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Tag: hyperconverged infrastructure

  • Lenovo Updates Diverse HCI Platform Portfolio

    Lenovo today announced a bevy of updates to its server portfolio that expand the number of options organizations have when it comes to bundling stacks of software with Lenovo hyperconverged infrastructure (HCI) platforms to reduce the total cost of on-premises IT.

    For example, Lenovo in collaboration with Nutanix and AMD, today launched a Lenovo ThinkAgile HX HCI based on AMD EPYC processors, which promises to reduce by 50% the number of servers required to run the Nutanix HCI software stack.

    Lenovo in collaboration with Microsoft today also unveiled Lenovo ThinkAgile MX Azure Stack HCI Edge appliance based on Azure Stack HCI software. That platform runs the same software stack on-premises that Microsoft employs in its Azure cloud to simplify hybrid cloud computing environments.

    In addition, Lenovo added a Diamanti SR630 appliance to its lineup based on storage software developed by Diamanti optimized for instances of Kubernetes running on bare-metal servers.

    Finally, Lenovo in collaboration with VMware added a Lenovo ThinkAgile VX HCI offering that comes bundled with SAP HANA databases running on top of VMware vSphere.

    Kamran Amini, vice president and general manager of server, storage and software-defined infrastructure for the Lenovo Data Center Group, said rather than optimizing HCI infrastructure for one single platform such as VMware, the Lenovo portfolio is designed to provide IT organizations with the flexibility to enable organizations to deploy stacks of Nutanix, Microsoft, Kubernetes or VMware software as they best see fit.

    The economic downturn brought on by the COVID-19 pandemic has been especially challenging for providers of IT infrastructure platforms deployed in local data centers that many IT teams have been not been able to visit in recent months. However, those IT teams have been relying more on the ability to manage Lenovo servers remotely rather than attempting to migrate existing application workloads to the cloud overnight, he noted.

    It’s too early to say what the impact COVID-19 will have had on IT strategies. While many new applications are being deployed in the cloud, there is still a plethora of performance, security and compliance requirements that make it preferable to deploy some classes of workloads in on-premises IT environments. After more than a decade of having public clouds available as an option, the bulk of application workloads in the enterprise continue to run in on-premises IT environments. If it remains relatively simple to remotely manage those systems from home, the pressure to lift and shift workloads to the cloud becomes less intense.

    Amini said the COVID-19 pandemic essentially served as a wake-up call for organizations to modernize IT management processes using platforms that are designed to be managed from anywhere.

    Now that it’s apparent many IT teams will be working remotely a lot more often, many organizations are revisiting their IT strategies. There’s no doubt public clouds will play a larger role in IT going forward. However, the future of IT in general and cloud computing in particular will be, if anything, more hybrid than ever.

  • Nutanix Brings HCI Platform to AWS

    Nutanix Brings HCI Platform to AWS

    Nutanix today announced that Nutanix Clusters are now available on bare-metal instances of the Amazon Elastic Compute Cloud (Amazon EC2) provided by Amazon Web Services (AWS).

    Manoj Agarwal, senior vice president of engineering for Nutanix, said Nutanix Clusters on AWS will provide IT organizations with access to hyperconverged infrastructure (HCI) capabilities based on Nutanix virtual machine that AWS doesn’t provide today on a public cloud.

    IT organizations that already have Nutanix clusters deployed in on-premises IT environment will not have to refactor them to lift and shift them into a public cloud, he said, noting IT teams will also be able to provision Nutanix Clusters on AWS using the same Nutanix Prism management tools they currently employ in on-premises IT environments.

    IT teams will also be able to employ on AWS add-on tools from Nutanix such as Files to manage unstructured data, Calm to orchestrate applications and Era to manage databases.

    Agarwal declined to reveal whether Nutanix plans to support other public clouds. However, deploying HCI software on multiple clouds will provide IT organizations with the opportunity to deploy workloads without having to be concerned about being locked into a specific cloud service, he said.

