6 Software-Defined Storage Companies to Watch

While the traditional storage industry has been largely experiencing anemic growth, at a 2.7 percent compound annual growth rate (CAGR) through 2021, there are pockets of the market that are seeing high growth and revenue. One such pocket is software-defined storage ( #SDS ). This segment is growing at a 13.5 percent CAGR through 2021, according to IDC. SDS is penetrating IT infrastructures to meet the needs of the next-generation datacenter. As companies transform their businesses and move operations to the cloud, they are adopting SDS for greater agility, reduced costs, and greater operational efficiency.

IDC defines SDS using the following criteria, “storage software that runs on commodity hardware, does not require any proprietary hardware components like custom ASICs [application-specific integrated circuit chips], and is a standalone storage system.”

Companies are abandoning traditional hardware-defined storage designs for software-defined storage models. “The legacy systems have improved their software to make them easier to use, borrowing some of the ideas of SDS,” said Eric Burgener, IDC research vice president of enterprise storage. “But they will generally always be more complex to manage, and certainly more expensive to buy and maintain.”

SDS is a subset of the larger storage market, and it can be split into four segments: block, file, object, and hyperconverged infrastructure (HCI), according to IDC. It’s worth noting that Gartner segments this differently into two categories: infrastructure (which would include block, file, object, and hyperconverged) and management (which coordinates the delivery of storage services).

VMware was one of the first companies to support this newer storage model with its software-defined data center and vSAN technology. But as the SDS market continues to grow, there are more companies coming forward with SDS innovations. We’ve identified six SDS companies that we believe are worth watching as this market continues to experience growth.

Cloudian

Cloudian set out to bring object storage to the enterprise. The company launched in 2011 with its flagship product, HyperStorage, a hybrid cloud storage platform.

It has recently updated the platform to include on-premises data centers and multiple public clouds, and it acquired SDS file storage company Infinity Storage. The founder of Infinity invented the write-once-read-many (WORM) file system that most SDS platforms use, including Cloudian. Prior to the acquisition, the two companies launched HyperFile, which used Infinity’s file storage software built into Cloudian’s storage platform.

The platform is widely seen as a way to consolidate data storage into a managed environment, while maintaining cloud-like object storage without obstructing the data.

Founders: Hiroshi Ohta and Michael Tso
Total Funding: $104.1 million (Digital Alpha Advisors, Lenovo, Epsilon Venture Partners, Intel Capital, DVP Investment, Innovation Network Corporation of Japan, City National Bank, Eight Roads Ventures, Goldman Sachs)

Cohesity

Cohesity was started in 2013 by Mohit Aron who previously co-founded Nutanix. The hyperconverged secondary storage company has been growing rapidly, and it saw a 600 percent increase in sales revenue over the previous year in 2017.

The company’s data storage platform, Orion, seeks to eliminate secondary storage silos by consolidating an enterprises on-premises and cloud-based secondary storage silos onto a centralized, hyperconverged platform.

Last year, Cohesity updated the platform to combine data protection and scalable file and object storage. The update enabled enterprises to also use Orion as a backup system and a searchable archive for large amounts of structured and unstructured data.

Founder: Mohit Aron
Total Funding: $160 million (Battery Ventures, Foundation Capital, Hewlett Packard Ventures, Accel Partners, Artis Ventures, GV, Cisco Investments, Qualcomm Ventures, Sequoia Capital, Wing Venture Capital, DHVC, Trinity Ventures, InstantScale Capital)

Datrium

Datrium was founded in 2012 by Data Domain and VMware veterans to create a slightly different model for storage than HCI infrastructure players. It provides open converged infrastructure for hybrid clouds in a way that doesn’t require the overhead of HCI. It does, however, integrate some features of HCI such as scale-out backup, cloud-based disaster recovery, and the ability to scale automatically to overcome bottleneck problems.

When Datrium launched, up until last year, it only had support for VMware servers and virtual machines (VMs), but it added storage support for open source platforms and Linux containers and Docker persistent volumes. This update enables enterprises to manage multiple environments from a single source. The company also enhanced its private cloud infrastructure platform with new scaling functions.

Founders: Boris Weissman, Brian Biles, Ganesh Venkitachalam, Hugo Patterson, and Sazzala Reddy
Total Funding: $110 million (New Enterprise Associates, Lightspeed Ventures)

Portworx

Portworx is a growing container storage company, which is packaged as a container itself. The company, founded in 2014, seeks to provide container-native storage and enable container use for DevOps and production environments.

Its cloud native data management platform provides automated data services, including data persistence and security, and it saves and stores container data. It can run on any infrastructure using a container, including Kubernetes, Mesosphere DC/OS, and Docker Swarm.

Portworx recently launched an open source stateful storage project, STORK, a storage orchestrator runtime for Kubernetes. The project allows DevOps teams to run stateful applications on Kubernetes and offer storage health monitoring.

Mesosphere recently became a reseller of Portworx’s products, combining Mesosphere’s automated compute service with Portworx’ automated storage platform.

Founders: Goutham Rao, Murli Thirumale, and Vinod Jayaraman
Total Funding: $28.5 million (Mayfield Fund, Sapphire Ventures, GE Ventures, Michael Dell)

Rubrik

Rubrik provides automated data backup, recovery, search, cloud, and development services across cloud and on-premises environments. The company launchedthe ninth release of its data management platform, Alta, in June 2017 with additional support for a number of physical and virtual environments.

In February, Rubrik acquired NoSQL data backup company, Datos IO. This acquisition is meant to help its enterprise customers undertake digital transformations and AI initiatives. In April, the company released a software-as-a-service platform, Polaris, for data management applications.

While Rubrik and Cohesity are competitors in this market, Rubrik disagrees on the use of the term “hyperconverged secondary storage,” deeming it a marketing term and preferring “cloud data management.”

Like Cohesity, it has seen enormous growth in the past few years as the market explodes. Rubrik was named as an alternative acquisition target for VMware by a VMware investor.

Founders: Arvind Jain, Arvind Nithrakashyap, Bipul Sinha, and Soham Mazumdar
Total Funding: $292 million (Kevin Durant, Greylock Partners, IVP, Lightspeed Ventures, Khosla Ventures)

SoftNas

SoftNas launched its first product, Cloud NAS, in 2013. Its goal was to fill a gap in terms of cloud native services by giving a native storage experience in a cloud environment, according to Arun Chandrasekaran, VP and distinguished analyst for Data Center and Cloud Infrastructure at Gartner.

Last year, the company released a new version of Cloud NAS and three additional products as it rebranded itself as a hybrid cloud platform provider.

CloudNAS works as an alternative to hardware-based storage, on-premises network attached storage (NAS), storage area networks (SAN), and file servers. It replaces these with cloud object storage, which can be more easily scaled to accommodate enterprise needs.

