e.g. CV, grades) of yourself to the mail, so we can quickly determine if this topic fits your skills.



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Florian Schmidt
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