2/26/2023 0 Comments Shonan 13 raw![]() ![]() Schroeder, “Practical scrubbing: Getting to the bad sector at the right time,” in IEEE/IFIP International Conference on Dependable Systems and Networks. McGuire, “Accelerated Heartbeat Protocols,” in Proceedings of the 18th International Conference on Distributed Computing Systems (ICDCS), 1998. Machowinski, “How predictive maintenance can eliminate downtime,”, Last accessed. “2018 Cloud Computing Survey,”, Last accessed. ![]() Traditional ML evaluation techniques (e.g., cross-validation) are rarely applicable, as they do not consider the real-life peculiarities. How do we evaluate the AIOps solutions In-context? AIOps solutions must be evaluated in a context which resembles their actual production usage.How do we make AIOps solutions Scalable? AIOps solutions need to be scalable and efficient as they must analyze the monitoring data from thousands to millions of nodes and react to changes in microseconds.How do we make AIOps solutions Maintainable? AIOps solutions need to require minimal maintenance and fine-tuning, since DevOps engineers are usually not ML experts, who are already overcommitted on many company-wide ML-initiatives.Such interpretable models enable DevOps engineers to reason about model recommendations, to gain upper management support for following such recommendations, and, more importantly, enabling DevOps engineers to improve the status quo (e.g., by improving and optimizing their monitoring solutions). How do we make AIOps solutions Interpretable? AIOps solutions need to be interpretable even if at the cost of lower performance.How do we make AIOps solutions Trustable? AIOps solutions must incorporate years of field-tested engineertrusted domain expertise into their ML models, instead of simply employing sophisticated models on raw data. ![]()
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