Based on modern container technology and bundled with unique purpose-built container-aware block storage, Robin Cloud Platform, powered by containers, enables application and data lifecycle management to plan, build and operate large-scale infrastructure. This capability is way more than the limited capability offered by the moving parts of the component-based stack for Big Data and databases in your data center.
Robin Cloud Platform (RCP) marshals all your existing commodity hardware resources into a scalable and elastic pool of compute and storage resources for Big Data and databases across the data center.
Without Hypervisor Overhead
Workload, Guarantee QoS
App Lifecycle Management
- Eliminate hypervisor performance penalty
- Get bare-metal performance for your Databases
- Improve IO throughput by 40%-60%
- Contain database and OS sprawl
- Gain app-to-spindle performance guarantee
- Eliminate noisy neighbor issues
- Enable 1-click application deployment
- Create clones, snapshots for time-travel
- Tame complicated distributed applications: Hadoop, Cassandra, Oracle
Robin Cloud Platform Features Overview
GUI based management for Big Data and databases in your data center
App-to-Spindle Guaranteed QoS
1-Click Simple Application Deployment
Snapshot and Restore
Simplified Application Upgrade
Decoupled Model Overview
Decoupled mode allows separation of compute and storage. This enables users to right size hardware for each layer. Users can buy high CPU and memory configuration for the compute nodes and while the storage nodes can be optimized for capacity.
With the decoupled mode, Robin Cloud Platform also allows users to decouple compute from storage and scale each layer interdependently. Tightly coupling compute and storage requires users to scale both these layers in lock-steps which could lead to resource wastage. For instance, if users need more storage capacity for data, they are forced to add compute capacity as well. Similarly, when users just need more compute capacity, they are unnecessarily adding storage capacity as well. For
For a data-heavy application, data volume growth will most likely be much faster than growth in concurrent workload. Not having a way to scale storage independent of compute is therefore not a viable option in many cases. This is one of the many reasons traditional hyper-convergence is not always suitable for the data-heavy workloads.
Hyperconverged Model Overview
If some users really like the “hyper-converged” mode, Robin Cloud Platform supports that as well.
In converged node deployment mode both compute and storage layers are co-located on the same physical servers. This allows for data and compute locality for applications like Hadoop (to avoid network becoming a performance bottleneck while moving very large data volumes).
Only Robin Cloud Platform provides users the flexibility to choose either decoupled or hybrid modes – or use a combination of the two – depending on the business/application needs.