On Demand Webinars
The convergence of 5G, Edge Compute and Artificial Intelligence (AI) promise to be catalyst for Digital transformation within industrial segments. Advanced 5G is specifically designed to address the needs of verticals with capabilities like enhanced mobile broadband (emBB), ultra-reliable low latency communications (urLLC), and massive machine type communications (mMTC), to enable near real-time distributed intelligence applications. For example, automated guided vehicle and autonomous mobile robots (AGV/AMRs), wireless cameras, augmented reality for connected workers, and smart sensors across many verticals ranging from healthcare and immersive media, to factory automation.
Using this data, manufacturers are looking to maximize operational efficiency and process optimization by leveraging AI and machine learning. To do that, they need to understand and effectively manage the sources and trustworthiness of timely data.
This presentation will take a deep dive into how:
- Edge can be defined and current state of the industry
- Industrial Edge is being transformed
- 5G and Time-Sensitive Networking (TSN) play a foundational role in Industry 4.0
- The convergence of high-performance wireless connectivity and AI creates new data-intensive use cases
- The right data pipeline layer provides persistent, trustworthy storage from edge to cloud
Cloud to Edge infrastructures are rapidly growing. It is expected that by 2025, up to 75% of all data generated will be created at the edge. However, Edge is a tricky word and you’ll get a different definition depending on who you ask. The physical edge could be in a factory, retail store, hospital, car, plane, cell tower level, or on your mobile device. The network edge could be a top-of-rack switch, server running host-based networking, or 5G base station.
The Edge means putting servers, storage, and other devices outside the core data center and closer to both the data sources and the users of that data—both edge sources and edge users could be people or machines.
At our first webcast in this series, “Storage Life on the Edge: Managing Data from the Edge to the Cloud and Back” you‘ll learn:
- Data and compute pressure points: aggregation, near & far Edge
- Supporting IoT data
- Analytics and AI considerations
- Understanding data lifecycle to generate insights
- Governance, security & privacy overview
- Managing multiple Edge sites in a unified way
Ransomware is malware that encrypts valuable data and then asks the victim for ransom in lieu of providing the decryption keys. One way to not fall prey to Ransomware is to keep regular backups, and use them as last line of defence. Lately some of the ransomware attacks have started encrypting or destroying the backup images as well. They target predominately Windows as of now, though other systems are also targeted.
This webinar is about solutions built from the ground up to lockdown disk-based backup images. It goes beyond storage, and protects certain specific processes from code injection and masquerading to gain trust. Here we will discuss our experience of designing and developing this solution on Windows platform.
In this session we will:
- Explain ransomware behaviour around backup data with concrete examples
- Explain best practices when dealing with 3rd party products, anti-virus etc.
- Share experiences with customers involving real ransomware attacks
- Discuss future directions
As storing data in the cloud has become ubiquitous and mature, many organizations have adopted a multi-cloud strategy. Eliminating dependence on a single cloud platform is quite a compelling case.
But multi-cloud environments are not without challenges. Taking advantage of the benefits without increasing complexity requires a strategy that ensures applications are not tightly coupled to cloud-specific technologies. Supporting a storage abstraction layer that insulates the application from the underlying cloud provider's interfaces allows an application to be easily used with multiple clouds. Join to hear SNIA experts cover:
- Risk mitigation of multiple clouds
- Transparent movement of data from cloud to cloud
- Political, regulatory and compliance considerations
- Multi-cloud as part of a business continuity strategy
- Exit cost reduction
- Running work in parallel across clouds
The automotive industry is effectively transforming the vehicle into a data center on wheels. Connectedness, autonomous driving, and media & entertainment bring in more and more storage onboard and into the networked data centers. But all the storage in (and for) a car is not created equal. There are 10s if not 100s of different processors on the car. Some are attached to storage and some are not. Each application demands different characteristics from the storage device. Let’s explore all of this in an informational journey with the industry experts from both the storage and automotive worlds.
- What’s driving growth in automotive storage?
- Special requirements for autonomous vehicles
- Where automotive data is typically stored?