    In the wake of the economic downturn brought on by the COVID-19 pandemic, IT teams are under even greater pressure to reduce total costs. Many IT teams prior to the pandemic managed cloud and on-premises IT environments in isolation. As part of the effort to reduce the total cost of IT, more organizations are now looking to embrace a heterogeneous hybrid cloud strategy that would enable them to manage multiple platforms via a common management plane. IT teams may not dynamically move workloads between clouds, but they will eventually move toward a common management framework that enables workloads to be more easily managed independent of the underlying IT infrastructure.

    Nutanix, of course, is not the only provider of an IT platform aiming to become the provider of that management plane. Rather than rely on separate compute and storage services, Nutanix is making the case for an HCI platform that converges the management of compute, storage and networking.

    Of course, providers of cloud service are simultaneously making available on-premises instances of cloud platforms they will manage on behalf of customers. The Nutanix approach enables IT teams to automate the building and managing of their own hybrid cloud computing environments without having to cede control to a cloud service provider, noted Agarwal.

    It’s still early days as far as hybrid cloud computing is concerned, but it’s clear that the pace at which IT teams are moving toward them will accelerate in the wake of the downturn. The issue now is determining how best to achieve that hybrid cloud goal given the relative maturity of the management frameworks that would be used to manage multiple platforms. Regardless of the path selected, however, there will eventually be one IT team to rule them all.

  • Nutanix Extends DevOps Ambitions

    Nutanix Extends DevOps Ambitions

    Nutanix at its .NEXT Europe conference has signalled its ambitions now extend into the realm of DevOps. The company announced it will make available an Acropolis Compute Cloud (AC2) and an Acropolis Object Storage Service on top of its Enterprise Cloud OS software that creates an instance of a hyperconverged infrastructure (HCI) platform that can be deployed on-premises or in a public cloud.

    In addition, Nutanix is embedding an App Marketplace in its Nutanix Calm orchestration software through which applications developed on top of Enterprise Cloud OS can be accessed.

    Finally, Nutanix has added Veritas Technologies to the list of providers of data protection software that can be employed to provide backup and recovery software for applications running on top of its core AHV hypervisor.

    Greg Smith, vice president of product marketing for Nutanix, says his company is now moving well beyond simply trying to combine compute and storage in a locally deployed appliance. It envisions organizations employing Enterprise Cloud OS to drive hybrid cloud computing applications across a consistent set of automated orchestration services based on a common platform optimized around an HCI architecture.

    HCI architectures were pioneered by cloud service providers, and Nutanix applied those concepts to local data centers in the form of an appliance. The company then took the software it developed for the appliance to create a portable cloud operating system environment it is now extending with, for example, an object service that is compatible with the S3 interface defined by Amazon Web Services (AWS).

    Smith says Nutanix is making the compute and storage services available on top of Enterprise Cloud OS as an alternative to more expensive compute services based on platforms such as VMware. Nutanix is essentially in a race against other providers of HCI software to extend the reach of its platform. VMware, for example, has made its software stack available on the IBM Cloud and similarly is working to make its software available on AWS. Smith says the Nutanix approach gives IT organizations more control over where they want to deploy HCI software on any platform, including server platforms from Cisco Systems, Dell EMC, Lenovo and Hewlett-Packard Enterprise (HPE) if they so desire. All three of those vendors also provide access to rival HCI software platforms.

    Nutanix developed its own hypervisor on which Enterprise Cloud OS is built to enable its software to be deployed on multiple platforms. But just to make things more interesting from an IT operations perspective, Nutanix also has HCI software that can be deployed on a VMware hypervisor.

    Against that backdrop, IT organizations are trying to determine the rate at which they want to replace traditional rack-based systems with HCI platforms, which combine compute and storage to reduce the total cost of operating an IT environment. Most legacy applications still expect to access external storage. But as new applications are developed, the expectation is that most of them will run on some form of an HCI platform that can scale out to support a much broader range of applications.

