Storage Developer Conference

As data-intensive workloads transition to low-latency NVMe flash-based storage to meet increasing user demand, the Fibre Channel industry is combining the lossless, highly deterministic nature of Fibre Channel with NVMe. FC-NVMe targets the performance, application response time, and scalability needed for next-generation data centers while leveraging existing Fibre Channel infrastructures. This presentation will provide an overview of why Fibre Channel’s inherent multi-queue capability, parallelism, deep queues, and battle-hardened reliability make it an ideal transport for NVMe across the fabric.

Learning Objectives: 1) A reminder of how Fibre Channel works; 2) A reminder of how NVMe over Fabrics work; 3) A high-level overview of Fibre Channel and NVMe, especially how they work together.

Nantero NRAM™ is a new class of memory with the potential to add non-volatility to existing RAM applications. It can be arranged in a crosspoint structure for large memories or a 1T-nR arrangement for smaller faster arrays, in standalone devices or as embedded RAM. NRAM uses carbon nanotubes in a dielectric-free structure to achieve unlimited write endurance. While there are obvious advantages to this class of device, including replacing DRAM in storage devices, there are a number of less obvious changes to how designers approach the data storage hierarchy. Decoupling cache size from battery backup power lets designers rethink performance profiles. Exploitation of various interfaces into the system are examined, from SATA to PCIe to the many options in the DRAM bus. This presentation also explores the growing application space for artificial intelligence, deep learning, and in-memory computing and considers the impact of a high performance non-volatile memory in those use cases.

Learning Objectives: 1) Awareness of performance characteristics of a DRAM-class non-volatile memory in crosspoint and 1T-nR configurations; 2) Non-obvious use cases for NRAM; 3) Application of non-volatile memory in AI / deep learning engines.

Leveraging the NVMe standard to present FPGA accelerators as NVMe namespaces allows user space code to access accelerators as simple block devices via standard in-box drivers. NVMe-over-Fabrics (NVMe-oF) is a network protocol for NVMe that is used to communicate between a host machine and NVMe devices over high-performance Ethernet networks. Leveraging NVMe-oF allows an accelerator, that presents as a standard NVMe namespace, to be shared across existing transports such as RDMA, TCP/IP or Fibre Channel. With NVMe-oF, client machines can borrow accelerators over the fabrics connection which can then be accessed as if they were local to the system, allowing the same user code to run on direct attached accelerators and over-Fabrics accelerators. The ease and granularity available when setting up the over-fabrics connections allows servers to share accelerators on demand, allowing for the disaggregation of acceleration compute resources. Using NVMe Controller Memory Buffer (CMB), the fabrics connection is further improved by allowing devices to send and receive data directory from the accelerator without accessing host memory. We will discuss the advantages of accelerator disaggregation and its impact on resource usage.

Learning Objectives: 1) Advantages and performance of NVMe for storage workload acceleration; 2) Performance of NVMe over Fabrics for storage workloads and acceleration; 3) Advantages of using Controller Memory Buffer coupled with NVMe over Fabrics.

Cloud-native frameworks are becoming a de-facto choice for deploying scalable micro-services. Flash based storage manageability in the container frameworks need to evolve to deliver scalable storage services to container workloads. OpenSDS (Linux Foundation project) aims to provide a unified software-defined storage control plane to simplify flash storage manageability to service on-prem and cloud micro-services. In this session, we present NVMe and NVMe over Fabrics (NVMe-oF) manageability architecture in OpenSDS using Swordfish APIs, a case study with Kubernetes and community roadmap to deliver unified flash manageability vision.

Learning Objectives: 1) Flash manageability using Swordfish APIs; 2) OpenSDS Linux Foundation project overview (unified storage control plane); 3) Container flash driver integration; 4) Kubernetes.

The SNIA’s Scalable Storage Management Technical Work Group (SSM TWG) has developed an open industry standard specification that provides a unified approach for the management of storage systems and data services. Swordfish™ is an extension of the DMTF Redfish specification developed by the Storage Networking Industry Association (SNIA) to provide a unified approach for the management of storage equipment and services in converged, hyper-converged, hyperscale and cloud infrastructure environments, making it easier for IT administrators and DevOps to integrate scalable solutions into their data centers.

