Self Driven Networks

Networks that combine telemetry, workflow-automation, DevOps and AI

Self Driven Networks

What are Self Driven Networks?

Self-driven networks are networks that combine telemetry, workflow-automation, DevOps and AI. By combining all these techniques, the network can adapt in a responsive way to the changing circumstances. 

Besides this, a self-driven network can also detect proactively certain problems and changes in the network to avoid problems and interruptions. 

The concept self-driven network is not only about the network. The user experience is key. That’s why the infrastructure needed to manage the network can’t be an issue anymore. This is not the part where most of the resources of the IT-team should go to. Because of this philosophy a self-driven network is fully Cloud-based in terms of management and monitoring. 

A self-driven network also isn’t dependent on the infrastructure needed to manage it. It doesn’t matter if the network is small of large, the infrastructure scales when the network is growing. 

Aspects of Self Driven Networks

A self-driven network is built on multiple aspects: 

  • Self-discover: The network discovers changes in terms of hardware, software and network. It uses this data to run the decision process.
  • Self-Config/Self-Organize: When specific changes are occurring, the network makes changes to anticipate.
  • Self-Monitor: A self-driven network doesn’t need a separate monitoring system. The network is continuously monitored on different parameters and responds or reports when needed.
  • Self-Diagnose: When there are anomalies, the network will use AI and Machine Learning to search for the cause and a possible solution.
  • Self-Healing: When the network is in a degraded state due to changes or problems, the network will respond and will bring the network back in a healthy state.
  • Self-Report: When there are certain problems that can’t be solved, the network will create events or actions for the IT-team. 

As a result you actually get a continuous cycle. Data enters the cloud (network traffic, logs,…) and the network analyses this data. Based on this analysis, the network will make certain decisions (optimisation of the network). This way you get a new network configuration (e.g. in case of WiFi adjusting channels, power,…) which will generate new data to be analysed by the network. 

Extreme Networks

Extreme Networks is already known for their CloudIQ ecosystem where access points, switches and 3rd party devices (monitoring via the XIQ Site Engine) can be managed. Recently it also made the CoPilot available in public beta.

The CoPilot processes all data using Machine Learning and AI and then shows in one page what possible problems are on the network. In this way, it is faster to find what possible problems are and easier to troubleshoot.

Extreme Networks is also working on the AutoPilot which also solves problems by itself when needed. This way it is a self-healing product.

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A recognized integrator in Luxembourg for many years, SIMAC PSF relies on a well-established partnership with Kappa Data for security solutions.

Simac, Claudia Koenig

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