Make security accessible by meshing Gigamon with your network and security services
The Gigamon Hawk deep observability pipeline harnesses actionable network-level intelligence to amplify the power of your cloud, security, and observability tools. This powerful combination enables you to assure security and compliance governance, speed root-cause analysis of performance bottlenecks, and lower the operation overhead associated with managing your hybrid and multi-cloud IT infrastructures.
Gigamon traffic data is retrieved by appNovi through API to aggregate network connections between endpoints across the network including hybrid and multi-cloud environments. When Gigamon data is aggregated with other cyber asset data sources users search across all cyber assets to identify those with security control gaps. Saving queries with integrated outcomes provides the ability to automatically identify gaps in security controls and automate remediation through your existing orchestration solution.
Gigamon’s traffic is aggregated alongside other traffic in appNovi for complete visualization of your network connections between cyber assets across your multi and hybrid cloud environments. Understanding cyber asset network connections enable the identification of application components, their owners, and business significance to enable informed risk management and ensure a non-disruptive incident response.
Improve Vulnerability Management in 2023
Every enterprise must identify and manage vulnerabilities across the network. And the network continues to change – bare metal machines, virtual infrastructure, and the increasing prevalence of containers. But IT assets are more than just infrastructure – they...
appNovi Solution Brief
Learn about the appNovi cybersecurity mesh platform for attack surface identification and mapping, vulnerability management, and incident response enablement.
Explore how appNovi can help you align to CIS controls to mature vulnerability management, attack surface mapping, incident response, and data center migration processes.