Remote Office Monitoring
Network Monitoring Sensors
The agents are small Ethernet and WiFi appliances that verify network connectivity, Internet speed, DNS, and run transactions with web applications. Network monitoring from the user perspective assures that the network is always available and well performing.
When one or more sensors detect an anomaly, the dashboard reports if the problem is related to the network, application, or WiFi network.
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“NetBeez gave us a proactive troubleshooting tip for a problem that could have gotten worse at a later time.”David FloresSenior Network Administrator at Kingston
“We realized we needed a solution that gives us different points of measurement to collect the data we needed to effectively determine the cause of the reported issue...NetBeez is a must-have tool for the connected multi-site enterprise.”KeithDirector of Cloud Services at TMW
“We have found Netbeez to be invaluable in illuminating areas of our network that we would normally not be able to see, to quickly be able to make an issue determination and remediation plans.”GavinISP Systems Engineer at Trustpower
The Ethernet sensor is a small-form factor appliance that can be deployed in remote offices and connected on a switch or a router to monitor the performance of the LAN and WAN.
Ethernet (GigE model)
CPU: 1.91 GHz quad-core (Intel Atom)
RAM: 2 GB
Disk Drive: 8 GB
Ethernet NIC: 10/100/1000 Mbps (RJ-45)
Here’s how it works
NetBeez is a simple plug-and-play solution that scales from few locations to hundreds. The agents are connected to a switch port, to the WiFi network, or installed as virtual machines.
The agent management and network monitoring data is done via the dashboard, which can run on-premise as a virtual appliance, or in the cloud.
NetBeez enables network engineers to be more efficient to manage a WAN that has many remote locations.
Network monitoring from the user perspective will enable network engineers to:
1. Detect network issues before users call the help desk
2. Troubleshoot network versus application issues
3. Identify performance degradation trends with real-time data