The three products it launched as part of its makeover are set to make it faster and easier to migrate applications to the cloud while providing backup and recovery.

Founders: Rick Braddy and William Hood
Total Funding: $6.4 million (angel investors)

https://www.sdxcentral.com/articles/news/6-software-defined-storage-companies-to-watch/2018/04/

Cumulus Networks Bolsters Cumulus NetQ with Kubernetes Integration to Provide Network Operators with Actionable Insight into Container Networking

MOUNTAIN VIEW, Calif.--(BUSINESS WIRE)--@Cumulus Networks, the leaders in building web-scale networks for the digital era with open and modern solutions, today announced @Kubernetes support with Cumulus #NetQ, a network operations tool that provides visibility and intelligence into the health of the entire network. The support for Kubernetes builds on existing integration with @Docker Swarm to enhance visibility, streamline troubleshooting, and help network operators avoid costly downtime in container environments. The company also introduced a new global leader of engineering, @Partho Mishra, and the appointment of @Shrijeet Mukherjee as Chief Architect. Designed to work hand in hand with Cumulus Linux, Cumulus NetQ provides actionable insight into every trace and hop in the Linux-based data center—from the container, virtual machine, or host, all the way to the switch and port. The metadata it collects across these elements ensures visibility and intelligence into the health of the network, making sure everything is behaving as intended. Cumulus NetQ 1.3, available now, adds direct integration with Kubernetes, the popular container orchestration engine in use by 71% of enterprises.1 This release also supports the Container Networking Interface (CNI) ecosystem, specifically across the two most popular CNIs of Calico and Flannel. Both CNIs are maintained by Tigera, which has partnered with Cumulus on the integration. Enterprise adoption of Linux-based containers is increasing rapidly, due to containers’ ability to dramatically improve flexibility when running cloud-native applications on a physical or virtual infrastructure. 451 Research predicts2 containers will grow to become a $2.7 billion market by 2020; 3.5 times greater than the $762 million container market in 2016. Yet with all their benefits for speed and efficiency, containers can cause major challenges for network operators. Because containers are ephemeral, the traffic patterns are constantly changing, so being able to view history and changes to the network becomes more important than ever. According to Gartner, multihost networking is important because “the portability and ephemeral life cycle of containers will overwhelm the traditional networking stack. The native container networking stack doesn't have robust access and policy management capabilities.”

https://www.businesswire.com/news/home/20180418005410/en/Cumulus-Networks-Bolsters-Cumulus-NetQ-Kubernetes-Integration

Microsoft delivers first test build of Windows Server 2019

@Microsoft is making available today, March 20, the first preview build of its next on-premises Windows Server release, known as #WindowsServer2019. To test the release, those interested should sign up to be Windows Insiders. The final version is slated to roll out to users in the latter half of calendar 2018, right around the same time as the next feature update for Windows Server, known as 1809, which is expected to roll out in October 2018. Windows Server 2019 is going to be the next version of Windows Server that qualifies as a Long-Term Servicing Channel (LTSC) release. Windows Server 2016 is the current LTSC release of Server. Microsoft recommends admins who want to run SQL Server, SharePoint Server and other workloads to go with the LTSC version of Windows Server and not the Semi-Annual Channel versions. (An example of a Semi-Annual Channel version of Windows Server is the soon-to-be-released 1803 and the coming 1809; these are the feature updates released twice yearly and supported for 18 months only.) Microsoft officials have said before that the on-premises/LTSC versions of Windows Server will include features that previously have debuted in the Semi-Annual Channel versions. In today's blog post about Windows Server 2019, Microsoft officials listed a few of the features they're planning for Server 2019. Among these features: Windows Defender Advanced Threat Protection service is coming to Windows Server 2019 (as it is to Windows 7 and 8.1) Windows Subsystem for Linux will be built into Windows Server 2019 (just like it is in Windows 10) Linux containers will be able to run on Windows Server 2019 Further reduction in size of the Server Core base image in Windows Server 2019 Kubernetes management of Windows Server 2019 hosts Project Honolulu (Microsoft's graphical management tool for Windows Server that's been in preview) will be generally available and be able to manage new hybrid-cloud scenarios as of Windows Server 2019

http://www.zdnet.com/article/microsoft-delivers-first-test-build-of-windows-server-2019/

IBM Unfurls Analytics Platform Based on Microservices

@IBM #Microservices will be enabled by @Kubernetes #container #orchestration software which could change how next-generation #AI applications are built. IBM today unveiled an analytics platform based on an in-memory database and a microservices architecture enabled by Kubernetes container orchestration software that promises to transform how next-generation AI applications are built, deployed and consumed. Capable of ingesting data at a rate of one million records per second, the IBM Cloud Private for Data platform is intended to enable analytics infused with AI capabilities to surface insights in real time, says Rob Thomas, general manager for IBM Analytics. “We can ingest 250 billion records a day,” says Thomas. The IBM Cloud Private Data platform makes extensive use of Docker containers to both capture data in a standard format and expose analytics as a set of easier to consume microservices.
https://www.rtinsights.com/ibm-unfurls-analytics-platform-based-on-microservices/

How Amazon could kill Kubernetes with developer kindness

As of re:Invent 2017, @Amazon Web Services ( #AWS ) loves @Kubernetes and is officially "all in" on the open source container orchestration project. Given that 63% of Kubernetes cloud workloads already run on AWS, coupled with AWS's stated goal of enabling maximum developer choice, it was perhaps a foregone conclusion that AWS would roll out Amazon Elastic Compute Service for Kubernetes (EKS), a managed Kubernetes service to rival those already offered by @Microsoft and @Google. What isn't certain, however, is what happens next. After all, almost in the same breath that AWS chief Andy Jassy announced EKS, he also announced Amazon Fargate, a serverless option for managing containers. In so doing, Rishidot founder Krishnan Subramanian has argued, Fargate could make "Kubernetes a sideshow [for] container cluster management."

https://www.techrepublic.com/article/how-amazon-could-kill-kubernetes-with-developer-kindness/

IBM Java CTO: Devs shouldn't have to learn Docker, K8s, 30 other things to deploy an app

