IT monitoring from the user’s perspective

The passive monitoring of Real User Experience

The innovative Real User Experience (RUE) of NetEye allows to understand and improve the performances of the applications and cloud services experienced by the users and customers. Through a passive monitoring RUE identifies on real time every transaction, measuring the availability, response time and all the Key Performance Indicators useful to evaluate the level of the delivered services.

The bottlenecks on performance are, therefore, discovered including the impacted users, applications, networks or working stations. This proactive approach aims to continually improve all business critical services as e-shops, ERP or CRM, by obtaining not only an higher customers/users’ satisfaction but also avoiding possible turnover loss.

What carachterizes our solution?

  • Thanks to the RUE module, NetEye goes well beyond the traditional Open Source monitoring systems providing real time metrics to measure the end user experience for the delivered services
  • RUE is an Open Source solution that offer flexibility and freedom of usage andprovides a wide range of features but at much lower investment costs compared to notorious proprietary systems
  • The solution is rapidly installed and deployed, also thanks to the autoconfiguration system that calculates automatically the baselines
  • NetEye and RUE are designed based on the experience gained through the years and according to our customer business  needs. The solution ensures not only the internal control of the infrastructure but also guarantees that the performances of the services offered to the users/customers are meeting their expectations
  • RUE is a passive approach that does not influence the performances of the infrastructure and that allows to register and analyze on real time millions of transactions by collecting the network traffic through the adoption of a probe
  • RUE analyzes the details on the single transaction, detects possible slowness on performance  by identifying the cause in the IT infrastructure

Statistics and Machine Learning Techniques for RUE

In the age of the cloud the optimization of real end-user experience (RUE) is getting essential for success. On the one hand users expect applications to work faultlessly independent of the time, location, and device one is using them from. Application performance monitoring (APM) is therefore often based on RUE performance metrics. On the other hand, network performance monitoring (NPM) plays an increasing role in the understanding of how an application is working across the network and how potential impacts on the application performance are caused by servers or the network – application-aware network performance monitoring (ANPM). Common goals of APM and NPM are to use performance metrics measured by RUE to ensure user satisfaction by detecting problems as soon as they occur in order to resolve any potential issues before the end-user gets aware of them. During the last few months, we have examined different machine learning and advanced statistics techniques, to extract the most information ever from performance metrics measured by NetEye RUE. 

All study details can be found:

How can RUE help to manage the IT service in the ITIL processes?


  • Demand management – RUE identifies the number and the frequency of accesses to the various services by customers/users discovering eventual peaks on demands. In this way it is possible to conduct a thorough analysis which allows during the strategic stage to adapt the correct capacity of the resources or to define new service lines aligned with the business needs


  • Service Level Management – thanks to the KPIs provided by RUE you can check that the level of service agreed in the SLA contracts is respected. RUE, in addition, provides useful information to redefine or change the thresholds for the services agreed with the customers
  • Capacity Management - with the detection of the cause of deterioration in the performance, it is also possible to identify the IT components involved and rationally plan the resources needed to maintain the agreed levels of service
  • Supplier Management - thanks to the Key Performance Indicators the supplier manager can define and / or modify the contracts with external suppliers in a more accurate way, ensuring that they are aligned with the needs of the business and in particular with what is established in the SLR (Service Level Requirement) and the SLA (Service Level Agreement)
  • Availability Management – by monitoring the various services from the user perspective it is possible to work proactively and ensure that the level of availability guaranteed for all services equals or exceeds the current and future requirements of the business


  • Change Management - through the rapid identification of performance anomalies due to the introduction of new applications, releases and modifications on the components it is possible to prevent possible problems during the delivery of a change
  • Release and deployment Management – it is possible to analyze the impact of new releases on the users and trace the source of eventual deterioration in the performance


  • Problem Management – Incident Management - thanks to the number of impacted users and to the urgency given by the criticality of the service, you can define the right priority to the various problems and incidents


  • The 7-step Improvement Process - thanks to the detailed analysis of the transactions provided by RUE it is possible to identify and interpret the performance issues in order to act proactively and continuously optimize the IT services

Overview of the main features

  • Viewing performance divided into networks, groups of networks, workstations, applications or groups of applications
  • Creation of alerts generated by the deviation of Key Performance Indicators from the standard levels (baselines) to react proactively in case of degraded performance
  • Rapid identification of the root cause of the degradation of performance, attributing it immediately to the network, to the application, to the client or to the service provider Cloud
  • Prioritization based on the impact and urgency given by the number of users involved and the degree of criticality of the service
  • Measurement of Key Performance Indicators to ensure that the levels set out in the contractual SLA, OLA or SLR are respected
  • Evaluation of the level of service provided from perspective of the users/customers
  • Performance monitoring of all web applications and cloud services
  • Detailed analysis up on single transactions with the identification of the source, target IP addresses and all the other Key Performance Indicators
  • Reporting and performance trends of the various services
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