Moving Data Protection to the Cloud: Trends, Challenges and Strategies

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.

Organizations inevitably store multiple copies of the same data. Users and applications store the same files over and over, intentionally or inadvertently. Developers, testers and analysts keep many similar copies of the same data. And backup programs copy the same or similar files daily, often to multiple locations or storage devices. It’s not unusual to end up with some data replicated thousands of times.

So how do we stop the duplication madness? Join this webcast where we’ll discuss how to reduce the number of copies of data that get stored, mirrored, or backed up as we discuss:

•Should I eliminate duplicates at the desktop, server, storage or backup device?
•Dedupe technology
•Local vs. global deduplication
•Avoiding or reducing data copies (non-dupe)
•Block-level vs. file- or object-level deduplication
•In-line vs. post-process deduplication
•More efficient backup techniques

Register today (but only once please) for this webcast so you can start saving space and end the extra data replication.

Whether traveling by car, plane or train, it is critical to get from here to there safely and securely. Just like you, your data must be safe and sound as it makes its journey across an internal network or to an external cloud storage device. It's well known that data is often considered less secure while in motion, and attackers are finding increasingly innovative ways to compromise data in flight. And the risks associated with data in transit are dependent on the security measures that are in place. So how do you adequately protect data in transit?

In this webcast, we'll cover what the threats are to your data as it's transmitted, how attackers can interfere with data along its journey, and methods of putting effective protection measures in place for data in transit. Included in this webinar will be:

•What you should expect to happen to secure data in transit; what are the trade-offs
•What transport layer security protocols (SSL, TLS, etc.) are best for protecting data in transit?
•Different encryption technologies and their role in protecting data in transit
•Which criteria should be used?
•How do you know which encryption to use?
•What’s applicable to different workloads?
•Best practices for data protection in transit

Join us on a journey to provide safe passage for your data by registering today!

The broad adoption of 5G, Internet of things (IoT) and edge computing will reshape the nature and role of enterprise and cloud storage over the next several years. What building blocks, capabilities and integration methods are needed to make this happen?

Join this webcast for a discussion on:

●With 5G, IoT and edge computing - how much data are we talking about?
●What will be the first applications leading to collaborative data-intelligence streaming?
●How can low latency microservices and AI quickly extract insights from large amounts of data?
●What are the emerging requirements for scalable stream storage - from peta to zeta?
●How are yesterday’s object-based batch analytic processing (Hadoop) and today’s streaming messaging capabilities (Apache Kafka and RabbitMQ) work together?
●What are the best approaches for getting data from the Edge to the Cloud?

After you watch the webcast, check out the Q&A blog: https://bit.ly/37pCC7X

Electronic payments, once the purview of a few companies, have expanded to include a variety of financial and technology companies. Internet of Payment (IoP) enables payment processing over many kinds of IoT devices and has also led to the emergence of the micro-transaction. The growth of independent payment services offering e-commerce solutions, such as Square, and the entry of new ways to pay, such as Apple Pay mean that a variety of devices and technologies also have come into wide use.

Along with the rise and dispersal of the payment eco-system, more of our assets that we exchange for payment are becoming digitized as well. When digital ownership is equivalent to physical ownership, security and scrutiny of those digital platforms and methods takes a leap forward in significance.

Assets and funds are now widely distributed across multiple organizations. Physical asset ownership is even being shared between many stakeholders resulting in more ownership opportunities for less investment but in a distributed way.

In this talk we look at the impact of all of these new principles across multiple use cases and how it impacts not only on the consumers driving this behavior but on the underlying infrastructure that supports and enables it. We will look particularly at:

•The cloud network, applications and storage implications of Internet of Payments
•Use of emerging blockchain capabilities for payment histories and smart contracts
•Identity and security challenges at the device in addition to point of payment
•Considerations on architecting IoP solutions for future scale

The pandemic has taught data professionals one essential thing. Data is like water when it escapes; it reaches every aspect of the community it inhabits. This fact becomes apparent when the general public has access to statistics, assessments, analysis and even medical journals related to the pandemic, at a scale never seen before.
Insight understands information in context to the degree that you can gain an understanding beyond just the facts presented and instead make reasonable predictions and suppositions about new instances of that data.
Having access to data does not automatically grant the reader knowledge of how to interpret that data or the ability to derive insight. It is even challenging to judge the accuracy or value in that data.
The skill required is known as data literacy, and in this presentation, we will look at how access to one data source will inevitably drive the need to access more. We will examine:
•How data literacy is defined by the ability to interpret and apply context
•What supporting information is needed
•How a data scientist approaches new data sources and the questions they ask of it
•How to seek out supporting or challenging data to validate its accuracy and value for providing insight
•How this impacts underlying information systems and how data platforms need to adjust to this purpose+ data eco-system where data sources are no longer single use

After you watch the webcast, check out the Q&A blog: https://bit.ly/30AwN53

NVMe over Fabrics technology is gaining momentum and getting more tractions in data centers, but there are three kinds of Ethernet based NVMe over Fabrics transports: iWARP, RoCEv2 and TCP. How do we optimize NVMe over Fabrics performance with different Ethernet transports?

