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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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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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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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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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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Multiple clouds within an organization have become the norm. This strategy enables organizations to reduce risk and dependence on a single cloud platform. The SNIA Cloud Storage Technologies Initiative (CSTI) discussed this topic at length at our live webcast last month Why Use Multiple Clouds?
We polled our webcast attendees on their use of multiple clouds and here’s what we learned about the cloud platforms that comprise their multi-cloud environments:
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Everyone is familiar with the term “Cloud†but it’s still worth asking “What is Cloud?†It can be defined as “networked computing facilities providing remote data storage and processing services via the Internet.†And while that definition is simple (if a little wordy!), the real-world of cloud is complex, dynamic, and ever growing.
That’s why we’re hosting this series which will include brief 15-minute discussions on cloud and cloud related technologies:
At this first talk “What is Cloud?†on March 2, 2022, the SNIA Cloud Storage Technologies Initiative will present a brief history of “The Cloud.†If you are a cloud expert, these sessions might not be for you, but for everyone else, this series of short talks might clear up a lot of questions you may have. Join us for a discussion on:
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The convergence of 5G, Edge Compute and Artificial Intelligence (AI) promise to be catalyst for continued digital transformation. For many industries, it will be a game-changer in term of how business in conducted. On January 27, 202, the SNIA Cloud Storage Technologies Initiative (CSTI) will take on this topic at our live webcast “5G Industrial Private Networks and Edge Data Pipelines.â€
Advanced 5G is specifically designed to address the needs of verticals with capabilities like enhanced mobile broadband (emBB), ultra-reliable low latency communications (urLLC), and massive machine type communications (mMTC), to enable near real-time distributed intelligence applications. For example, automated guided vehicle and autonomous mobile robots (AGV/AMRs), wireless cameras, augmented reality for connected workers, and smart sensors across many verticals ranging from healthcare and immersive media, to factory automation.
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As storing data in the cloud has become ubiquitous and mature, many organizations have adopted a multi-cloud strategy. Eliminating dependence on a single cloud platform is quite a compelling case with benefits of increased reliability, availability, performance, and the avoidance of vendor lock-in and/or specific vendor vulnerabilities to name a few. In short, spanning multiple clouds ensures a business does not have all its eggs (i.e. data) in one basket. Access your email, calendars & files via cloud services like google workspace set up migration – from anywhere and from any device.
But multi-cloud environments are not without challenges. Taking advantage of the benefits without increasing complexity requires a strategy that ensures applications are not tightly coupled to cloud-specific technologies. Supporting a storage abstraction layer that insulates the application from the underlying cloud provider’s interfaces allows an application to be easily used with multiple clouds. It allows storage features specific to a cloud to be exposed in a standardized manner and enables data to be transparently accessed and migrated as needed in order to take advantage of cloud-specific features without the application being aware of the underlying mechanics, thus reducing or eliminating the limits and vulnerabilities of any one cloud.
For a scalable, fine-grained access control for hybrid- and multi-cloud, you may check out this site https://privacera.com/products/centralized-access-control/.
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The ability to run analytics from the data center to the Edge, where the data is generated and lives creates new use cases for nearly every business. The impact of Edge computing on storage strategy was the topic at our recent SNIA Cloud Storage Technologies Initiative (CSTI) webcast, “Extending Storage to the Edge – How It Should Affect Your Storage Strategy.†If you missed the live event, it’s available on-demand. Our experts, Erin Farr, Senior Technical Staff Member, IBM Storage CTO Innovation Team and Vincent Hsu, IBM Fellow, VP & CTO for Storage received several interesting questions during the live event. As promised, here are answers to them all.
Q. What is the core principle of Edge computing technology?
A. Edge computing is an industry trend rather than a standardized architecture, though there are organizations like LF EDGE with the objective of establishing an open, interoperable framework. Edge computing is generally about moving the workloads closer to where the data is generated and creating new innovative workloads due to that proximity. Common principles often include the ability to manage Edge devices at scale, using open technologies to create portable solutions, and of ultimately doing all of this with enterprise levels of security. Reference architectures exist for guidance, though implementations can vary greatly by industry vertical.
Q. We all know connectivity is not guaranteed – how does that affect these different use cases? What are the HA implications?
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