This session will present an overview of the SNIA Swordfish specification, and will show how Swordfish takes and extends the Redfish specification to deliver the Swordfish storage model. It will also cover the drivers for the SNIA Swordfish approach, as well as providing a comprehensive overview of the functionality included in the Swordfish specification. It will also present an overview of common storage management use cases easily addressed by Swordfish.

Learning Objectives: 1) Understand why and how SNIA partnered with DMTF to create Swordfish; 2) Learn about the growing importance of Swordfish to the storage industry; 3) Get pointers to online Swordfish resources, communities and tools; 4) Discover storage management use cases for data center equipment and services.

NVMe over Fabrics is a powerful standard that provides fast access to non-volatile memory devices across fabric interconnects. An emerging NVMe-oF transport is good old TCP/IP. Its benefits are obvious, as it is fast, scalable, well-understood, and extremely simple to deploy. TCP/IP is, after all, the most widely used network protocol of them all, and well known and heavily-implemented in every data center. The major question is how to achieve high performance and low latency with TCP/IP. As most designers know, TCP/IP has pitfalls, such as timeout-based retranmissions and incast. However, performance results are very promising. The NVMe Technical Working Group is building both the standard and its open-source implementation in concert. Its prominent features include data integrity and transport layer security. In practice, NVMe/TCP is an excellent transport for networked flash and complements NVMe/RDMA and NVMe/FC nicely.

Two emerging interconnect efforts, OpenCAPI and Gen-Z, are top-of-mind today in system architecture and storage, including advanced platform support of Persistent Memory. Come hear distinguished leads from each project give an update on the goals, progress, and futures of each. Expect to learn both the differences and commonalities between these potentially symbiotic standards, and how they may enable new platforms and new storage solutions as they move forward.

Kubernetes supports external storage through volume plugins, however, the framework was built using generic concepts so as to work with all types of storage including legacy SANs as well as newer Software Defined Storage (SDS) solutions. As a result of this approach, Kubernetes cannot natively take advantage of some of the benefits of cloud-native storage systems like hyperconvergence, and also lacks native support for advanced storage monitoring and snapshots.

Dinesh will present STORK (STorage Orchestrator Runtime for Kubernetes) a new open source extension for Kubernetes, that provides additional intelligence and control for your storage. He will show how STORK can be used to co-locate pods with their data, deal with storage failures seamlessly and take application consistent volume snapshots through Kubernetes.

This talk will show how users can overcome limitations of stateful services and bulletproof them in Kubernetes using STORK. Dinesh will demonstrate how, using STORK, Kubernetes based applications can respond automatically to common failure modes like network partitions, and node and driver failures without downtime. He will talk about how this model can be extended for other drivers and the future roadmap.

Learning Objectives: 1) Optimizing stateful applications when using Kubernetes; 2) Running highly available stateful applications without any user intervention; 3) Creating and using application consistent volume snapshots with Kubernetes.

Today’s NVMe storage platforms now support massive quantities of NVMe devices, upwards of 96 drives per system. With all this growth comes new issues around Power delivery, airflow and aggregate performance. While newer architectures like NVMe-oF and in-memory platforms are being developed, they still treat the storage elements as simply ‘holding locations.’

Creating a paradigm shift with In-Storage Compute is a simple, scalable, low power solution that provides developers with opportunities to have intelligent storage and break the boundaries still being hung onto via traditional rotating media architectures.

Learning Objectives: 1) In-Storage Compute value; 2) How to deploy at scale; 3) The ease of implementation with existing architectures.

Cinder has long been a key component in OpenStack for providing block storage. It provides support for a broad variety of storage backends ranging from LVM, NFS shares, FC and iSCSI SANs, and more. Yet with all these options, Cinder provides one consistent API abstraction that can be used to manage those varied storage options.

But what many don’t realize is – Cinder can be used for much more than OpenStack.

Over the last several releases, there has been a focus on making Cinder a viable stand alone storage management interface. Today, Cinder can be used not just in OpenStack, but in container environments such as Kubernetes. It can be used as a scriptable interface for devops tooling and automation. And with clients and SDKs available for Python, Golang, Java, and more, it can provide a simple, programmatic way to build storage management into CI/CD pipelines and other custom workflows.

This session demonstrates how to leverage the capabilities of Cinder to meet many of your storage provisioning needs.

Learning Objectives: 1) Programmatic storage management; 2) Cloud block storage; 3) Storage management use cases.