Andreas Kumlehn

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Anomalies in the runtime behavior of software systems, especially in distributed systems, are inevitable, expensive , and hard to locate. To detect and correct such anomalies (like instability due to a growing memory consumption, failure due to load spikes, etc.) one has to automatically collect, store, and analyze the operational data of the runtime(More)
Distributed applications, cloud systems, the Internet of Things , etc. are generating increasing amounts of operational data, such as CPU loads, thread states, memory consump-tions, method runtimes, or logs. Many tools continuously collect and analyze such data that is best represented as time series. Typical analyses try to find and localize run-time(More)
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