There is a new architectural approach to accelerating storage-intensive databases and applications which take advantage of new techniques that dramatically accelerate database performance, improve response times and reduce infrastructure cost at massive scale. This new architecture efficiently stores fundamental data structures increasing space savings—up to 80%—over host- and software-based techniques that cannot address inherent inefficiencies in today’s fastest SSD technology.

Real Time Analytics and Data intensive applications have driven the adoption of high performance, low latency, highly parallel NVMe solutions and now we are in the cusp of wide adoption of NVMe over Fabrics (NVMe-oF) Storage in both On-Prem and Cloud Data Centers. Since the introduction of NVMe-oF, a lot of investment and effort have gone in to improve the overall storage performance and features resulting in substantial improvement of IOPs and CPU utilization and lowering the TCO for the customer.

Currently Stateful Applications contribute to the major chunk (more than 50%) of containerized application deployment for enterprise. To maintain an uninterrupted application availability for the containerized applications, backup and recover these application to be DR ready is the need and important strategy of the enterprises. One important aspect is to backup and recover in an alternative environment. With alternative environment we mean, in an hybrid environment, i.e. take an example of Cloud1 managed K8S environment being recovered into Cloud2 managed K8S environment.

Many businesses like ours are challenged with on-demand infrastructure provisioning at the speed of software while the datacenter footprint is diminishing. Pure Storage as a company is getting out of the datacenter center business and are adopting more of a OpEx cost model with strict legal and data compliance guidelines for many of our business application pipelines. We chose to go with a programmable Infrastructure and Connected Cloud architecture with open APIs.

CPU performance improvements based on Dennard scaling and Moore's Law have already reached their limits, and domain-specific computing has been considered as an alternative to overcome the limitations of traditional CPU-centric computing models. Domain-specific computing, seen in early graphics cards and network cards, has expanded into the field of accelerators such as GPGPUs, TPUs, and FPGAs as machine learning and blockchain technologies become more common.

Malware, short for malicious software, is a blanket term for viruses, worms, trojans and other harmful software that attackers use to damage, destroy, and gain access to sensitive information; software is identified as malware based on its intended use, rather than a particular technique or technology used to build it. Ransomware is a blended malware attack that uses a variety of methods to target the victim’s data and then requires the victim to pay a ransom (usually in crypto currency) to the attacker to regain access to the data upon payment (with no guarantees).

Most of the top storage vendors are moving to storage as a service solution. Exploring all the ecosystem components including open source solutions to build a complete data management solution on top of the existing storage capabilities. The intensity of this move is accelerated as more cloud-native and hybrid use cases are in demand. In this session, we will see an overall architecture for a typical stack with key data management including data protection and monitoring across existing storage infrastructure. We will also see how this trend is shaping container and cloud-native storage.

DNA Sequencing using Sequencing-by-synthesis (SBS) technology is today responsible for the majority of sequencing done worldwide. This presentation will cover the fundamentals behind SBS, the steps involved in going from a DNA sample to data, and the current state of art of sequencing platforms. The presentation will end by discussing how DNA sequencing can be applied to DNA-based data storage.

Data is growing at an exponential pace and the need to manage this data at the core and edge is a multi-facet problem. New innovative methods to ensure data availability & utilization of the resources that store this data are being developed. Storage device health monitoring & utilization is one such issue. Developing models to predict drive degradation while using machine learning principles is highly desirable. A recent Google blog described the machine learning techniques being used to promote & improve drive maintenance of their fleet.

As NVMe-oF specifications continue to develop in NVM Express, so are the corresponding Swordfish management capabilities. This presentation provides an update on the latest NVMe-oF configuration and provisioning capabilities available through Swordfish.