Index At @IBM 's Index developer conference in San Francisco, on Tuesday, @The Register sat down with Big Blue's @Java CTO @John Duimovich to talk about the Java programming language, IBM, the cloud and other developer-oriented concerns. Duimovich made the case for IBM as a cloud platform partner, based on the company's Java expertise. He also argued for Java – 22 years old – as a vital, evolving language. Oracle, Java's meddling uncle, last year said it would hand over governance of Java EE to the Eclipse Foundation. For enterprise Java, that means a chance to accelerate the development and deployment of new features and to become more responsive to the needs of corporate developers. "What they did is they gave control of the evolution of enterprise Java to a foundation," Duimovich explained. "They moved the code itself and the governance. And I think that was in part that acknowledgement of some of the momentum that MicroProfile has had." MicroProfile is an initiative to make Java EE – or Jakarta EE, assuming the name change vote goes as expected – more suitable for the development of lightweight, composable microservices, as opposed to large monolithic applications. "This is where the compatible future of cloud Java is being defined," he said. "You're going to see EE evolve to adopt many of these new technologies." We sent a vulture to IBM's new developer conference to find an answer to the burning question: Why Big Blue? READ MORE IBM, said Duimovich, is interested providing support for any language that enough developers want. He said the company sees quite a bit of interest in Node.js, particularly for front-end applications, and more modest interest in Swift now that its ecosystem has become more mature. "If you have any serious performance needs, Java's your story," he said. "If you want to integrate with all the systems you're going to have to integrate with terms of an enterprise, no question." Duimovich contends enterprise Java is "actually a pretty interesting space" these days, pointing to developments like reactive programming, where you're dealing with asynchronous code and high event rates for IoT applications. "Enterprise Java at the Eclipse Foundation is going to drive new features more quickly," he said. "And I think it will also be a more inclusive community that's easier to join." For IBM, that's an opportunity to build relationships with the open source development community. "Now that IBM is open source, we have a much greater chance to actually engage with developers," he said. Where once IBM kept its cards close to its vest, now as developer of open source technology, there's far more contact with the development community, which has the potential to translate into new customers. "This excites me because I've much better contact points, a broader set of developers," he said. "People who may not be IBM customers still are able to interact with us and work with us and then, and hopefully from our perspective, turn into IBM customers because they can buy support and other things." Embracing open source means opportunities for technical interaction between IBM personnel and outside developers. Duimovich recounts how IBM gave a university course in how to use the OMR technology to build a virtual machine called Base9. "We got six people instantly who want to work with us because they knew we were doing this," he said, adding that being involved in open source means a better reception from developers. Obscure bug reports Open sourcing its JVM hasn't translated into a significant increase in community code contributions yet, but Duimovich voiced appreciation for the obscure bug reports where someone will fix some edge case with a line or two of code. Seeing Java EE develop at a more rapid pace has pluses and minuses, Duimovich said. "Developers who are waiting for language features and other stuff won't have to wait three years," he explained, pointing to aspects of Kotlin, Scala, or other languages that may be incorporated into Java EE sooner rather than later. "Java this year got a shell, a read-eval-print loop (REPL)," he said. "Every other scripting language had that. Java is finally there." The downside, he said, is that everyone has to move faster just to keep up. "It's a great time to be a Java developer," he said, "and a VM developer," adding that competition between virtual machines benefits everyone. Duimovich sees IBM playing a starring role in the cloud optimization of Java. As an example he pointed to VM startup time. A 40-second startup time didn't matter as much when app servers stayed up for months, but you can't have that for containers. "So we've made both our startup time and ramp up time over 2x better than existing JVMs and we're continuing to focus on that," he said. IBM's Java VM has also been optimized to return memory when it's not being used. "Our VMs will automatically give the system back memory when we go idle," explained Duimovich. Reducing a system's memory footprint in the cloud translates to reducing the system's cost. That's not so much of an issue with JVMs that are maxed out all the time. "But I can tell you from our mainframes and from our deployments, we've seen there's a lot of idle VMs that wake up once in a while," he said. The most pressing technical issue for Java and containers, said Duimovich, is having Java memory adapt to container sizes, because if you exceed that, it kills the container. Low level "You want them to dance as one, so to speak," he explained. "If you reduce the memory in the container, you reduce the memory in Java. Those are the kinds of things we're working on at the low level." In its effort to reduce the footprint of Java, IBM is also working on moving its JIT compiler outside of the address space and have it as a service. "That opens up a huge bunch of opportunities for us," said Duimovich, noting that each instance saves 200 to 400 MB of footprint, which is what you want for microservices and moves Java closer to the memory requirements of other languages. And as a service, he said, it has more visibility across instances, which provides the opportunity to compare performance data in A/B testing. "The easy way to think about it is if I'm bringing up 100 or 1000 microservices, did every one of them need to compile Object?" he said. "Clearly not. And you can get that with AOT – ahead-of-time compilation static – but then you've giving up some of the things Java can do like dynamic bytecode modification." Beyond @Java, Duimovich expressed interest in making development easier overall by making it more dev and less ops. "The notion that as a developer you'll have to learn @Docker, @Kubernetes, and 30 other things before you can even deploy an app is something I'd like to get rid of," he said. Maybe there's a cloud for that. ®

https://www.theregister.co.uk/2018/02/22/ibm_java_cto_john_duimovich_interview/

OpenEBS Certified With Red Hat OpenShift, StackPointCloud, and IBM Cloud

In the twelve months since open sourcing, @OpenEBS has become the most liked project of its type on @GitHub with a substantial contributor and user community. Users are now talking at meet-ups around the world about how they use OpenEBS to simplify and improve the storage of important data created by #microservices, whether running in enterprise #datacenters or on the #cloud.   This success has not gone unnoticed by partners that use @Kubernetes in their solutions.   Today @MayaData, the company behind @OpenEBS, has announced partnerships with @RedHat @OpenShift and @StackPointCloud, two of the leading Kubernetes based management platforms now available. OpenEBS was certified by both partners and now is an available default option for storage for the leading orchestration solution Kubernetes; OpenEBS runs on Kubernetes to provide storage to Kubernetes. Importantly, OpenEBS can run in conjunction with underlying shared storage to provide better control and performance while extending the life of existing shared storage systems. Technical leads from StackPointCloud and the OpenEBS community are doing two online Hangout / AMA sessions to demonstrate OpenEBS on StackPointCloud serving Jenkins and other workloads on Friday Feb 16, 2018.  

https://www.prnewswire.com/news-releases/openebs-certified-with-red-hat-openshift-stackpointcloud-and-ibm-cloud-672729373.html

Cisco Champions Public Cloud Choice And Partner Flexibility With New Cisco Container Platform

@Cisco Systems is moving to one-up competing vendors in the burgeoning market for @Kubernetes #container #technology with the introduction of a turnkey system designed to allow for deployment and management of containerized applications across public and private clouds. Called the Cisco Container Platform, the system gives partners a clear path into lucrative application lifecycle management and other services sold on a recurring revenue basis, and as the platform expands, those opportunities will only grow, executives said. "Partners love having choices of solutions so they can do real value-based selling," said Dave Cope, senior director, Cisco Cloud Platform and Solutions Group. "They don't have to walk in and try to shove any peg in a hole. They can listen to the customers, understand their needs and from Cisco provide a variety of solutions based on the maturity and needs of their customer."

