Storage Performance Benchmarking: Part 2

Traditionally, much of the IT infrastructure that we’ve built over the years can be divided fairly simply into storage (the place we save our persistent data), network (how we get access to the storage and get at our data) and compute (memory and CPU that crunches on the data). In fact, so successful has this model been that a trip to any cloud services provider allows you to order (and be billed for) exactly these three components.

We build effective systems in a cost-optimal way by using appropriate quantities of expensive and fast memory (DRAM for instance) to cache our cheaper and slower storage. But currently fast memory has no persistence at all; it’s only storage that provides the application the guarantee that storing, modifying or deleting data does exactly that.

Memory and storage differ in other ways. For example, we load from memory to registers on the CPU, perform operations there, and then store the results back to memory by using byte addresses. This load/store technology is different from storage, where we tend to move data back and fore between memory and storage in large blocks, by using an API (application programming interface).

New memory technologies are challenging these assumptions. They look like storage in that they’re persistent, if a lot faster than traditional disks or even Flash based SSDs, but we address them in bytes, as we do memory like DRAM, if more slowly. These PMs (persistent memories) lie between storage and memory in latency, bandwidth and cost, while providing memory semantics and storage persistence. In this webcast, SNIA experts will discuss:

•Traditional uses of storage and memory as a cache
•How can we build and use systems based on PM?
•What would a system with storage, persistent memory and DRAM look like?
•Do we need a new programming model to take advantage of PM?
•Interesting use cases for systems equipped with PM
•How we might take better advantage of this new technology

Kubernetes (k8s) is an open-source system for automating the deployment, scaling, and management of containerized applications. Kubernetes promises simplified management of cloud workloads at scale, whether on-premises, hybrid, or in a public cloud infrastructure, allowing effortless movement of workloads from cloud to cloud. By some reckonings, it is being deployed at a rate several times faster than virtualization.

In this presentation, we’ll introduce Kubernetes and present use cases that make clear where and why you would want to use it in your IT environment. We’ll also focus on the enterprise requirements of orchestration and containerization, and specifically on the storage aspects and best practices.

•What is Kubernetes? Why would you want to use it?
•How does Kubernetes help in a multi-cloud/private cloud environment?
•How does Kubernetes orchestrate & manage storage? Can Kubernetes use Docker?
•How do we provide persistence and data protection?
•Example use cases

Has hybrid cloud reached a tipping point? According to research from the Enterprise Strategy Group (ESG), IT organizations today are struggling to strike the right balance between public cloud and their on-premises infrastructure. In this SNIA webcast, ESG senior analyst, Scott Sinclair, will share research on current cloud trends, covering:

•Key drivers behind IT complexity
•IT spending priorities
•Multi-cloud & hybrid cloud adoption drivers
•When businesses are moving workloads from the cloud back on-premises
•Top security and cost challenges
•Future cloud projections

The research will be followed by a panel discussion with Scott Sinclair and SNIA cloud experts Alex McDonald, Michelle Tidwell, Mike Jochimsen and Eric Lakin.

We’re all accustomed to transferring money from one bank account to another; a credit to the payer becomes a debit to the payee. But that model uses a specific set of sophisticated techniques to accomplish what appears to be a simple transaction. We’re also aware of how today we can order goods online, or reserve an airline seat over the Internet. Or even simpler, we can update a photograph on Facebook. Can these applications use the same models, or are new techniques required?

One of the more important concepts in storage is the notion of transactions, which are used in databases, financials, and other mission critical workloads. However, in the age of cloud and distributed systems, we need to update our thinking about what constitutes a transaction. We need to understand how new theories and techniques allow us to undertake transactional work in the face of unreliable and physically dispersed systems. It’s a topic full of interesting concepts (and lots of acronyms!). In this webcast, we’ll provide a brief tour of traditional transactional systems and their use of storage, we’ll explain new application techniques and transaction models, and we’ll discuss what storage systems need to look like to support these new advances.

And yes, we’ll explain all the acronyms and nomenclature too.

You will learn:

• A brief history of transactional systems from banking to Facebook
• How the Internet and distributed systems have changed and how we view transactions
• An explanation of the terminology, from ACID to CAP and beyond
• How applications, networks & particularly storage have changed to meet these demands