Machine Learning and Artificial Intelligence Techniques Using Observability Data in Distributed Systems

Abstract

Organizations depends on Observability data to reliably operate systems and develop applications. The amount of data generated in the systems exponentially grows with business demand with new and existing customers, more products and features being released and because developers and operators require more data to analyze and debug applications. As the data grows, the complexity, mean time to detect (MTTD) and mean time to resolve (MTTR) grows as well. Using Machine Learning (ML) and Artificial Intelligence (AI) techniques discussed in this paper will improve MTTR, MTTD, reduce complexity of debugging issues using Observability data collected from the various distributed systems.