http://m.crn.com/news/cloud/300098641/cisco-champions-public-cloud-choice-and-partner-flexibility-with-new-cisco-container-platform.htm

HPE and Portworx Tap Kubernetes for Stateful Container Storage Config

@Hewlett Packard Enterprise ( #HPE) and @Portworx released a reference configuration that uses @Kubernetes to offer enterprises a quick way to deploy and manage #stateful #container workloads. The reference configuration, which refreshingly lacks a catchy name or acronym, combines HPE’s #Synergy composable system as the basis for running Portworx’s #PXEnterprise storage platform using Kubernetes as the container orchestrator and scheduler.

https://www.sdxcentral.com/articles/news/hpe-and-portworx-tap-kubernetes-for-stateful-container-storage-config/2018/01/

Serverless Framework for Real-Time Apps Emerges

Serverless computing can advance real-time applications by providing developers with access to a framework employing an event-driven architecture. Serverless computing has a lot of potential to advance real-time applications by providing developers with access to a framework employing an event-driven architecture that makes IT infrastructure resources seamlessly available on demand. The trouble is that the existing serverless computing frameworks are too slow to support real-time applications. At the Kubecon + CloudNativeCon 2017 conference this week iguazio moved to address that issue by making available a high-speed serverless computing framework as an open source project that it developed in support of the company’s real-time analytics database See also: Why putting #IoT into @Docker containers will unlock it Dubbed nuclio and written in the #Go programming language, iguazio CTO @Yaron Haviv says this #serverlesscomputing framework is unique because it allows developers to employ function within the context of a Docker container running on a @Kubernetes cluster or a software development kit ( #SDK ) that iguazio developed. That approach differs considerably from a proprietary serverless framework such as the @Lambda service developed by @Amazon Web Services ( #AWS), which Haviv also notes requires organizations to also consume a raft of complimentary AWS compute and storage services to work. Supported programing language include supports Golang and Python, with support for Java and Node.js coming soon. Haviv says the high-speed function-as-a-service (FaaS) layer of software iguazio developed for nuclio makes it possible for real-time applications to invoke IT infrastructure in parallel on a truly elastic basis. “Nuclio uses Flash directly,” says Haviv. “In an on-premises environment, it can fit in a 2u box.” In addition, Haviv says nuclio includes tools to enable simple debugging, regression testing and even a multi-versioned continuous integration/continuous development (CI/CD) pipeline to drive DevOps processes. Function images can also be stored in a shared repository.

