Hystax Acura pioneered cross-hypervisor Disaster Recovery and stores customer data and snapshots in a cloud-native format, ready to use in case of failover.
No cloud modifications are required to support Disaster Recovery scenarios, only native API is used to create basic routines like volumes, snapshots, subnets and virtual machines.
Hystax Acura uses EBS and cinder functionality to create volumes and snapshots on Amazon Web Services and OpenStack / KVM. No underlying hardware or SDN is used – any storage can be used for storage which helps customers to work with familiar solutions and re-utilize existing hardware in case of Disaster Recovery to private cloud.
Hystax Acura agent consistently replicates business applications on a protected platform, calculates deltas and sends them to a snapshot storage. Data is stored in a ready-to-launch format.
All P2V / V2V processes are fully-automated and executed in the background.
The solution supports orchestration and lets configure dependencies between components of business applications.
Restored machines are not tied to Hystax Acura – there is no performance impact in case of failover.
Hystax Acura provides you with powerful and flexible DR plans which contain all necessary information to recreate your original production workloads. DR plans are generated automatically based on replicated infrastructure, you just need to revise it. Hystax Acura supports cloud orchestration and recreate infrastructure in a pre-defined order.
Regular automatic DR plan testing is available. Hystax Acura will automatically create a cloud site from your DR site and run a bunch of test scripts. Testing reports are available.
Hystax Acura provides two-step deduplication and WAN optimization that reduces network and storage utilisation up to 70%
Hystax Acura is covered with RESTful API, you can build own DR and self-healing scenarios upon the solution
Hystax Acura provides instant recovery from any restore point with a few clicks. You can easily restore all changes from DR site back to production workloads within a regular maintenance period