    It’s not likely legacy applications running on rack systems will go away anytime soon. But it is apparent that IT operations teams will be managing a mix of rack and HCI systems for years to come.

    — Mike Vizard

  • Managing Complexity in Dev/Test Infrastructure Using Machine Learning

    Managing Complexity in Dev/Test Infrastructure Using Machine Learning

    Businesses are increasingly developing software solutions that can drive innovation and digital transformation. As the number of developers increases in the organization, the ratio of developers to IT also increases over time. The net result: more dynamic and complex dev/test infrastructure requirements and slower support from IT.

    Developers and testers often cannot get their hands on infrastructure environments in a timely manner to accelerate delivery of software applications to their customers. They have to deal with lack of timely support from IT and long waits for hardware resources and for provisioning and configuring of the environments.

    How does engineering IT manage this complexity and deliver more agility to their engineering stakeholders?

    Provide Self-Service Creation of Dev/Test Sandbox Clouds

    Engineering IT teams can increase the velocity of development and testing if they enable self-service ability for dev teams to quickly provision their own lab infrastructure and application stacks at a click of a button.

    Self-service, API-driven infrastructure is a fundamental requirement for enabling developers to write code (which can be done using their favorite programming language) and make RESTful API calls to the underlying programmable infrastructure. This allows them to dynamically and automatically manage initial deployments and configurations as well as manage ongoing, automated dynamic provisioning of infrastructure, autoscaling, monitoring and alerting.

    All this automation removes the confusion and error-prone manual steps for the entire application delivery process, including development, testing, staging and production deployments. This, in turn, accelerates software delivery and increases quality.

    Additionally, if self-service is available as a SaaS-based delivery model, it is easy to add more features and workflows very quickly without having IT doing a major upgrade.

    Breaking these silos improves collaboration between teams, accelerates velocity of software development, improves infrastructure utilization, increases overall operational efficiency and reduces costs.

    Eliminating Silos in the Dev/Test Infrastructure

    Silos are common in companies where various specialist teams (storage, networking, security) form fiefdoms around their respective functional areas. Silos impede velocity because they lead to complexity of operations, lack of consistency in the environment, and lack of automation.

    Automating across silos turns into to an exercise of custom scripts and lot of “glue and duct tape,” which makes maintenance and change management complex, slow and error-prone.

    Breaking these silos improves collaboration between teams, accelerates velocity of software development, improves infrastructure utilization, increases overall operational efficiency and reduces costs.

    A hyperconverged cloud design with a software-centric, scale-out architecture tightly integrates compute, storage, networking and virtualization resources and other technologies from scratch in a commodity hardware box supported by a single vendor. Also, companies can keep costs under control by leveraging scale-out cloud designs that make it easy to start small, grow based on demand, and stay close to the right size and customer demands.

    Additionally, development teams should have the ability to quickly deploy/clone/share complex multi-tiered application stacks between various teams and between development and testing, breaking the silos within the development organization.

    Automate Operations, Monitoring and Patching

    Engineering IT teams need to have complete visibility and control of their entire stack from the infrastructure up to applications. They need intelligent software to monitor the hardware and software stack, manage large-scale clusters and automatically handle routine but time-consuming and complex operations such as failure handling, patching, security updates and software upgrades.

    Running a service with traditional sysadmin teams who execute the above activities manually becomes expensive—especially if they operate in server, storage, networking and security silos—as the dev/test environments become more dynamic and the demand for more environments and projects grows.

    However, it is possible to use an intelligent private cloud platform that leverages hyperconverged scale-out designs, machine learning software and a SaaS-based operational console to reduce complexity and increase the agility of dev/test teams.

    Cloud-based monitoring and advanced analytics dramatically reduce the need for experts in different parts of the infrastructure, scale linearly as the size of the operation increases and cut operational complexity by 90 percent.