https://www.rtinsights.com/serverless-framework-for-real-time-apps-emerges/

The Evolution and Future of Hypervisors

#Hypervisors are a #virtualization technique that powers #cloudcomputing infrastructure like @Amazon #EC2 and @Google #ComputeEngine. Although #container virtualization technology like @Docker and @Kubernetes have taken the spotlight recently, #containers are often deployed on top of hypervisors on the cloud. In this article, we will first outline the architecture of classical trap-and-emulate hypervisors that were invented in the 1970s. We then describe how hypervisors evolved from the 1970s to today’s cloud computing era. Finally, we will look at future trends that affect hypervisor design. (This article was inspired by an awesome talk on Amazon’s Nitro project by Anthony Liguori, which I highly recommend everyone interested in hypervisors and cloud infrastructure to watch.) Architecture A hypervisor is a piece of system software that provides virtual machines (VMs), which users can use to run their OS and applications on. The hypervisor provides isolation between VMs, which run independent of each other, and also allows different VMs to run their own OS. Like other virtualization techniques, hypervisors provide multitenancy, which simplifies machine provision and administration. One of the main criticisms against hypervisors is that they tend to usually be heavy-weight compared to other virtualization techniques like containers (Morabito et al., 2015). However, it’s also possible to build hypervisors that are light-weight (Manco et al., 2017) and also make the guest OS more light-weight when running in under a hypervisor (Madhavapeddy, 2013). A hypervisor can be decomposed into two major parts: the virtual machine monitor (VMM) and the device model. The VMM is responsible for setting up VMs and handling traps (a.k.a VM exits) caused by the guest OS executing privileged instructions like I/O access. The device model, on the other hand, is responsible for implementing I/O interfaces for all the devices like networking cards, storage, and so on, the hypervisor supports. Hypervisor architecture is illustrated in the following diagram. Hypervisor architecture. The hypervisor can be decomposed into two parts: the virtual machine monitor (VMM) and the device model. (The terms hypervisor and VMM are often used interchangeably. However, we refer to hypervisor as the combination of a VMM and a device model.) Virtual machine monitor (VMM) A VMM must satisfy three properties (Popek and Goldberg, 1973): Equivalence property states that program execution has identical observable behavior on bare metal and under VMM, except for timing and resource availability, which are difficult to preserve because of shared physical hardware. Efficiency property states that the majority of program instructions are executed directly on a physical CPU without interference from the hypervisor. Resource control property states that the VMM manages all hardware resources. Virtual machines require permission from the hypervisor to directly access hardware. As a side note, it’s worth noting that emulators satisfy both equivalence and resource control properties, but does not satisfy the efficiency property. The KVM subsystem in the Linux kernel (and other OS’es it has been ported to), for example, provides the building blocks for implementing a VMM. The KVM subsystem is effectively a portable abstraction over CPU hardware virtualization capabilities, which can be leveraged by userspace applications like QEMU to implement a VMM or a full hypervisor. Device Model The device model is the part of a hypervisor, which provides I/O interfaces for virtual machines. While the VMM is responsible for handling traps, it delegates I/O requests to the appropriate device model. Examples of device models are virtualized NICs and storage devices. Device models can either provide interface for a real hardware device or a paravirtualized device. The device model can be implemented either using software, like the virtio family of drivers, or in hardware, using SR-IOV, for example. I/O Virtualization To implement a device model, I/O virtualization is needed. The two approaches for I/O virtualization are software-based and hardware-assisted. Software-based I/O virtualization implements I/O interfaces in software to allow sharing the same physical devices across multiple virtual machines. Software-based I/O virtualization can be implemented on top of various different backends. For example, a software-based storage device can be layered on top of a block device or a filesystem. One issue with software-based approach is that the device model uses the same CPU resources that the vCPUs, which reduces available CPU capacity and causes jitter. Hardware-assisted I/O virtualization implements I/O interfaces in hardware. This approach requires hardware support for sharing the same physical device across multiple virtual machines. SRV-IO is a PCI extension, which allows a physical PCI function to be partitioned into multiple virtual PCI functions. Evolution The semantics of a trap-and-emulate VMM was formalized in the early 1970s (Popek and Goldberg, 1973) and made popular again in the mid-1990s for running commodity OS’es on multicore machines (Bugnion et al., 1997). However, the most popular machine architecture at the time, Intel x86, was not virtualizable because some of it’s privileged instructions did not trap. The VMware hypervisor, which targeted x86, was first released in 1999. It used binary translation to replace privileged instructions to trap into the hypervisor, while still running unprivileged instructions directly on the physical CPU, which solved x86’s virtualization issues (Adams and Agesen, 2006). This allowed the VMware hypervisor to run unmodified commodity OS’es on x86 hardware in virtual machines without the performance penalty of emulation. The Xen hypervisor released first in 2003 took a different approach to solving the x86 virtualization issue. Instead of binary translation, they modified the source code of the guest OS to trap to the hypervisor instead of executing non-trapping privileged instructions. Intel and AMD released x86 CPUs with virtualization extensions in 2005 and 2006, which made classic trap-and-emulate virtualization possible. KVM, initially developed for Linux, implements a kernel subsystem that in combination with QEMU’s device model provides a full hypervisor. Initially, the KVM project provided software-based device model that emulated full hardware devices, but later acquired paravirtualized I/O device model when the virtio device model was introduced. Future The classic hypervisor architecture has stood the test of time but there some trends that affect hypervisor design. Hardware virtualization is becoming more wide-spread. For example, the Amazon Nitro project (talk by Anthony Liguori) takes an unconventional approach to hypervisor design, which replaces all of the software-based device model with hardware virtualization as illustrated in this diagram. Amazon’s Nitro hypervisor also uses a custom designed VMM that leverage’s Linux KVM. Operating systems have also started to evolve to accommodate hypervisors better. Unikernels are an interesting OS design approach that packages the OS and the application into one bundle, which runs in the same CPU protection level (Madhavapeddy, 2013). This eliminates the traditional separation between kernel and user space, which reduces context switch and system call overheads at the expense of losing some OS functionality. The basic idea was already pioneered earlier in the form of library OSes, but the much simpler device model of a hypervisor compared to bare metal made the idea much more feasible for real world use. Light-weight virtualization is becoming more and more important as the use of cloud computing grows. Containers are excellent technology for providing light-weight virtualization. However, containers are unable to provide the full isolation capabilities of VMs, and have various security problems because containers share the same host OS and have access to the large OS system call interface (Manco et al., 2017). Hypervisors can be slimmed down significantly (Manco et al., 2017) and unikernels provide even larger opportunity to optimize the hypervisor if we relax the equivalence property requirement of VMMs (Williams, 2016). Serverless computing is a new computing model, better described as Functions as a Service (FaaS), that allows application developers to deploy functions instead of applications to a managed platform. One approach to serverless computing is to use hypervisors and unikernels for packaging and deploying the functions (Koller and Williams, 2017). Energy efficiency is another important future direction for hypervisor design. Communications technology, which cloud computing is a large part of, is forecasted to consume around 20% of global electricity by 2030, or as much as 50% in the worst case (Andrae and Edler, 2015)! The energy overhead of a hypervisor can be extremely high depending on workload. One experiment reports between 59% and 273% energy overhead for KVM (Jin et al., 2012)! Kernel-bypass networking has become important recently because NICs are getting faster and traditional TCP/IP and POSIX socket abstraction is proving to have high overheads (Han et al., 2012; Young et al., 2014; Yasukata et al., 2016). Hypervisors that implement the device model using I/O paravirtualized effectively introduce another layer to the networking data path, which increases networking overheads. In Linux, the vhost architecture is one solution to the problem. Vhost moves the virtio paravirtualized I/O device model from QEMU (which is the VMM userspace kernel) to the host kernel (which also hosts the KVM module), which eliminates the exit from host kernel to userspace VMM. Another solution is full hypervisor kernel-bypass using hardware NIC virtualization introduced by the Arrakis project (Peter et al., 2014). Summary The hypervisor architecture invented in the 1970s has stood the test of time. The x86 architecture quirks meant that the first successful hypervisors had to resort into binary translation to handle privileged instructions. Binary translation solutions were followed by paravirtualization (popularized by Xen) but hypervisor architectures were consolidated to the classic model as Intel and AMD added virtualization extensions to the x86 architecture. Although containers have recently become a very popular virtualization technique, emerging computing paradigms like serverless computing could make hypervisors an attractive technique again. Light-weight hypervisor designs, unikernels, and hardware-assisted virtualization all reduce hypervisor overheads, which also makes hypervisors more competitive against containers.
https://medium.com/@penberg/the-evolution-and-future-of-hypervisors-999f568f9a5d

How Serverless Technologies Impact Kubernetes

#Containers may serve as functions in a @Kubernetes environment—an approach in contrast to other services. On today’s episode of The New Stack Makers streamed live from KubeCon + CloudNativeCon, we were joined by @Alex Ellis, Principal Application Developer at @ADP and Director at @OpenFaaS, and @Kassandra Perch, @IOpipe Developer Evangelist. We discussed the differences, similarities and the relative overall maturity of #serverless technologies. For those used to working with more traditional cloud-native environments and who are looking to utilize serverless technologies, having the ability to work with containers provides familiarity and stability. “Having the @Docker container as that primitive means that we can get a buy-in from the whole cloud-native community. It’s what they know, and it’s what they trust. It’s battle tested. You can just take that to production,” said Ellis. OpenFaaS gives developers the ability to package both code and binaries as serverless functions, with the flexibility to choose either Docker or Kubernetes as one’s serverless platform of choice. Sponsor Note The Cloud Native Computing Foundation (CNCF) is driving adoption of a new computing paradigm that is optimized for modern distributed systems environments, including container packaging, dynamic scheduling, and microservices-based application development and operations. Perch later went on to highlight the ways in which IOPipe is focusing on AWS Lambda, and is interested in seeing the serverless community evolve and grow. “You lose a lot of control over your application when you go with a cloud function provider like @AWS Lambda, or @Google Cloud Functions,” Perch said. “I think that’s why Kubernetes-based systems are so interesting, because you get a little bit of that control back, for better or for worse.”

https://thenewstack.io/serverless-technologies-impact-kubernetes/

Red Hat takes different path in app design as enterprise scales out

The year-long embrace of the @Kubernetes container orchestration management system across the enterprise culminated in @Amazon Web Services Inc.’s announcement last month of its @Elastic #Container Service for the #opensource storage platform. The announcement was not a major surprise, given the news in August that AWS would be joining the #CloudNativeComputingFoundation, but it was well received by developers at the recent AWS re:Invent conference in Austin, Texas, nonetheless. One major reason for the positive response is that Kubernetes has increasingly become a significant element in the design and deployment of applications. For open-source companies like Red Hat Inc., this will be a key focus as the container revolution marches boldly into 2018. “Kubernetes has been the single biggest driving force to shift all enterprise architecture from scale up to scale out. That has created a whole number of ripple effects in how applications are designed within the enterprise,” said Steve Watt (pictured), chief architect of emerging technologies at Red Hat.