Setting aside the consideration of network infrastructure, scalability, security requirement and complete solution stack, this webcast will explore the performance of different Ethernet-based transport for NVMe over Fabrics at micro benchmark level. We will show three key performance indicators: IOPs, Throughput, and Latency with different workloads including: Sequential Read/Write, Random Read/Write, 70%Read/30%Write, with different data size. We will compare the result of three Ethernet based transports: iWARP, RoCEv2 and TCP.

Further, we will dig a little bit deeper to talk about the variables that will impact the performance of different Ethernet transports. There are a lot of variables that you can tune but these variables will impact the performance of each transport to different extents. We will cover the variables:
1.How many CPU cores are needed (I’m willing to give)?
2.Optane SSD or 3D NAND SSD?
3.How deep should the Q-Depth be?
4.Why do I need to care about MTU?

This discussion won’t tell you which transport is the best. Instead we unfold the performance of each transport and tell you what it would take for each transport to get the best performance, so that you can make the best choice for your transport for NVMe over Fabrics solutions.

After you watch the presentation, check out the Q&A blog: https://bit.ly/36A44AU

In this webcast, SNIA experts will discuss what composable infrastructure is, what prompted its development, solutions, enabling technologies, standards/products and how computational storage fits in.

RAID on CPU is an enterprise RAID solution specifically designed for NVMe-based solid state drives (SSDs). This innovative technology provides the ability to directly connect NVMe-based SSD’s to PCIe lanes and make RAID arrays using those SSD’s without the need for a RAID Host Bus Adapter (HBA). As a result, customers gain NVMe SSD performance and data availability without the need of a traditional RAID HBA.

This webcast will recall key concepts for NVMe SSDs and RAID levels and will take a deep dive into RAID on the CPU technology and the way it compares to traditional Software and Hardware RAID solutions. Learn more about this new technology and how it is implemented, and gain a clear insight into the advantages of RAID on the CPU.

Everyone knows data volumes are exploding faster than IT budgets. And customers are increasingly moving to flash storage, which is faster and easier to use than hard drives, but still more expensive. To cope with this conundrum and squeeze more efficiency from storage, storage vendors and customers can turn to data reduction techniques such as compression, deduplication, thin provisioning and snapshots. This webcast will specifically focus on data compression, which can be done at different times, at stages in the storage process, and using different techniques. We’ll discuss:

•Where compression can be done: at the client, on the network, on the storage controller, or within the storage devices
•What types of data should be compressed
•When to compress: real-time compression vs. post-process compression
•Different compression techniques
•How compression affects performance

Tune in to this compact and informative SNIA webcast, which packs in copious content .

After you watch the webcast, check out the Q&A blog: https://sniansfblog.org/data-compression-qa/

The storage industry has many applications that rely on storing data as objects. In fact, it’s the most popular way that unstructured data is accessed. At the drive level, however, the devil is in the details. Normally, storage devices store information as blocks, not objects. This means that there is some translation that goes on between the data as it is consumed (i.e., objects) and the data that is stored (i.e., blocks).

Naturally, being efficient means that there are performance boosts, and simplicity means that there are fewer things that can go wrong. Moving towards storing key value pairs that get away from the traditional block storage paradigm make it easier and simpler to access objects.

Both The NVM Express™ group and SNIA have done quite a bit of work in standardizing this approach:

•NVM Express™ has completed standardization of the Key Value Command Set
•SNIA has standardized a Key Value API
•Spoiler alert: these two work very well together!

What does this mean? And why should you care? That’s what this webinar is going to cover! This presentation will discuss the benefits of Key Value storage, present the major features of the NVMe-KV Command Set and how it interacts with the NVMe standards. It will also cover the SNIA KV-API and open source work that is available to take advantage of Key Value storage.

We’ll be going deep under the covers to discuss:
•How this approach is different than traditional block-based storage
•Why doing this makes sense for certain types of data (and, of course, why doing this may not make sense for certain types of data)
•How this simplifies the storage stack
•Who should care about this, why they should care about this, and whether or not you are in that group

After you watch the webcast, check out the Q&A blog at https://bit.ly/2JSFcez

Protection against cyber threats is recognized as a necessary component of an effective risk management approach, typically based on a well-known cybersecurity framework. A growing area to further mitigate risks and provide organizations with the high level of protection they need is cyber insurance. However, it’s not as simple as buying a pre-packaged policy.

