On Demand Webinars
Everyone enjoys having storage that is fast, reliable, scalable, and affordable. But it turns out different applications have different storage needs in terms of I/O requirements, capacity, data sharing, and security. Some need local storage, some need a centralized storage array, and others need distributed storage—which itself could be local or networked. One application might excel with block storage while another with file or object storage. With limited resources, it’s important to understand the storage intent of the applications in order to choose the right storage and storage networking strategy, rather than discovering the hard way that you’ve chosen the wrong solution for your application.
Artificial intelligence (AI) is a technology which itself encompasses a broad range of use cases, largely divided into training and inference. In this webcast, we’ll look at what types of storage are typically needed for different aspects of AI, including different types of access (local vs. networked, block vs. file vs. object) and different performance requirements. And we will discuss how different AI implementations balance the use of on-premises vs. cloud storage. Tune in to this SNIA Networking Storage Forum (NSF) webcast to boost your natural (not artificial) intelligence about application-specific storage.
Each SAN transport has its own way to initialize and transfer data. So how do initiators (hosts) and targets (storage arrays) communicate in Fibre Channel (FC) Storage Area Networks (SANs)?
Find out in this live webcast where Fibre Channel experts will answer:
- How do FC links activate?
- Is FC routable?
- What kind of flow control is present in FC?
- How do initiators find targets and set up their communication?
- Finally, how does actual data get transferred since that is the ultimate goal?
This session will introduce these concepts to demystify the FC SAN for the network professional.
The use of genomics in modern biology has revolutionized the speed of innovation for the discovery of medicines. The COVID pandemic response has quickened genetic research and driven the rapid development of vaccines. Genomics, however, requires a significant amount of compute and data storage to aid discovery. This session is for IT professionals who are faced with delivering and supporting IT solutions for the required compute and data storage for genomics workflows. It will feature viewpoints from both the bioinformatics and technology perspectives with a focus on some of these compute and data storage challenges.
We will discuss:
- How to best store and manage these large genomics datasets
- Methods for sharing these large datasets for collaborative analysis.
- Legal and ethical implications of storing shareable data in the cloud
- Transferring large data sets and the impact on storage and networking
Data gravity has pulled computing to the Edge and enabled significant advances in hybrid cloud deployments. The ability to run analytics from the datacenter to the Edge, where the data is created and lives, also creates new use cases for nearly every industry and company. However, this movement of compute to the Edge is not the only pattern to have emerged. How might these other use cases impact your storage strategy?
This interactive webcast by the SNIA CSTI will focus on the following topics:
- Emerging patterns of data movement and the use cases that drive them
- Cloud Bursting
- Federated Learning across the Edge and Hybrid Cloud
- Considerations for distributed cloud storage architectures to match these emerging patterns
To counter the ever-increasing likelihood of catastrophic disruption and cost due to enterprise IT security threats, data center decision makers need to be vigilant in protecting their organization’s data. Confidential Computing is architected to provide security for data in use to meet this critical need for enterprises today.
This webcast provides insight into how data center, cloud and edge applications may easily benefit from cost-effective, real-world Confidential Computing solutions. This educational discussion will provide end-user examples, tips on how to assess systems before and after deployment, as well as key steps to complete along the journey to mitigate threat exposure. Presenting are Steve Van Lare (Anjuna), Anand Kashyap (Fortanix), and Michael Hoard (Intel), who will discuss:
- What would it take to build-your-own Confidential Computing solution?
- Emergence of easily deployable, cost-effective Confidential Computing solutions
- Real world usage examples and key technical, business and investment insights
Thanks to big data, artificial intelligence (AI), the Internet of things (IoT), and 5G, demand for data storage continues to grow significantly. The rapid growth is causing storage and database-specific processing challenges within current storage architectures. New architectures, designed with millisecond latency, and high throughput, offer in-network and storage computational processing to offload and accelerate data-intensive workloads.
Join technology innovators as they highlight how to drive value and accelerate SSD storage through the specialized implementation of key value technology to remove inefficiencies through a Data Processing Unit for hardware acceleration of the storage stacks, and a hardware-enabled Storage Data Processor to accelerate compute-intensive functions. By joining, you will learn why SSDs are a staple in modern storage architectures. These disaggregated systems use just a fraction of computational load and power while unlocking the full potential of networked flash storage.
As noted in our panel discussion “What is Confidential Computing and Why Should I Care?,” Confidential Computing is an emerging industry initiative focused on helping to secure data in use. The efforts can enable encrypted data to be processed in memory while lowering the risk of exposing it to the rest of the system, thereby reducing the potential for sensitive data to be exposed while providing a higher degree of control and transparency for users.
As computing moves to span multiple environments from on-premises to public cloud to edge, organizations need protection controls that help safeguard sensitive IP and workload data wherever the data resides. In this live webcast we’ll cover:
- How Confidential Computing works in multi-tenant cloud environments
- How sensitive data can be isolated from other privileged portions of the stack
- Applications in financial services, healthcare industries, and broader enterprise applications
- Contributing to the Confidential Computing Consortium
In our second installment of our Storage Technologies & Practices Ripe for Refresh, we will cover older HDD device interfaces and file systems. Advice will be given on how to replace these in production environments as well as why these changes are recommended. Also, we will be covering protocols that you should consider removing from your networks, either older versions of protocols where only newer versions should be used, or protocols that have been supplanted by superior options and should be discontinued entirely.
Finally, we will look at physical networking interfaces and cabling that are popular today but face an uncertain future as networking speeds grow ever faster.
In the "arms race" of security, new defensive tactics are always needed. One significant approach is Confidential Computing: a technology that can isolate data and execution in a secure space on a system, which takes the concept of security to new levels. This SNIA Cloud Storage Technologies Initiative (CSTI) webcast will provide an introduction and explanation of Confidential Computing and will feature a panel of industry architects responsible for defining Confidential Compute. It will be a lively conversation on topics including:
- The basics of hardware-based Trusted Execution Environments (TEEs) and how they work to enable confidential computing
- How to architect solutions based around TEEs
- How this foundation fits with other security technologies
- Adjacencies to storage technologies
In modern analytics deployments, latency is the fatal flaw that limits the efficacy of the overall system. Solutions move at the speed of decision, and microseconds could mean the difference between success and failure against competitive offerings. Artificial Intelligence, Machine Learning, and In-Memory Analytics solutions have significantly reduced latency, but the sheer volume of data and its potential broad distribution across the globe prevents a single analytics node from efficiently harvesting and processing data.This panel discussion will feature industry experts discussing the different approaches to distributed analytics in the network and storage nodes. How does the storage providers of HDDs and SSD view the data creation and movement between the edge compute and the cloud? And how can computational storage be a solution to reduce data movement?