Next Level Performance Monitoring – Part I

Posted by on Jun 20, 2017 in NetEye, Network Traffic Monitoring, Real User Experience Monitoring | 0 comments

Network traffic keeps becoming more and more heterogeneous. In many cases, it is not enough to monitor a system as we have done in the past. Here I will present the key ingredients according to Würth Phoenix for successful state of the art performance monitoring and proactive analysis of those applications that are critical for your business.

Combining User Experience and Performance Metrics for new Insights

User experience is a very important factor. If your measurements seem in the right range, BUT end users complain about slow applications, you need to act. For this reason, user experience combined with an overview of all the servers being put under monitoring is the right place to start. In our opinion it is of vital importance to know when critical business applications begin to slow down before your users start to complain. You can achieve this by running continuous checks via Alyvix – our active user experience monitoring solution. Test cases can be written specifically for the most vital parts of your applications, and the functionality and speed of those very parts can be checked as often as needed. The outcome in terms of performance of each individual user interaction tested is then saved into the same central time series data base as the performance metrics registered from all original sources of interest (such as Perfmon data, ESX performance data, etc.) It is then possible to perform a multiserver zoom and with a single click to navigate to the most interesting servers during time periods where Alyvix detected problems.

Screenshot from 2017-05-29 10:42:58

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Synthetic Application Monitoring with Alyvix

Posted by on May 9, 2017 in NetEye, Real User Experience Monitoring | 0 comments

Alyvix Training - Synthetic Application Monitoring

Synthetic Application Monitoring:

Allows monitoring applications from the user’s point of view by simulating transaction sequences, followed by the measurement and recording of the perceived performance data.

Would you like to be independent from subjective statements as “application XY is slow” or outage indications from your users? In this case, the concept of synthetic application monitoring and the corresponding monitoring tool Alyvix are right for you. If you are interested to get to know this concept and tool, the Synthetic Monitoring Training offered by Würth Phoenix might be the right choice.

Synthetic Monitoring Training 2017

13th to 14th June – Bolzano/Italy

20th to 21st June – Niedernhall/Germany

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Remote banking monitoring with Alyvix and NetEye

Posted by on Dec 13, 2016 in NetEye, Open Source System Management Conference, Real User Experience Monitoring | 0 comments

RemoteBanking_Header_Alyvix
Massimo Giaimo, Senior System & Network Administrator at IBT, shares his experience with Alyvix and NetEye.

What are the most recent significant changes in the application monitoring?

For decades, IT departments have mainly implemented performance-monitoring strategies through the control of the uptime of the systems. Only in recent years, companies realized that is not sufficient to monitor the availability of the infrastructure. To ensure customer satisfaction and the proper functioning of the delivered services it is essential to measure the End User Experience. Response times, failed interactions and real use are now the new monitoring metrics.

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Are you wasting many hours by executing repeating tasks?

Posted by on Nov 21, 2016 in NetEye, Real User Experience Monitoring | 0 comments

Hand simple tasks over to Alyvix. In this way, you will be able to save precious working hours and in turn, to invest your precious time in more important activities.

Automation of repeating tasks with Alyvix

Alyvix has been designed to simulate real user inputs or actions, to check if an application runs correctly and to register its performance values in order to compare past and actual application performance values. Through such comparisons, it is possible to detect application performance degradations (for example after an update).

Since such simulations turned out to be a good thing, it came to my mind to use Alyvix also to execute repeated tasks, which otherwise an employee had to do. Do you know what I mean? Let me explain it through a real life example:

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How to use anomaly detection to create smarter alerts

Posted by on Nov 11, 2016 in Network Traffic Monitoring, Real User Experience Monitoring | 0 comments

Alarms and monitoring go hand in hand. Whenever an algorithm or threshold is used to decide whether the current value of a registered KPI should rise an alarm or not the result can be a hit, a correct reject, a miss or a false alarm.

threshold

The standard way to rise alarms is studying standard traffic – which should not rise alarms – and deciding on a static threshold based on the historic standard traffic (For example see Figure 1) and experience. Everything below the threshold is than considered as standard traffic and everything above rises an alarm. This kind of threshold-based alarm creation is robust to many outliers and might be sufficient if the mean of the standard traffic does not change dynamically (in that case the threshold needs to be adapted dynamically, too). Signals might contain also anomalies that are quite useful for problem detection that look very different from classic (more or less extreme) outliers. For example a change in the distribution or similar (see Figure 2, red area on the right) can be a first sign of instability and taking an immediate counter-action can prevent the anomaly turning into a real problem.

median

For this reason the study of alternative more sophisticated alerting mechanisms is a useful addition to current common practice.

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