Everything You Wanted To Know about Storage But Were Too Proud To Ask: Buffering

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

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

In the FCIA webcast “Protocol Analysis for High-Speed Fibre Channel Fabrics” experts covered the basics on protocol analysis tools and how to incorporate them into the “best practices” application of SAN problem solving.
Our experts return for this 201 course which will provide a deeper dive into how to interpret the output and results from the protocol analyzers. We will also share insight into using signal jammers and how to use them to correlate error conditions to be able to formulate real time solutions.

Root cause analysis requirements now encompass all layers of the fabric architecture, and new storage protocols that usurp the traditional network stack (i.e. FCoE, iWARP, NVMe over Fabrics, etc.) complicate analysis, so a well-constructed “collage” of best practices and effective and efficient analysis tools must be developed. In addition, in-depth knowledge of how to decipher the analytical results and then determine potential solutions is critical.

Join us for a deeper dive into Protocol Analysis tools and how to interpret the analytical output from them. We will review:
•Inter switch links (ISL) – How to measure and minimize fabric congestion
•Post-capture analysis – Graphing, Trace reading, Performance metrics
•Benefits of purposeful error injection
•More Layer 2-3 and translation layers debug
•Link Services and Extended Link Services - LRR Link Ready Rests

You can watch the 1st webcast on this topic on-demand at http://bit.ly/2MxsWR7