Maginatics Cloud Storage Platform for Elastic NAS Workloads Optimized for Cloud Maginatics Cloud Storage Platform () is the first solution optimized for the cloud. It provides lower cost, easier administration, and better scalability and performance than any alternative in-cloud platform, especially for scale-out workloads, the most likely to benefit from migration from traditional infrastructure to a cloud environment. Indeed, is the only storage solution that enables organizations to take full advantage of the economics, agility and elasticity of the cloud for running scale-out workloads. Inhibitors to Cloud Adoption The cloud is the ideal platform for running the scale-out workloads found in a range of disciplines from Media and Entertainment (e.g., batch video rendering) to Life Sciences (e.g., multistep genomics analysis). Even large-scale Web farms can benefit from in-cloud operation. The reason, quite simply, is the effectively infinite compute and storage resources available in the cloud. To run these applications in the cloud, organizations must either re-write them or, more often, use a legacy file system backed by volumes of block storage. At scale, these legacy file system approaches are costly to build and maintain because of: The number of compute nodes dedicated to the storage cluster. The requirement to pre-allocate capacity. The need to use block storage rather than more cost-effective objectbased storage. The inefficiency of the local and network RAID required for data protection.
delivers the scalability and performance of cloud computing without trade-offs or compromises and eliminates the price premium that accompanies the use of legacy solutions for these deployments. Translating Traditional Storage Architectures to the Cloud Most legacy solutions for scale-out workloads replicate, in the cloud, the same storage configurations used in physical data centers. This forces system administrators to go through capacity and performance planning just as they would with a traditional storage system, limiting agility, a key benefit of the cloud. In addition, the fault tolerance and data protection mechanisms required by these file systems increase cost by reducing data efficiency and, for certain workloads, can adversely affect system performance. Costs of alternative solutions are also driven by the need for a cluster of compute nodes just to stand up the storage cluster and the relatively expensive (block) storage that must be pre-allocated whether it is used or not. boasts a significant cost advantage over these systems because of the small compute footprint (the Magiantics Virtual Filer) dedicated to the storage cluster, the use of less expensive and ondemand capacity, and the built-in reliability of object storage which eliminates the need for local or network RAID. On the following page, figures 1 and 2 provide examples of the cost difference between and, a leading alternative open source solution, over a six month period for a typical multistep genomic analysis workload. With scale-out workloads moving to the cloud, there is a need for new storage architectures to take full advantage its benefits, especially elasticity. addresses that need head-on. Another inhibitor to migrating workloads to the cloud is the time required to move data to the cloud in the first place. not only provides superior in-cloud performance, it accelerates initial data injection thanks to its native WAN optimization capabilities and distributed architecture.
Cost of a 50 TB workload over 6 months $800,000 $700,000 $709,657 $600,000 $500,000 $400,000 $300,000 $200,000 $100,000 $158,478 $85,956 $0 0.6 TB/node 6 TB/node Figure 1: Cost comparison of and including cloud, support and license expenses for a 50 TB workload Cost of a 15 TB workload over 6 months $250,000 $200,000 $214,352 $150,000 $100,000 $50,000 $51,681 $35,177 $0 0.6 TB/node 6 TB/node Figure 2: Cost Comparison of and including cloud, support and license expenses for a 15 TB workload
The Benefits of vs. Alternative Solutions in the Cloud The benefits of versus alternative solutions can be summarized as follows: No scale-performance trade-off The Maginatics MagFS Agent on each worker node provides consistent, unabated access to all data in the underlying shared object storage capacity pool. Because all worker nodes have their own native connectivity to the object store yet maintain a consistent view of the namespace, adding more worker nodes, more data or both does not affect data access. The following figures provide examples of the aggregate throughput of and FS, with multiple concurrent clients. The FS cluster is comprised of three replicated nodes in 4x50GB RAID0 configuration. Multi-Client Writes with Small Files 4 Clients (1,000 1 MB) 1024 KB 77 472 Block Size in KB 512 KB 256 KB 77 81 440 473 FS 64 KB 110 448 0 100 200 300 400 500 Aggregate Bandwidth in MB/sec Figure 3: Multi-client throughput comparison between and FS for small files.
Multi-Client Writes with Large Files 4 Clients (2 5 GB 2) 1024 KB 75 300 Block Size in KB 512 KB 256 KB 68 81 310 329 FS 64 KB 77 319 0 50 100 150 200 250 300 350 Aggregate Bandwidth in MB/sec Figure 4: Multi-client throughput comparison between and FS, for large files. Up to 98.5% data efficiency without sacrificing reliability The inherent data durability afforded by object storage obviates the need for data striping schemes that impact performance and reduce data efficiency. For example, a public in-cloud storage cluster built with a legacy, block-based file system and replication across nodes can reduce data efficiency by more than 60%. This means that for a terabyte of raw capacity, the actual usable capacity is under 400GB. With, essentially each terabyte of raw capacity is usable. That is because the efficient metadata to data storage ratio. Elastic Storage Capacity With, you can add worker nodes as needed without having to reconfigure a storage cluster to add additional capacity. As new compute nodes are added, they immediately see a global namespace that is fully consistent across all nodes and that scales with the capacity of the underlying object storage.
Optimized data injection. enables organizations to accelerate data injection into the cloud via its native WAN optimization capabilities and distributed architecture. This is a major advantage versus alternative solutions, where the time needed to move data into the cloud is often an inhibitor of cloud adoption. The ability of to accelerate data over distance also accounts the efficient access it provides from geographically-distributed clients; e.g., for hybrid cloud and bursting scenarios. Conclusion Compared to both traditional and alternative in-cloud solutions, Maginatics Cloud Storage Platform reduces expenses, eases or eliminates the burden of administrative overhead, enhances scalability and improves performance for scale-out workloads running in the cloud. By delivering the full advantages of cloud economics, agility and elasticity for running these workloads, can improve an organization s efficiency, productivity and profitability while lowering its risk profile.