How to Train Deep Learning Models in the Cloud

Industry analysts predict Deep Learning will account for the majority of cloud workloads. Additionally, training of Deep Learning models will represent the majority of server applications in the next few years. Among Deep Learning workloads, foundation models — a new class of AI models that are trained on broad data (typically via self-supervision) using billions of parameters – are expected to consume the majority of the infrastructure.

It’s a fascinating topic that the SNIA Cloud Storage Technologies Initiative (CSTI) will tackle on March 15, 2023 at our live webcast “Training Deep Learning Models in the Cloud” where our SNIA Deep Learning experts, Milind Pandit, from Habana, an Intel Company and Seelam Seetharami of IBM, will discuss how Deep Learning models are gaining prominence in various industries, and provide examples of the benefits of AI adoption.

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Kubernetes Trials & Tribulations Q&A: Cloud, Data Center, Edge

Kubernetes cloud orchestration platforms offer all the flexibility, elasticity, and ease of use — on premises, in a private or public cloud, even at the edge. The flexibility of turning on services when you want them, turning them off when you don’t, is an enticing prospect for developers as well as application deployment teams, but it has not been without its challenges.

At our recent SNIA Cloud Storage Technologies Initiative webcast “Kubernetes Trials & Tribulations: Cloud, Data Center, Edge” our experts, Michael St-Jean and Pete Brey, debated both the challenges and advantages of Kubernetes. If you missed the session, it is available on-demand along with the presentation slides. The live audience raised several interesting questions. Here are answers to them from our presenters.

Q. Are all these trends coming together? Where will Kubernetes be in the next 1-3 years?

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What are Digital Twins?

Have you ever wondered how intelligent Industry 4.0 factories or smart cities of the future will process massive amounts of sensor and machine data? What you may not expect is a digital twin will most likely play a role. A digital twin is a virtual representation of an object, system or process that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making. Digital twins can be used to help answer what-if AI-analytics questions, yield insights on business objectives and make recommendations on how to control or improve outcomes.

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Kubernetes at the Cloud, Data Center and Edge

The race to the cloud has been fast and furious. The ease and flexibility of turning on services when you want them, turning them off when you don’t, is an enticing prospect for developers as well as application deployment teams, but it has not been without its challenges. Many cite expanding costs, data sovereignty, or security as reasons for repatriation of workloads, but what about other factors, such as data gravity, latency, and extending workloads to the edge? Addressing these challenges will be front and center at our SNIA Cloud Storage Technologies Initiative (CSTI) webcast on November 10, 2022, “Kubernetes Trials & Tribulations: Cloud, Data Center, Edge.”

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Kubernetes is Evolving, Are You?

Wide-spread adoption of Kubernetes over the last several years has been remarkable and Kubernetes is now recognized as the most popular orchestration tool for containerized workloads. As applications and workflows in Kubernetes continue to evolve, so must the platform and storage.  

So, where are we today, and where are we going? Find out on October 11, 2022 in this webcast “15 Minutes in the Cloud: Kubernetes is Evolving, Are You?,” where we’ll discuss:

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Kubernetes is Everywhere Q&A

Last month, the SNIA Cloud Storage Technologies Initiative hosted a fascinating panel discussion “Kubernetes is Everywhere: What About Cloud Native Storage?”  where storage experts from SNIA and Kubernetes experts from the Cloud Native Computing Foundation (CNCF) discussed storage implications for Kubernetes. It was a lively and enlightening discussion on key considerations for container storage. In this Q&A blog, our panelists Nick Connolly, Michael St-Jean, Pete Brey and I elaborate on some of the most intriguing questions during the session.

Q. What are the additional/different challenges for Kubernetes storage at the edge – in contrast to the data center?  

A. Edge means different things depending on context. It could mean enterprise or provider edge locations, which are typically characterized by smaller, compact deployments of Kubernetes. It could mean Kubernetes deployed on a single node at a site with little or no IT support, or even disconnected from the internet, on ships, oil rigs, or even in space for example. It can also mean device edge, like MicroShift running on a small form factor computer or within an ARM or FPGA card for example.

