servicenav innovation

Beyond innovation

Save time, availability and IT performance to serve the business. How do you deliver on this promise?

AIOps monitoring platforms combine multiple data source collection, Big data and machine learning architecture, and a unified interface to provide a unique experience for IT production users and IT service consumers.

ServiceNav's development is part of this revolution and its ambition is to put the latest technological innovations at the service of its Clients, to which it contributes.

Innovation archi Work plan 1

Core Architecture

Designed for the SaaS monitoring

in a multi-client, multi-site context

From the very beginning of its development -2007-, the ServiceNav product was designed for SaaS monitoring in a multi-client, multi-site context, based on simple principles: minimizing data volumes on the Internet to reserve bandwidth (scarce at the time) for production flows, no compromise on security, making data collection reliable, data model facilitating product learning and at the same time sticking to the reality of the networks, quick and easy deployment and use. The architecture of the platform is based on its principles: ServiceNav Box collectors as close as possible to the objects to be monitored, wherever they are on the Internet, no incoming data flow, inter-component communication bus, resumption of data exchanges in case of flow interruption, integrated park updates, deployment of a ServiceNav Box in less than 15 minutes, monitoring configuration without Nagios knowledge or need for Linux expertise.

Big Data

The ServiceNav software architecture carries the foundation for a new generation monitoring platform

The year 2015 marks a breakthrough in ServiceNav's innovation strategy. Coservit was able to demonstrate its know-how in a competitive market. The context of SaaS monitoring is: data, even more data, in various forms: metrics, traces, logs. This digital data provides a great deal of technical information in real time on the state of health of the supervised IT assets. Our SaaS business model and our multi-tenant architecture accentuate these massive data management issues. A large part of our R&D projects is therefore focused on the issues of elasticity, robustness and self-management of distributed systems capable of supporting hybrid cloud and Big Data operating models.

As a member of the steering committee of the Minalogic competitiveness cluster, Coservit actively participates in regional innovation development events and actions. In this context, Coservit is working to bring together the teams of the Grenoble Computer Science Laboratory with the R&D teams of leading industrial companies in the field of Big data analytics (Salesforce, HP Innovation Center, LIG, etc.). To this end, Coservit is leading an ambitious collaborative project, Smart Support Center The project was awarded the Minalogic label and received funding from the French government's single interministerial fund (FUI). Following this success, which has led to the creation of more than twenty jobs, the ServiceNav software architecture is the foundation of a new generation monitoring platform: multi-source collection, automatic discovery of objects to be monitored, horizontal and vertical scalability to absorb, process in real time and store massive volumes of data.

Bigdata innovation


The possibilities of the Dataviz module of ServiceNav are unlimited

Communicating and restoring know-how in the simplest of ways: data contains relevant and valuable information for communicating on the performance and availability of the information system, as well as for steering its future development. As early as 2017, we wanted to revolutionize the way this information was produced and shared. The possibilities of ServiceNav's Dataviz module are limitless, and go beyond the dissemination of technical information to venture into business dashboards, monitoring processes at the heart of your organization. The innovation concerns the ergonomics and the simplicity of design and distribution.



AIOps combines theIA
and the Big data
to automate incident detection and resolution.

The high availability of information systems requires efficient supervision tools. The rise of connected objects and the increasing complexity of digital environments call into question the traditional tools of IT departments. To meet these challenges, our project aims at a new generation of "AIOps" software, as formalised by Gartner. AIOps combines AI and Big data to automate incident detection and resolution. Currently, 50% of detections are not relevant, structurally altering the performance of support teams. On a large scale, the stakes are colossal. In 2019, Gartner sees a 25% increase in customer requests on AIOps. This technology applies to many areas: Industry of the Future, mobility, health. We are first targeting our respective historical markets: IT outsourcing companies and 4.0 industries.

The injection of decisive analytical components into the ServiceNav architecture is already a reality, with the status prediction functionality. The challenge is to detect weak signals before alerts appear. Consequently, to process these potential alerts at the right time: during the day, mobilizing the competent resources when they are available, minimizing the costs and disorganization linked to working outside working hours.

In parallel, Coservit is initiating the R&D BOOSTER 2018 (Smart Incident Detection Project). This collaborative project aims to reduce the volume of false alarms by half, thus improving the productivity of Service Centers. This project leads to the design and experimentation, in a representative environment, of new Big Data implementations for the massive processing of new algorithms. In the context of the convergence of connected objects, the complementary nature of the partners will enable the prototyping of a central Artificial Intelligence platform to initiate a new generation of supervision solutions in a SaaS model on a large scale. In addition to advancing the science of Artificial Intelligence and massive data processing for which the regional ecosystem is already recognized, the techniques developed allow ServiceNav to differentiate its product offering on its market.

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