Data Protection and OpenStack Mitaka

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.

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

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 .

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

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

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

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.