Watch the videos and get the slides of our two talks:
Machine Learning and Advanced Statistics for Performance Monitoring
End User Experience Monitoring for Cloud Applications
Susanne Greiner, our Data Scientist, spoke about Machine Learning and Advanced Statistics for Performance Monitoring:
Performance is playing an increasingly important role in the IT sector. Performance monitoring helps to detect whether a network is stable enough, whether an application is fast enough, whether users can be expected to be satisfied with a service, and to answer many similar questions. Key ingredient for monitoring are the right metrics. To create promising metrics that might become valuable Key Performance Indicators (KPIs) one needs data, profound domain knowledge, and suitable maths. In time of analog storage the collection of data might have been a problem, but not anymore. Nowadays data are collected and stored everywhere at any time. This amount of (big) data can be used in several ways. Sophisticate methods, e.g. anomaly detection, make it possible to deal with problems and get to their roots even when the sheer amount of data available would take too much time to analyze by a human admin relying on common practice methods. Goal of this talk is to show the role of advanced statistics and machine learning compared to currentcommon practice when extracting insights from multiple data sources. Advantages when it comes tovisualization, bottleneck detection, and alarm creation are presented via practical examples from theperformance monitoring field. Open Source tools such as for example the SciPy stack, scikit-learn, as well as InfluxDB and Grafana can help to accomplish a minor part of the big task but in particular their combination has a huge potential in this field.
Francesco Melchiori, our Alyvix Product Manager introduced End User Experience Monitoring for Cloud Applications with Alyvix:
Alyvix provides GUI tools to graphically define every transactions of user interaction flows on any application. Alyvix is able to automate all applications that are in the cloud or on-premises. (e.g. Onlineshop, Citrix etc.). That is because Alyvix is not bolted to application APIs, but it acts as it would sit in front of their interface interacting with them (as a human would do). Alyvix tests the availability of your applications and measures their responsiveness. Hence, Alyvix measures how long transactions take to be accomplished, and reports the performance in HTML pages. Through the integration to your monitoring system (e.g. NetEye, Icinga, Nagios) those outcomes can be tracked. Latency spikes and service downtimes can be clearly recognized from time series charts. Moreover, notification messages and other logics can be set. Alyvix certifies the ongoing quality of IT cloud services highlighting in which location and on whattime they are performing well or worse than expected. With this information, IT operations teams can modulate infrastructure resources and IT clients can check their SLA with providers. Alyvix is a Python-based open source software, which can be easily deployed on Windows 64-bit machines. During his speech, Francesco Melchiori will present the Alyvix features, explain how they can be used to monitor cloud applications and show why they help keeping the quality of your IT services high.advanced statistics, Alyvix, End User Experience, machine learning, performance monitoring, Real User Experience