One big challenge for Kubernetes at the edge in general is to provide a lightweight deployment. Added components, like container-native storage, are required for many edge applications, but they take up resources. Therefore, the biggest challenge is to deploy the storage resources that are necessary for the workload, but at the same time, making sure your footprint is appropriate for the deployment infrastructure.  

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Kubernetes is Everywhere – What About Cloud Native Storage?

Organizations are adopting containers at an increasingly rapid rate. In fact, there are few organizations that haven’t implemented containers in their environment today. DevOps teams expect a flexible, seamless development, deployment and orchestration experience. With platform agnostic capabilities and a stateless container design, Kubernetes streamlines these processes – and now, with the contribution of persistent, cloud native storage, stateful information becomes reality along with advanced storage capabilities including features such as snapshots, rollbacks, etc.

On July 19, 2022, storage implications for Kubernetes will be the topic of our SNIA Cloud Storage Technologies Initiative (CSTI) live webcast “Kubernetes is Everywhere – What About Cloud Native Storage?” where storage experts from SNIA and Kubernetes experts from the Cloud Native Computing Foundation (CNCF) will discuss:

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5G, Edge, and Industry 4.0 Q&A

The confluence of 5G networks, AI and machine learning, industrial IoT, and edge computing are driving the fourth industrial revolution – Industry 4.0. The impact of the industrial edge and how it is being transformed were among the topics at our SNIA Cloud Storage Technologies Initiative (CSTI) webcast “5G Industrial Private Network and Edge Data Pipelines.” If you missed it, you can view it on-demand along with the presentation slides in the SNIA Educational Library. In this blog, we are sharing and clarifying answers to some of the intriguing questions from the live event.

Q. What are some of the key challenges to support the agility and flexibility requirements of Industry 4.0?

A. The fourth industrial revolution aka Industry 4.0 aspires to fundamentally transform the flexibility, versatility and productivity of future smart factories. Key attributes of this vision include complex workloads to enable remote autonomous operation, which involves autonomous mobile robots and machines, augmented reality aided connected workers, wireless sensors, actuators and remote supervisory control systems, as shown in the diagram below. Machines in smart factories will no longer be stationary. To enable quick response to supply demand changes and enable mass customization (“batch size of one”), factory lines need to be quickly reconfigurable and need machines to move within a certain range. These AI-based, mobile autonomous robots and machines require high data through-put wireless networks and highly reliable sub-second latency for machine-to-machine control communications.

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Understanding How Data Privacy, Data Governance, and Data Security Differ

Ever wonder what’s the difference between data privacy, data governance and data security? All of these terms are frequently (and mistakenly) used interchangeably. They are indeed related, particularly when it comes to keeping data in the cloud protected, private and secure, but the definitions and mechanics of executing on each are all quite different.

Join us on March 30, 2022 for another SNIA Cloud Storage Technologies Initiative (CSTI) “15 Minutes in the Cloud” session for an overview of what each of these terms means, how and where they intersect, and why each one demands adequate attention or you risk threatening the overall security of your data.

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Scaling Storage to New Heights

Earlier this month, the SNIA Cloud Storage Technologies Initiative (CSTI) presented a live webcast called “High Performance Storage at Exascale” where our HPC experts, Glyn Bowden, Torben Kling Petersen and Michael Hennecke talked about processing and storing data in shockingly huge numbers. The session raises some interesting points on how scale is quickly being redefined and what was cost compute prohibitive a few years ago for most, may be in reach for all sooner than expected.

Q. Is HPC a rich man’s game? The scale appears to have increased dramatically over the last few years. Is the cost increasing to the point where this is only for wealthy organizations or has the cost decreased to the point where small to medium-sized enterprises might be able to indulge in HPC activities?

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