    Manage Resource Management Using Machine Learning

    Applying machine learning to infrastructure management means intelligent software could learn about operational patterns, anticipate capacity needs, raise alerts about security anomalies, self-monitor and self-heal your environment in the face of failures, intelligently apply security patches and automatically upgrade hardware and software systems without any downtime. The next generation of infrastructure management will be driven by advances in machine learning and artificial intelligence, where the infrastructure is able to basically “drive itself” with minimal user intervention.

    This will help engineering IT teams optimize resource usage and capacity based on current and future dev/test demand and also be able to better handle the availability and performance they can deliver to their engineering teams. A lot of efficient resource management comes down to capacity planning, utilization monitoring, right-sizing of workloads, demand forecasting and detecting zombie VMs and unused resources.

    Demand forecasting and capacity planning can be viewed as ensuring there is sufficient capacity and redundancy to serve projected future demand with the required availability. Capacity planning should consider organic growth, which stems from natural service adoption and usage by dev/test teams. Having intelligent predictive analytics and machine learning can help greatly with accurate forecasting, alerting and providing lead time for acquiring additional capacity.

    Better insights into how the infrastructure is performing can also help in fine-tuning performance of end user workloads. For example, an intelligent system that is monitoring a workload for storage performance might recommend using SSDs instead of spindles to increase the IOPS and improve workload responsiveness.

    An intelligent private cloud platform that uses hyperconverged scale-out designs, machine learning software, and a SaaS-based operational console can reduce complexity and increase the agility of dev/test teams.

    About the Author / Kamesh Pemmaraju

    Kamesh Pemmaraju leads product management, product marketing, and technology partnerships at ZeroStack. Kamesh is a seasoned product management/marketing leader with a strong engineering and consulting background. In his most recent product roles at Mirantis and Dell, he focused on delivering private and hybrid cloud solutions to enterprises. He holds a Master of Science in Computer Science from Indian Institute of Science. Connect with him on LinkedIn and Twitter.

  • DevOps Needs a New Cloud Solution for Best Practices

    DevOps Needs a New Cloud Solution for Best Practices

    Imagine this scenario: You are a company building modern software which is a key driver of your business. To support this, you have grown your infrastructure organically over time by adding servers, storage, networks, security, virtualization software, monitoring, alerting and analytics tools. You have also added a plethora of other middleware, databases, messaging and operating systems that your developers need to build, test and deliver their applications.

    Because of this unplanned organic growth, there is no consistency in the environment. You manage, maintain and operate much of this environment manually. Your various specialist teams (storage, networking, security) begin to form fiefdoms around their respective functional areas. Change becomes extremely difficult and automating across silos turns into a maintenance nightmare. You over-purchase to meet the demand and risk under-utilizing resources. Your costs spiral out of control. You are now finding it a hopeless challenge to meet the needs of your developers—which was the primary purpose of doing all of this in the first place.

    Moving to a Modern Platform

    A modern DevOps platform should address the requirements of both your development and IT/operations teams. It should give software development teams an easy way to consume on-demand compute, storage and networking as well as provide easy access to continuous integration and continuous deployment (CI/CD) tooling and software services that help increase their development throughput and shorten product delivery. In addition, the platform should also empower operation teams to manage, maintain and operate the entire infrastructure environment with very few people using smart software that drives automation and intelligence into the entire stack.

    In short, it should have the ability to break the silos within your IT environment and between development, QA and operations teams. By doing this, you can increase the velocity of software development, improve infrastructure utilization, increase overall operational efficiency and reduce costs.

    Requirements for a Cloud Infrastructure That Streamlines DevOps

    There are several requirements for a modern, cloud-based DevOps platform. Let’s look at the key essentials of such a solution.

    Self-service API-driven infrastructure is a fundamental requirement to enable infrastructure as code, a key attribute to enable DevOps best practice. It allows developers to write code (which can be done using their favorite programming language) and make RESTful API calls to the underlying programmable infrastructure to manage initial deployments and configurations. It also enables them to manage ongoing automated dynamic provisioning of infrastructure, auto-scaling, monitoring and alerting.

