Control-Plane Modelling

NetBrain begins by building a data model of the entire network, including the full control plane logic, analyzing up to 12,000 variable types (e.g. route tables, BGP peers, etc.)

Building this robust data model creates the end-to-end visibility and system access necessary to power network automation tasks. Based on this discovered network model, Dynamic Map and Executable Runbooks are enabled across any part of the multi-vendor network.

Out of the box, NetBrain supports over 150+ vendors.

Deep Network Discovery

NetBrain’s auto-discovery engine supports a variety of network technologies and discovery methods, using live data collected via API, CLI, and SNMP. Traditional networks, SDN/SD-WAN, and virtualized devices are knitted together to build a consistent view of the entire network. This comprehensive view enables the network operator to manage their heterogeneous network as one.

Through auto-discovery, everything about a running network and its condition – including inventory, multi-tiered topology, network design and network baseline – is modeled and ready to be used with NetBrain’s main features – the Dynamic Map and Executable Runbook.

netbrain domain management network discovery

Single-Source-of-Truth via CMDB

NetBrain CMDBCustomers often have a Configuration Management Database in place to store information about hardware and software assets. NetBrain can take existing client inventories into account when performing its initial discovery.

Via integration through its REST API, NetBrain can sync up with other data sources, serving as a primary or secondary CMDB with additional features and capabilities.

Scheduled Network Benchmarks

netbrain network benchmarksIt’s challenging to keep your network documentation updated to reflect dynamic changes. NetBrain catalogs these changes automatically by taking routine snapshots, or ‘benchmarks’ of the network.

The basic system benchmark can regularly collect live data as baselines to build topology, calculate paths, device groups, sites and MPLS Virtual Route Tables.

The user defines what network data should be retrieved, and NetBrain executes this operation on every device currently discovered within the domain.

Golden Network Baseline

NetBrain uses your system benchmarks to develop its own understanding of healthy or nominal network conditions. As part of this process, NetBrain can discover and interpret up to 12,000 variables such as CPU utilization, memory usage, routing tables, duplex settings, collisions, and BGP peers.

Powered by persistent AI analysis, the Golden Baseline defines what’s “normal” for a complex network. Once the golden baseline is complete, it can generate alerts on deviations from specified variables or patterns. It can also be used as a basis for network management analysis and troubleshooting.

This feature is utilized heavily within NetBrain’s automation framework and is critical to understand “Is this expected?” during any network problem investigation.

netbrain golden baseline compare

Scale for Enterprise Networks and Big Data

enterprise grade network scalabilityNetBrain is designed to handle even the largest networks, scaling to 100,000+ network nodes with thousands of concurrent users. This scalability is achieved by modular software architecture that can scale horizontally.

NetBrain can be deployed across multiple data centers, environment types, and supports disaster recovery for all discovered devices.