Storage Developer Conference

NVM Express is predominately a block based protocol where data is transferred to/from host memory using DMA engines inside the PCIe SSD. However since NVMe 1.2 there exists a memory access method called a Controller Memory Buffer which can be thought of as a PCIe BAR managed by the NVMe driver. Also, the NVMe over Fabrics standard was released this year that extended NVMe over RDMA transports. In this paper we look at the performance of the CMB access methodology over RDMA networks. We discuss the implications of adding persistence semantics to both RDMA and these NVMe CMBs to enable a new type of NVDIMM (which we refer to as an NVRAM). These NVRAMs can reside on the IO sub-system and hence are decoupled from the CPU and memory sub-system which has certain advantages and disadvantages over NVDIMM which we outline in the paper. We conclude with a discussion on how NVMe over Fabrics might evolve to support this access methodology and how the RDMA standard is also developing to align with this work.

Learning Objectives: 1) NVM Express overview; 2) NVMe over Fabrics overview; 3) Using IO memory as an alternative to NVDIMM; 4) Controller Memory Buffers in NVMe; 5) Performance results for new access method.

SMB3 is the default Windows and MacOS X file sharing protocol, but what about making it the default on Linux ? After developing the UNIX extensions to the SMB1 protocol, the Samba developers are planning to add UNIX extensions to SMB3 also. Co-creator of Samba Jeremy Allison will discuss the technical challenges faced in making SMB3 into a seamless file sharing protocol between Linux clients and Samba servers, and how Samba plans to address them. Come learn how Samba plans to make NFS obsolete (again :-) !

Learning Objectives: 1) SMB3; 2) Linux; 3) Windows interoperability.

A discussion of the Hyper-V Storage Quality of Service protocol (MS-SQOS) and updates to networked storage requirements for Windows Server 2016 virtual machine hosts. This session is targeted at engineers and product managers of providers of networked storage to Hyper-V hosts and anyone else interested in how Hyper-V hosts utilize storage. Those attending this session should be able to gain familiarity with customer scenarios around storage quality of service, should be able to describe the purpose and scope of the MS-SQOS protocol, and should understand how Windows Server 2016 made changes to how it uses networked storage.

Learning Objectives: 1) Describe the purpose and scope of the MS-SQOS protocol; 2) Become aware of customer scenarios around storage quality of service; 3) Enumerate updates in how Hyper-V hosts use networked storage in Windows Server 2016.

Traditional disk based storage arrays commonly use various forms of RAID for failure protection and/or performance improvement. Modern distributed storage systems are built as shared nothing architectures using commodity hardware components and have different failure characteristics.

RAID has changed very little ever since its introduction three decades ago. There are several new and powerful constructions of erasure codes in the recent past (post- 2007) that were handcrafted to meet the needs of modern storage architectures. Several notable ones are fountain codes, locally repairable codes (LRC) and regenerating codes. However, these codes have made very little impact in the industry, because of the highly resistant nature of the storage vendors to investigate this space.

The subject of erasure codes is core to storage technologies, but is sadly ignored by most storage conventions. One of the reasons could be the complexity involved in understanding the space.

This talk will provide a non-mathematical, non-marketing, no-nonsense spin to the space of modern erasure codes. By the end of this talk, the audience will be able to pick specific categories from a bouquet of erasure codes that best suit a given storage system design.

Learning Objectives: 1) History and classification of erasure codes; 2) Technical deep-dive into modern erasure codes; 3) Storage system parameters’ trade-off; 4) Storage system design & suitable codes; 5) Who is doing what in this space.

Storage virtualization is gaining popularity as an efficient way to increase the flexibility and the consolidation of data centers. Virtualization is commonly used to provide fast and reliable storage access and therefore constitute an important factor to fulfill customer’s demand for a minimum latency in cloud storage applications. This work introduces a new approach for implementing the iSCSI extensions for RDMA protocol (iSER) using block virtualization techniques. The iSER protocol is implemented in the user-space using the common Libiscsi library and serve as the transportation layer protocol instead of the common TCP protocol. A unique implementation of a virtual block device using Quick Emulator (QEMU) is proposed to carry out block virtualization delivered over iSCSI.