https://siliconangle.com/blog/2017/12/27/red-hat-takes-different-path-in-app-design-as-enterprise-scales-out-kubecon/

VMware's Big Vision: Deliver Any Application, On Any Device On Any Cloud

Maintaining a tradition of innovation, @VMware has extended its technology from the #datacenter into #publicclouds, #hyperconvergedinfrastructure, and #edgedevices, @MuneybMinhazuddin, VMware's vice president of solutions product marketing, told attendees of The NexGen 2017 Conference & Technology Expo. "Our vision is to deliver any application on any device on any cloud," Minhazuddin said Wednesday at the conference in Los Angeles. VMware has been disrupting technology since it released the hypervisor that first virtualized compute, then expanded that product into a broad private cloud solution. But the current portfolio stretches across a broad range of environments, with security embedded throughout, he said. "For VMware, innovation has been the core of how we've gone to market. We've disrupted the market in everything we do," Minhazuddin told NexGen attendees. The company's public cloud strategy goes beyond partners currently offering VMware environments—most notably Amazon Web Services and IBM. "Our cloud strategy has gone from building my own cloud to really consistent infrastructure across as many clouds as possible and consistent operations across all the clouds out there," he said. The inclusive, multi-cloud approach is driven by the monumental change that's taking place across all verticals in what businesses expect from their technology. "Tech used to be a support system for the business. Now, across all industries, tech is actually becoming a business," Minhazuddin said, adding companies not leveraging technology to run their businesses are being left behind. That imperative for digital transformation is focusing attention at the top of the stack. "What we see is it's all about the app. Your customer experience comes down to those applications," Minhazuddin said. Enterprises want more cloud-native applications, developed fast with DevOps-oriented methodologies. "The barrier to entry is as simple as, I have an idea, I spin up an app, I host it in the cloud," Minhazuddin said. VMware's comprehensive strategy starts with the company's bread and butter—private cloud. Newly developed products make private clouds easier to deploy, manage and secure, he said. With VMware Cloud Foundation, the company bundled all the elements of hybrid cloud, including NSX virtualized networking and vSAN storage, and added lifecycle automation to tackle mundane infrastructure maintenance. That makes the on-premises environment start looking like a cloud, with the "data center running on auto-pilot," freeing IT teams to focus on delivering applications for the business. VMware also extended vSAN into Dell-EMC hyper-converged appliances VxRack and VxRail—a common request from CIOs looking to leverage hyper-converged infrastructure. The platform then "landed into AWS," Minhazuddin said. While the deal struck with Amazon to offer VMware environments in the public cloud was game-changing as far as facilitating hybrid environments, it was only a part of VMware's grand vision. "What we realized is there's not going to be a single destination," he said. The strategy was to provide consistent infrastructure in the #datacenter and to public cloud partners like @AWS, @IBM, @Microsoft #Azure for Desktop-as-a-Service, @Google Cloud Platform for a managed @Kubernetes #container service, and thousands of MSPs running @VMware environments. But where the company didn't have a partnership that could yield consistent infrastructure, it looked to still enable consistent operations, he said. To that end, VMware Cloud Services delivers a host of management capabilities across private and all public clouds embedded into offerings like NSX, the Wavefront monitoring and analytics platform, the new AppDefense security platform, Workspace One user management, AirWatch device management, and more. The broad scope of its products helps customers transform their approach to cybersecurity, Minhazuddin said, an area where scale really starts to cause uncertainty for customers. "We're here to transform and lead the industry in secure infrastructure," he told NexGen attendees. VMware built "cyber hygiene" security principles directly into its infrastructure to deliver an integrated ecosystem that always implements the "fundamental things you do to keep a state of good." The five pillars of that approach are least privilege, segmenting networks and data, end-to-end encryption, multi-factor authentication, and patching. All the high-profile attacks in 2017 resulted from failures in at least one of those fronts, he said. Sourena Amini, a principal engineer at Sage Software who attended the NexGen session, told CRN VMware is wisely looking to solve one of the most significant problems in cloud computing—the difficulty in moving workloads between providers. "He was talking about how we can abstract the unit of business with unit of computing, storage and networking," Amini said. "The holy grail is to have common standards to go to any vendor. These guys are trying to make that happen at a smaller scale within their own ecosystem." Ubiquitous standards based on APIs are still years off, Amini said, but VMware is achieving something resembling that goal on a smaller scale. And security is an essential component of that vision. "You have to apply [security] to all, not just one vendor," he said. 

http://www.crn.com/news/cloud/300096836/vmwares-big-vision-deliver-any-application-on-any-device-on-any-cloud.htm?itc=most_pop

Containers will oust VMs and storage arrays, says Red Hat

@RedHat launches storage delivered via #containers and predicts a future in which costly and inflexible #storagehardware and pricey #hypervisors will be a thing of the past The #traditionalstorage array will become a thing of the past – and so will the virtual machine and hypervisor. Costly and cumbersome and lacking the flexibility to support the unpredictable and “bursty” requirement of applications in the cloud era, they will be replaced by containers.

That is the view of Red Hat, which earlier this month launched Container-Native Storage 3.6 for Red Hat #OpenShift Container Platform 3.6, its distribution of the @Kubernetes container #orchestration software.

In Openshift Container Platform, customers can deploy applications via container, rapidly scaling instances according to workload requirements.

Container-Native Storage allows storage for container-based apps to be spun up, run and be decommissioned as required to support those applications and can run on-premise or in the cloud and with service levels set by policy.

New features in Container-Native Storage include the addition of support for block (via iSCSI) and object storage.

Containers – such as Docker – are emerging as an alternative to server virtualisation. They are effectively a form of software-defined server/storage and offer a form of virtualisation, but more lightweight, that runs directly on the operating system.

Containers lack the hypervisor layer, and also the often-duplicated data in virtual machine images.

