Essential applications can remain tied to ageing operating systems, delivery platforms or infrastructure long after the application itself remains valuable. Broad network access and virtual desktop layers can also add dependencies that are not needed for a particular workload.
Droplet NeverTrust places the application at its own security boundary. It contains the workload, applies policy controls and defines its permitted communications. This allows organisations to retain suitable applications while separating them from dependent operating systems and infrastructure layers.
Droplet NeverTrust is suited to containing modern and legacy application workloads, including workloads that need defined communications at the edge or in operational technology environments. It can provide contained application delivery as an alternative to unnecessary VDI and broad network access.
The product also supports assessment of whether validated workloads can move away from hypervisor or physical-server layers. Suitable AI applications, models and sensitive data can be kept within an owned boundary.
The product applies to suitable workloads in connected, constrained and disconnected environments. This includes edge and operational technology contexts, where workload communications need to be explicitly defined.
Keeps suitable business-critical applications in use while separating dependent legacy layers.
Supports assessment of whether validated workloads can leave VDI, hypervisor or physical-server layers.
Bounds workload communications to explicitly permitted paths.
Allows suitable workloads to be contained in connected, constrained or disconnected environments.
Contain a valuable legacy application separately from its ageing operating system and infrastructure.
Deliver an application in a contained boundary instead of providing broad network reach.
Apply containment and explicit communications to suitable edge and operational workloads.
Assess whether a validated workload can move away from hypervisor or physical-server layers.
Keep suitable AI applications, models and sensitive data inside an owned boundary.