The benefit of using iSCSI/iSER protocol over the common iSCSI/TCP is clearly demonstrated. Experiments results demonstrate average improvement factor of about 200% over the common iSCSI/TCP in term of average I/O operations per second while using the conventional Flexible I/O storage benchmark. The proposed approach is compared to two commonly iSER implementations used for block virtualization. Both methods use common iSER kernel modules. The first method uses a virtual-function while the second technique uses iSER block device virtualization. The proposed user-space iSER approach shows significant performance improvement over the two existing methods for different typical workloads. The current research results are promising and applicable also to future upcoming protocols such as NVMe over Fabrics implementations.

Learning Objectives: Storage virtalization, RDMA, iSER, QEMU.

For years, enterprises have desired a way to ensure that an application will operate properly at scale on a particular storage array and network infrastructure, and increasingly, ensure that multiple applications can safely run at capacity on an all-flash or hybrid architecture. Companies need an approach that enables users to reference detailed workload analysis profiles as they build and share workload models, and simulate performance across a variety of vendors, products and technologies.

Learning Objectives: 1) How to determine what the traffic related to an enterprise application implementation looks like from the perspective of the network infrastructure between application servers and storage arrays; 2) How the application I/O workload can be modeled to accurately represent the application in production using storage analytics or vendor performance statistics to generate a synthetic workload model; 3) How a statistical application model can be used to validate both array and network performance at varying traffic levels and rates to rapidly test if/then scenarios; 4) How multiple application models can be combined to determine appropriate throughput and response time levels on a given array; 5) How using these models can enable engineers and architects to cost-effectively test and confidently deploy new networked storage infrastructure.

NVMe SSDs are becoming increasingly popular choice in scale out storage for latency sensitive workloads like databases, real time analytics, video streaming. NVMe SSDs provide significant performance throughput and lower latency compared to SATA, SAS SSDs. It is not unrealistic to expect these devices providing close to million random IOs per second. However scale out software stacks have significant amount of software overhead limiting the immense potential of NVMe SSDs. In this session, we present all flash scale out cluster performance, analysis on data path I/O overhead and programming techniques to systemically address software performance barriers.

Learning Objectives: 1) Scale out storage software data path flows; 2) Performance profiling with NVMe SSDs; 3) User mode v/s kernel mode NVMe SSD integration; 4) Optimization techniques.

A new class of ultra low latency remote storage is emerging - nonvolatile memory technology can be accessed remotely via high performance storage protocols such as SMB3, over high performance interconnects such as RDMA. A new ecosystem is emerging to "light up" this access end-to-end. This presentation will explore one path to achieve it, with performance data on current approaches, analysis of the overheads, and finally the expectation with simple extensions to well-established protocols.

With a design started in 2006, OpenIO is a new flavor among the dynamic object storage market segment. Beyond Ceph and OpenStack Swift, OpenIO is the last coming player on that space. The product relies on an open source core object storage software with several object APIs, file sharing protocols and applications extensions. The inventors of the solution took a radical new approach to address large scale environment challenges. Among them, the product avoids any rebalance like consistent hashing based systems always trigger. The impact is immediate as new machines contribute immediately without any extra tasks that impact the platform service. OpenIO also introduces the Conscience, an intelligent data placement service, that optimizes the location of the data based on various criteria such nodes workload, storage space. OpenIO is fully hardware agnostic, running on commodity x86 servers promoting a total independence.

Standardization efforts have continued for features to improve SSD performance and endurance. NVMe, SCSI, and SATA have completed standardization of streams and background operation control. Standardization is beginning on how SSDs may implement Key Value Storage (KVS) and In Storage Compute (ISC). This effort is progressing in the SNIA Object Drive Technical Work Group (TWG), and may involve future work in the protocol standards (NVMe, SCSI, and SATA). Currently the Object Drive TWG is defining IP based management for object drives in utilizing the DMTF RedFish objects. Future Object Drive TWG work will include APIs for KVS and ISC. This presentation will discuss the standardization of streams, background operation control, KVS, and ISC and how each of these features work.

Learning Objectives: 1) What is streams; 2) What is background operation control; 3) Progress of standardization in NVMe, SCSI, SATA, and SNIA.