Containers excel where the rapid scaling of web serving requests is met by the creation, use and dying out of many containers managed by an automated orchestration platform.

http://www.computerweekly.com/news/450428848/Containers-will-oust-VMs-and-storage-arrays-says-Red-Hat

Cloud Blockbuster: Cisco Teams With Google In Massive Enterprise Public Cloud Offensive

@Cisco is teaming up with enterprise powerhouse @Google in a wide-ranging deal that provides the networking giant with a seamless bridge to next-generation #publiccloud technologies including the coveted @Kubernetes #container #orchestration platform. The Cisco and Google Cloud #hybridcloud offering, which will become available in the second half of 2018, opens the door for developers to combine emerging Google Cloud services with Cisco on-premises networking, hyper-converged, and security offerings. Partners said the blockbuster deal gives Cisco a major competitive advantage as it extends its networking and security offerings into the fast-growing enterprise public cloud marketplace. [Related: Partners 'All In' On Cisco's AI And Machine Learning Investments] "With Google Cloud, Cisco can remain there to help you with the security, the routing, the orchestration -- it's a very good approach," said Robert Keblusek, CTO of Sentinel Technologies, a Downers Grove, Ill.-based solution provider and Cisco Gold partner ranked No. 117 on CRN’s 2017 Solution Provider 500 list. "It makes a lot of sense that Cisco wants to essentially network clouds -- provide orchestration, automation, management and security across all these different clouds. The more Cisco allows us to do from a networking and security perspective for customers that are consuming cloud services, the better." The hybrid solution will extend network policy and configurations to multiple on-premises and cloud environments, including orchestration and lifecycle management of resources, applications, and services. [Sponsored Suggested Post: Free IoT Virtual Conference Learn how to monetize IoT solutions. Discover new IoT technologies. Build strategic partnerships.] Kip Compton, vice president of Cisco's Cloud Platform and Solutions Group, said the combined platform would be open and flexible leveraging Google Container Engine with Cisco's broad portfolio of networking, security, hyper-converged and infrastructure solutions. "From the Cisco side, our HyperFlex hyper-converged platform we'll be adding Kubernetes to support this solution. But we're really bringing our entire portfolio to play," said Compton, in an interview with CRN. "We're going to be enable customers to define policy on the networking side that span the on-premise and Google public cloud environment. Likewise on security." The solution's hyper-converged platform supports existing application and cloud-native Kubernetes environments. It also leverages Google's Apigee enterprise-class API management, which enables legacy workloads running on premises to connect to the cloud through APIs. Enterprise app developers can securely access cloud APIs, and cloud developers can securely access enterprise APIs and on-premises resources. Sentinel's Keblusek said managing things like security, automation and artificial intelligence requires partners to "have a deep API access to infrastructures." "More and more of our investments in our management tools and how we go about automation are through APIs talking to various cloud providers," said Keblusek. "With Google's Apigee, you can take these legacy workloads on-premise to connect. So if I have a legacy workload and I want to connect to another workload or manage something in the cloud, I can tap into the API to help take control of aspects of the cloud that I need."

http://www.crn.com/news/networking/300094461/cloud-blockbuster-cisco-teams-with-google-in-massive-enterprise-public-cloud-offensive.htm

Virtuozzo simplifies persistent data storage for Kubernetes clusters

#Hyperconverged infrastructure software provider @Virtuozzo Inc. has punted out a new #persistentstorage product for @Kubernetes, which is a popular orchestration tool that’s used to manage software application #containers. The move comes following this summer’s release of Virtuozzo Storage for @Docker, a #softwaredefinedstorage platform designed for managing Docker containers with persistent data in production. Persistent storage, sometimes called nonvolatile storage, relates to storage devices that retain data after the power is switched off. With regard to application containers, the term more generally refers to storage volumes or individual clusters that remain available and retain data after the life of individual containers. Being able to retain data after an application container has shut down is obviously desirable, but Virtuozzo Chief Executive Officer George Karidis said it’s not so easy to set up this kind of persistent storage in container deployments that span across multiple servers. That’s where the new Virtuozzo Storage for Kubernetes platform should prove to be helpful, as it provides customers with a simplified way to set up and manage these persistent storage volumes. Basically, Virtuozzo Storage for Kubernetes is a set of easy-to-use management tools built atop of the company’s flagship software-defined storage platform. With the new product, users can set up, monitor and manage their Kubernetes storage clusters and other services such as file and object storage more easily. In addition, the platform allows users to define storage classes and automatic snapshot policies to ensure everything is safely backed up. Virtuozzo Storage for Kubernetes can be run on any kind of commodity hardware, the company said. “With our latest Virtuozzo Storage for Kubernetes solution, we’re delivering a tightly integrated, production-ready solution for K8s that makes it very easy for any enterprise, small business or service provider to put containerized apps into production,” Karidis said. Virtuozzo said its new Kubernetes storage platform, and also its Virtuozzo Storage for Docker, are both being exhibited this week at the DockerCon EU ‘17 event taking place in Copenhagen.

https://siliconangle.com/blog/2017/10/16/virtuozzo-simplifies-persistent-data-storage-kubernetes-clusters/

How to Put Docker into Production with Persistent Storage

As the adoption of application containers, including #Docker and #Kubernetes, continues to experience explosive growth, the need for effectively providing persistent storage to run stateful applications in production has developers and IT departments looking for answers. Typically, applications and data are kept separate: server-side applications can be horizontally-scaled easily to increase performance, cloned in the case of a failure, or removed if no longer needed. Storage resources are decoupled from the application, and its lifecycle is independent. While many application components can be designed to be stateless, this is almost never true for an entire application. The main example being a database, an application that may not be on the bleeding edge of application delivery, but still may be run in Docker containers. So, Docker for example, needs to have a way to allow applications to store and manage persistent data.  One solution for adding persistent storage of data to an application is leveraging object storage like S3. However, S3 does not support all data types — for example, a typical database is placed on a file system, and doesn’t fit the S3 model. To solve the problem, Docker volumes were introduced. Docker volumes add a data directory into an ephemeral container. Ephemerality means that an application running in a Docker container can be removed or redeployed at any time. In practice, the Docker storage volume is attached to a container upon start up with either the -v option or via Dockerfile's VOLUME instruction. The volume is managed independently from the container, ensuring that the volume isn’t deleted automatically when the container it is attached to goes away. While Docker volumes are a native feature of Docker, native implementations are very limited. The most important thing to know about Docker volumes is that out-of-the-box, Docker only supports local volumes (stored on the file system of the server where a container is deployed). This may be acceptable for development and testing environments, but it’s a show-stopper for production environments. This is because: Storage coupled with the original host will be lost if the server is rebuilt. Management and data protection are hard to implement with local volumes. In a multi-server environment (with Swarm or Kubernetes), the application owner has little control over which server will be chosen to deploy a new container. For many, relying on local storage is not a viable solution. Attaching an NFS share as a mount point for a container can be a solution for Swarm/Kubernetes clusters initially, but when production scaling begins, a flexible, manageable storage solution is required. For Docker users, there are alternatives. A good solution can come in the form of software-defined storage which runs on the same host as the application container and addresses all storage needs required by Docker. For example, you can connect a solution like Virtuozzo Storage with a Docker-certified plug-in, which provides an effective, high performance alternative (to native local volumes) storage backend for Docker volumes. The plug-in approach adds the much-desired flexibility in storage options for Docker users, who can pick a storage solution that is most appropriate for their needs. When leveraging a more complete software-defined storage to solve persistent storage needs, you gain a lot more in terms of how you can re-imagine the way your company manages its storage resources. Below are just some of the higher-level benefits of using software-define storage solution: High performance: faster than CEPH Extremely cost efficient: Works with commodity off-the-shelf hardware Massively scalable: Store petabytes of data. Easy to manage: Stay in control with an easy-to-use web-based management interface. When it comes to persistent storage for app containers, success is based on two key technologies: SSD caching and journaling provide a significant performance increase to the storage cluster with only 1 SSD per 4 HDD, and automated load balancing to keep "hot" data cached by moving it to less utilized disks, or local disks, or SSD disks – all to maximize utilization of all storage resources. After the Docker volume plug-in implementation, all the benefits of software-defined storage can be realized, in addition to getting persistent storage for application containers. Docker Swarm users can get a production-ready solution that combines storage and compute, eliminating the need for dedicated storage hardware. At the same time, storage performance grows linearly with deployment size and its capacity and performance demands, ensuring that storage is never a bottleneck in the container orchestration platform.