    All this automation removes the confusion and error-prone manual steps for the entire application delivery process, including development, testing, staging and production deployments. This, in turn, accelerates software delivery and increases quality.

    However, building such a self-service API-driven infrastructure by yourself is not easy. The key component that drives up the cost is the operational complexity and the cost of experts needed to build and operate it.

    Smart software that drives intelligence into the stack. Very few solutions in the market automatically handle the full life cycle (deployment, upgrades, monitoring, alerting and ongoing resource management) of infrastructure and also allow seamless migration of workloads between private environments and public clouds. Additionally, if self-service is available as a SaaS-based delivery model, it is easy to add more features and workflows very quickly without having IT perform a major upgrade. If your solution comes with an on-premises install, ask how much work IT has to do to maintain this environment and how often new features will get added.

    Hyper-converged Infrastructure (HCI): Eliminating silos in the infrastructure. As mentioned earlier, silos impede velocity because they lead to complexity of operations, lack of consistency in the environment and lack of automation. A hyper-converged cloud design with a software-centric architecture tightly integrates compute, storage, networking and virtualization resources and other technologies from scratch in a commodity hardware box supported by a single vendor. This approach eliminates silos and lowers costs and complexity. It also makes it easy to start small and grow on demand while staying tightly right-sized on capacity and cost.

    A built-in browse-able categorized application store. DevOps engineers need readily accessible CI/CD tools such as Jenkins, Git, Maven or JUnit to automate the development and test pipelines. Additionally, tools such as Ansible, Puppet and Chef help with automated configuration and lifecycle management of workloads. Application developers need to quickly integrate and deploy middleware services such as RabbitMQ, Redis or storage back-ends including MySQL, Postgres, Cassandra or MongoDB. Single-click deployment of such services and other complex multitier network tools and applications greatly automates, accelerates and simplifies the development process.

    Seamless migration between private and public clouds. Developers and testers often need much greater capacity than is available on-premises for scale testing, and they should be able to move their application to a public cloud for such purposes. Alternatively, they may already have some applications running on a public cloud and they may want to bring them back to their private cloud for cost savings or better performance. For these use cases, a private cloud solution should offer seamless bi-directional migration between the public cloud and the private cloud.

    Dashboards and visibility for troubleshooting. One of the key advantages for a private cloud is that you can get complete visibility across the infrastructure and applications. In a public cloud, you can only get VM-level stats but have no control or visibility below that. Make sure that your private cloud solution can provide visibility to developers directly. Many vendors only provide access to IT, thereby controlling what developers can do and making IT a bottleneck in the application development and deployment process.

    Better insights to improve efficiency and capacity management. A cloud requires capacity planning, utilization monitoring, right-sizing of workloads and detecting zombie VMs and unused resources. Look for a solution that comes with built-in analytics, management tools and insights. An even better approach would be having a solution where you don’t have to install the management tool on-premises so that it can deliver its value as a service.

    To meet the needs of application developers and development frameworks and to create an efficient DevOps platform, companies should look at consistent converged architectures managed via smart software. This empowers application developers and operations teams to leverage a consumption model they want, while providing control to IT and making them relevant to your business success.

    Integrated intelligence and insights delivered as a service ensure that you never have to use spreadsheets to decide what to purchase and when. Cloud solutions with smart software ensure that you never have to make a Level 1 support call again; your management software can do that for you.

    About the Author / Kamesh Pemmaraju

    Kamesh Pemmaraju leads product management, product marketing, and technology partnerships at ZeroStack. Kamesh is a seasoned product management/marketing leader with a strong engineering and consulting background. In his most recent product roles at Mirantis and Dell, he focused on delivering private and hybrid cloud solutions to enterprises. He holds a Master of Science in Computer Science from Indian Institute of Science. Connect with him on LinkedIn and Twitter.