VMware Carbon Black Cloud Workload™ delivers advanced protection purpose-built for securing modern workloads to reduce the attack surface and strengthen security posture.

Rachel Zhang Rachel Zhang VMware Presales at Dicker Data
Rachel Zhang

VMware Carbon Black Workload is for SMB

VMware Carbon Black’s VM protection solution, Carbon Black Cloud (CBC) Workload, is fully integrated in ESXi and vCenter; which, in most of the cases, is the only tool my customers are using to manage their virtualized environment. CBC Workload lets the vision of intrinsic security become more of a reality and relevant to small and medium enterprise users.

Firstly, there is no additional agent installation required, the sensor (agent) is built into vSphere (very light sensor: <1% average CPU usage, <1% average Disk usage, <1MB/day on network usage). With a single click, you can enable Carbon Black in your datacentre. After an easy deployment, the vCenter Server administrator will have the visibility of vulnerabilities in the entire environment. This helps the administrator to understand the security posture and schedule maintenance windows for patching and remediation.

This can be achieved by Workload Essential edition (licensed per socket), which is focused on identifying the risk with workload visibility and vulnerability management. In order to prevent malicious activities and protect VMs, customers will need Next-Gen Anti-Virus (NGAV) and Behavioural EDR features, which are available in the Workload Advanced edition. If you have to perform thread hunting, then it is time to upgrade to the Enterprise bundle which has features like live query for customisable detection, etc.

The Carbon Black Cloud gives workload protection for Windows and Linux virtual machines as well as Kubernetes clusters residing on vSphere, and it can be running at your own datacentre or in the public cloud. VMware Carbon Black Cloud Workload a flexible security solution no matter what size of the business it is.

VMware Carbon Black Workload Specs: 




Start a discussion, not a fire. Post with kindness



Subscribe to the Dicker Data blog

for regular updates and insights