Container Application deployments are growing exponentially, and so as the challenges with container data protection. Users are first worried to ensure the data backup for their deployments. Kubernetes provides data backup features through CSI. Is that sufficient? What are the new demands and challenges? What are the solutions to the challenges? How can we ensure container data backup beyond the CSI supported features? This session tries to answer these questions. Also, it discusses the current state of Kubernetes native data protection solutions.

This talk is going to give an overview of recent changes in the Samba fileserver and an outlook on the development roadmap. Recent development has been mainly focusing on security resulting in the release of Samba 4.15 last year. Looking forward there are many things the Samba fileserver development team has on its todo list and this presentation will give a first hand insight into the making of the next Samba versions.

The HDFS protocol supports POSIX.1e style ACLs. Supporting such ACLs in a multiprotocol environment means a translation method should be defined to translate between the NFSv3 mode bits, NFSv4 ACLs, Windows Style ACLs and the POSIX.1e ACLs. POSIX.1e ACLs differ in their structure and evaluation algorithm as compared to other ACLs that are currently supported in OneFS. The talk will detail the approach we took and also some of the surprising challenges related to multithreading.

In this presentation we will discuss why KV SSD is the ultimate storage solution, and why it will replace ZNS. We will explore how KV SSD solves many of the issues with flash management and the scaling of SSD devices in storage systems. KV SSD is a contrasting direction to Zone Namespaces and the migration of flash management to the Host. We feel KV SSD is a better direction, as the axiomatic optimal solution is to perform garbage collection at a single layer in any system, and that this garbage collection is optimal when it is as close to the flash as possible.

AI/ML is not new, but innovations in ML models development have made it possible to process data at unprecedented speeds. Data scientists have used standard POSIX file systems for years, but as the scale and need for performance have grown, many face new storage challenges. Samsung has been working with customers on new ways of approaching storage issues with object storage designed for use with AI/ML. Hear how software and hardware are evolving to allow unprecedented performance and scale of storage for Machine Learning.

About 80% of enterprises have experienced at least one firmware attack in the last two years* What is firmware resilience, how does it apply to SSDs to address these threats? - Not a new concept.

Durability and performance in an S3 alternative storage platform are complex problems, but not owning the hard drives brings another level of difficulty. At Storj, we have 13,500+ independent node operators putting their unutilized hard drive space to work by joining our decentralized network. Learn how Storj developed an architecture that could deliver the demands of an S3 workload and also ensure durability. Assuming any of the node operators could be malicious, required a focus on encryption.

In consumer and enterprise world, SSD Performance is the main quality constraint. SSD performance parameters are classified in terms of lOPS, Throughput, latency and Quality of service(QoS). SSDs processes millions bytes of data with certain latency and throughput for read, write and mixed operations. But Quality of service is not guaranteed by SSD vendors for single user. However, Enterprise/server SSD storage must meet a Quality of Service (QoS) level with the given requirement to ensure the study-state performance over long period of time.

Data center systems power consumption is currently one of the biggest concern and green computing is main industry interest. Recent research found that more than 60% power is consumed in CPU in a server. SNIA and NVMe computational storage standard compliant Samsung Smart SSD achieves high energy-efficient computing by offloading computation from CPU to SSD. DB SCAN acceleration engine in Smart SSD demonstrated that it can internally process data at the full speed and highly enhance energy efficiency.

Most programs have traditionally been divisible into either "in-memory" or "database" applications. When writing in-memory applications, all that matters for speed is the efficiency of the algorithms and data structures in the CPU/memory system during the run of the program, whereas with database applications the main determinant of speed is the number and pattern of accesses to storage (e.g., random accesses vs. sequential ones).