- Special use cases
- Vehicle networking & compute changes and challenges
Storing objects has become commonplace. Object storage provides bulk and undifferentiated storage for unstructured data like photos, video & audio, DNA sequences, files, backups, and it can even protect against ransomware. Object access is also simplified because there are no built-in hierarchies or filesystems of objects, and no devices to manage that look like disks.
So, what’s new? Object storage has traditionally been accomplished in the software stack and is now being accomplished directly on the media. In this presentation, we’ll highlight how this is happening and discuss:
- Object storage characteristics
- The differences and similarities between object and key value storage
- Security options unique to object storage including ransomware mitigation
- Why use object storage: Use cases and applications
- Object storage and containers: Why Kubernetes’ COSI (Container Object Storage Interface)?
NVMe® IP-based SANs (including TCP, RoCE, iWARP) have the potential to provide significant benefits in application environments ranging from the Edge to the Data Center. However, before we can fully unlock NVMe IP-based SAN’s potential, we first need to overcome the NVMe over Fabrics (NVMe-oF™) discovery problem. This discovery problem, specific to IP based fabrics, can result in the need for Host administrators to explicitly configure each Host to access each of the NVM subsystems in their environment. In addition, any time an NVM Subsystem interface is added or removed, the Host administrator may need to explicitly update the configuration of impacted hosts. This process does not scale when more than a few Host and NVM subsystem interfaces are in use. Also, due to the de-centralized nature of this process, it also adds complexity when trying to use NVMe IP-based SANs in environments that require a high-degrees of automation.
For these and other reasons, several companies have been collaborating on innovations that simplify and automate the discovery process used with NVMe IP-based SANs.
During this session we will explain:
- NVMe IP-based SAN discovery problem
- The types of network topologies that can support the automated discovery of NVMe-oF Discovery controllers
- Direct Discovery versus Centralized Discovery
- An overview of the discovery protocol
SNIA develops a wide range of standards to enhance the interoperability of various storage systems. With new technologies like computational storage, standards do not exist. As companies develop solutions, questions arise. Should computational storage have standards for recommended behavior for hardware and software? Should an application programming interface be defined?
At SNIA, over 250 volunteers answered yes, and new work is being defined both within SNIA and in collaboration with other industry standards bodies. Join leaders of the Computational Storage Technical Work Group as they discuss how they define and develop standards with input from many different companies and users, what they perceive as important today and moving forward, and how you can participate.
This talk will focus on the history of “Big Data” and how it has pushed the storage envelope, eventually resulting in a seemingly perfect relationship with Cloud Storage. But local storage is the 3rd wheel in this relationship, and won’t go down easy. Can this marriage survive when Big Data is being pulled in two directions? Should Big Data pick one, or can the three of them live happily ever after? This webcast will cover:
- The impact of edge computing
- The erosion of the data center
- Managing data-on-the-fly
- Grid management
- Next-gen Hadoop and related technologies
- Supporting AI workloads
- Data gravity and distributed data
Modern data centers systems consist of hundreds of sub-systems that are all connected with optical transceivers, copper cables, and industry standards-based connectors and cages. For interconnecting storage subsystems, two things are happening: Speeds are radically increasing making the maximum reach of copper wire interconnects very short and, at the same time, increasingly larger storage systems are expanding in size and much further apart. This is making longer reach optical technologies much more popular. However, optical interconnect technologies are more costly and complex compared to copper with a plethora of new buzz-words and technology concepts.
The rate of change from the huge uptick in data demand is accelerating new product developments at an incredible pace. While much of the enterprise industry is still on 10G/40G/100GbE speeds, the next generation optics groups are already commercializing 800G with 1.6Tb transceivers in discussion! Today, it’s all about power, cost, and upgrade paths.
In this SNIA Network Storage Forum webinar we’ll cover the latest in the impressive array of data center infrastructure solutions designed to address expanding requirements for higher-bandwidth and lower-power. This will include next-generation solutions leveraging copper and optics to deliver high signal integrity, lower-latency, and lower insertion loss to achieve maximum efficiency, speed, and density.