https://www.cio.com/article/3222727/infrastructure-storage/how-to-put-docker-into-production-with-persistent-storage.html

Amazon calls a $350,000 truce on the cloud wars and joins a Google-born cloud project

If you can't beat them, join them. That's what #Amazon Web Services ( #AWS ), did when it officially joined the Cloud Native Computing Foundation (CNCF) on Wednesday, just two weeks after #Microsoft joined as well. With Amazon's membership, CNCF now has the support of all five of the top cloud service providers, which is good news for #Kubernetes, a CNCF-managed container project. Kubernetes was created by #Google and is a key technology in Google's cloud. But Google gave the tech away as an open source project in 2014 and since then it's taken on a life of its own, with wide industry support. With AWS's blessing, this tech is one giant step closer to being the gold standard in what's known as "container management software," which is a technology that makes it easier to write apps for the cloud. By supporting Kubernetes, cloud vendors make it easier for their customers to jump ship from one cloud to the next. Both Microsoft and AWS committed to paying $350,000 annually for a seat on the board, which gives the companies some say in how funding is allocated across projects at CNCF. "We see Microsoft and Amazon joining as being the end of the beginning," Dan Kohn, executive director of CNCF, said. "The biggest companies in the industry are saying that there is real value here." CNCF manages a few different cloud technologies, but Kubernetes is the big one. AWS has its own competing tech, a proprietary service which would require users to stay inside of the Amazon technical universe. Kohn said that Amazon can continue supporting its competing product while working on Kubernetes. And, while this is all a feather in Google's cap, the true company at risk by the rise of Kubernetes is Docker, the $1 billion startup that basically invented this whole new market called containers and offers a direct competitor to Kubernetes. Still, Amazon didn't have much of a choice. Supporting Kubernetes is what Amazon users want. A CNCF survey found that 63% of users were already running Kubernetes on AWS — including Ticketmaster and the music video company Vivo. Kohn said that most users prefer software that is used en masse, and that can easily transfer across cloud providers. "This makes it even easier for companies to adopt Kubernetes. Companies want to use software that lots of other people are using because there will be more vendors supporting it and more people finding bugs," Kohn said.
http://www.businessinsider.com/amazon-joins-google-born-kubernetes-project-2017-8

VMworld 2017 Sneak Preview

The buildup to VMworld is always a frenzied time, and this year is certainly no different. The past 12 months has been an exciting time for VMware, as we have closed the Dell EMC deal, refined our focus and embraced and extended many partnerships. The R&D team is increasingly driven by customer-centric innovation. By that, I mean we are doing abundant due diligence to ensure our innovations are in line with our customers' most pressing challenges, and fit well within our engineering DNA. You'll see the results of this engineering focus at VMworld 2017. To begin, divesting from the cloud-provider business and selling VMware vCloud Air to OVH was a strategic necessity. We now no longer own or operate cloud datacenters, and that has allowed us to strengthen our value as a software company for the cloud era. Today, we have rapidly growing partnerships with those providers, with the common goal of working together to solve customer challenges. No one company can do it all, and I'm seeing the technology community as a whole doing a far better job of working together where possible, and differentiating where needed. Of course, we will compete in some places, but that won't stop us from working together at the same time.  Let's start with an example of one of the new emerging challenges we're working to solve in R&D. Internet of Things (IoT) is really starting to catch fire. We've learned from customers that there are many use cases where analyzing sensor and other types of data in the cloud just isn't practical. I've met with manufacturers in both the United States and Germany that expect many of their factories to generate a petabyte of data per day by 2020. Shipping that much data off-site each day for analysis isn't possible. Furthermore, many of these sites are physically isolated because these manufacturers won't risk an external compromise interrupting business. That said, these organizations have a strong need for edge compute appliances that can perform requisite analytics to improve operational efficiencies and indentify new competitive advantages. This is a challenge that can be solved in very compelling ways by combining #VMware 's experience with edge compute and #hyperconverged infrastructure, and the application platforms and frameworks from partners that complement our stack. That could be #AWS, #Docker, #Google, #Kubernetes, #Microsoft or #Pivotal. The list goes on. We're also seeing the need to scale serverless computing to the edge. While it would be difficult to move a full set of all serverless functions to edge devices and to keep them current, it's very achievable to move a set of necessary services to the edge. Organizations are asking for serverless solutions on our platform for a few reasons, including the need for lower latency, privacy, full telemetry and a verifiable audit trail. Customers in financial services, manufacturing and health care have all expressed interest in this approach. Before you consider this as some VMware-centric view of the world, note that Microsoft sees the same requirements, and recently released the Azure Functions Runtime as a result. At VMworld 2016, we demonstrated our cross-cloud vision and the feedback was highly positive. This year, we'll be showing the fruits of our cross-cloud labor and showcasing Software-as-a-Service (SaaS)-based cross-cloud management, networking and security. As we demonstrated last year, we've kept our focus on the top challenges facing organizations running their businesses across multiple and often competing clouds. That includes centralized network operations and security policies, cost management, and discovery, among other key capabilities. In addition to centralizing operations for cloud-provider-native services, we'll also showcase our progress in VMware Cloud on AWS. At this point, we've had a significant amount of early-access customers running their VMware environments in the AWS cloud. While we will certainly nod to the future, we will showcase a multitude of innovations, all of which will be available this year. I'm passionate about ensuring our innovations are timely and relevant, and hope to see you at VMworld, hear your ideas, and exchange thoughts and best practices. See you in Vegas!

https://virtualizationreview.com/articles/2017/07/01/from-the-cloud-to-the-edge.aspx?m=1