This webcast will provide an overview of how cyber insurance fits in a risk management program. It will identify key terms and conditions that should be understood and carefully negotiated. Cyber insurance policies may not cover all types of losses, so it is critical to identify what risks and conditions are excluded from a cyber insurance policy before you buy.

Join this webcast to learn:
•General threat tactics, risk management approaches, cybersecurity frameworks
•How cyber insurance fits within an enterprise data security strategy
•Nuances of cyber insurance – exclusions, exemption, triggers, deductibles and payouts
•Challenges associated with data stored in the cloud

After you watch the webcast, check out the Q&A blog: https://bit.ly/36ijYzI

The almost overnight shift of resources toward remote work introduces the need for far more flexible, dynamic and seamless end-to-end applications, putting us on a path that requires autonomous capabilities using AIOps – Artificial Intelligence for IT Operations.

This webcast will provide an overview of concepts and strategies to accelerate the digitalization of critical enterprise IT resources, and help architects rethink what applications and underlying infrastructure are needed to support an agile, seamless end-to-end data centric environment.  This session will specifically address migration from monolithic to microservices, transition to Cloud Native services, and the platform requirements to help accelerate AIOps application delivery within our dynamic hybrid and multi-cloud world.   

Join this webcast to learn:

• Use cases and design patterns: Data Fabrics, Cloud Native and the move from Request Driven to Event Driven

•    Foundational technologies supporting observability: how to build a more consistent scalable framework for governance and orchestration

•    The nature of an AI data centric enterprise: data sourcing, ingestion, processing, and distribution

After you watch the webcast, check out the Q&A blog: sniacloud.com/aiops-qa/

Everyone knows data volumes are growing rapidly, far faster than IT budgets, which range from flat to minimal annual growth. One of the drivers of such rapid data growth is storing multiple copies of the same data. Developers copy data for testing and analysis. Users email and store multiple copies of the same files. Administrators typically back up the same data over and over, often with minimal to no changes.

To avoid a budget crisis and paying more than once to store the same data, storage vendors and customers want to use data reduction techniques such as deduplication, compression, thin provisioning and snapshots.

This webcast will specifically focus on the fundamentals of data reduction, which can be performed in different places and at different stages of the data lifecycle. Like most technologies, there are related means to do this, but with enough difference to cause confusion. For that reason, we’re going to be looking at:

•How companies end up with so many copies of the same data
•Difference between deduplication and compression – when should you use one vs. the other?
•Where to reduce data: application-level, networked storage, backups, and during data movement
•When to collapse the copies: real-time vs. post-process deduplication
•Performance considerations

Tune in to this efficient and educational SNIA webcast, which covers valuable concepts with minimal repetition or redundancy.

After you watch the presentation, check out the Q&A blog at: https://bit.ly/34m949E

The rapid growth in infrastructure to support the real time and continuous collection and sharing of data to make better business decisions has led to an age of unprecedented information access and storage. This proliferation of data sources and of high-density data storage has put volumes of data at one’s fingertips. While the collection of large amounts of data has increased knowledge and efficiencies for businesses, it has also made attacks upon that information—theft, modification, or holding it for ransom--more tempting and easier. Cryptography is often used to protect valuable data.

This webcast will present an overview of applied cryptography techniques for the most popular use cases. We will discuss ways of securing data, the factors and trade-offs that must be considered, as well as some of the general risks that need to be mitigated, including:

•Encryption techniques for authenticating users
•Encrypting data—either at rest or in motion
•Using hashes to authenticate/ Information coding and data transfer methodologies
•Cryptography for Blockchain

The Enterprise and Data Center SSD Form Factor (EDSFF) is designed natively for data center NVMe SSDs to improve thermal, power, performance, and capacity scaling. EDSFF has different variants for flexible and scalable performance, dense storage configurations, general purpose servers, and improved data center TCO. At the 2020 Open Compute Virtual Summit OEMs, cloud service providers, hyperscale data center, and SSD vendors showcased products and their vision for how this new family of SSD form factors solves real data challenges.

Join this SNIA Compute Memory and Storage Initiative webcast where expert panelists from companies that have been involved in EDSFF since the beginning discuss how they will use the EDSFF form factor. OEMs will discuss their goals for E3 and the new updated version of the E3 specification! (SFF-TA-1008) Hyperscale data center and cloud service providers will discuss how E1.S (SFF-TA-1006) helps solve performance scalability, serviceability, capacity, and thermal challenges for future NVMe SSDs and persistent memory in 1U servers.