devopsy.kinsta.cloud

Author: Mike Vizard

  • Microsoft Revamps Approach to DevOps on Azure

    Microsoft Revamps Approach to DevOps on Azure

    Microsoft this week unfurled a broad range of DevOps services for the Azure cloud that are intended to make it easier for organizations to embrace modern application development and deployment processes.

    Jaimie Cool, director of product management for Azure DevOps, said it’s fundamentally simpler for organizations to embrace DevOps processes using tooling hosted in the cloud because they don’t have to spend time setting up the underlying infrastructure themselves. Once they master those processes in the cloud, organizations can take the tooling provided by Microsoft and extend it out to either instances of Azure running in a local data center or Windows Server platforms.

    The Azure DevOps portfolio spans Azure Pipelines, a continuous integration/continuous development (CI/CD) platform that supports any language; Azure Repos, a private repository based on Git; and Azure Test Plans, a wide range of testing tools. Azure DevOps also includes Azure Artifacts, which provides Maven, npm and NuGet package feeds from public and private sources, and Azure Boards, a suite of collaboration dashboards and reporting tools.

    Microsoft is positioning Azure DevOps as an evolution of Visual Studio Team Services (VSTS). VSTS users will be upgraded into Azure DevOps projects automatically. Organizations that are using the on-premises Team Foundation Server (TFS) component of VSTS will continue to receive updates based on features made available in Azure DevOps. TFS will be rebranded Azure DevOps Server starting with next release.

    As part of this launch Microsoft is also making Azure Pipelines available for free with unlimited minutes for 10 parallel jobs for every open source project. Major open source projects already using Azure Pipelines for CI/CD include Atom, CPython, Pipenv, Tox, Visual Studio Code and TypeScript.

    Cool said that when it comes to application development, too many organizations overlook the critical role of DevOps processes in making a project a success. There’s a tendency to focus too much on features rather than the tools that enable an organization to deliver those features consistently. DevOps processes are crucial when it comes to improving the quality of software and the velocity at which upgrades are delivered, he said.

    But the ultimate DevOps goal is to not to increase the number of releases put into production over a specific amount of time such as a week, month or quarter, he added. Rather, organizations should be able to updates to applications whenever they are ready or required.

    Cool noted there’s a high correlation between adoption of Docker containers and an appreciation of the value of DevOps. As organizations embrace microservices-based architectures based on containers, the complexity of the IT environment overall increases. That issue soon may be coming to a head for more organizations, as Microsoft is now seeing containers all over the place, he said.

    Longer term, Microsoft expects to see machine learning incorporated into DevOps processes as well, Coole said, noting that it’s still early days as far as machine learning and DevOps are concerned.

    Clearly, Microsoft is trying to provide a more sophisticated DevOps experience as part of an ongoing battle with Amazon Web Services (AWS) and other cloud service providers to attract developers to its platform. As those efforts continue to expand, the number of organizations Microsoft schools on the DevOps processes should increase correspondingly.

    — Mike Vizard

  • Atomist Advances Developer Productivity

    Atomist Advances Developer Productivity

    Atomist is extending the reach of an automated approach to managing software delivery out to the local machines developers work on every day.

    Company founder and CEO Rod Johnson said with its Software Delivery Machine (SDM) project, Atomist seeks to eliminate much of the complexity developers currently must navigate as they build code, including making changes that require updates to dependencies across projects.

    That capability makes it easier to keep multiple development projects consistent and up to date automatically, Johnson said.

    Atomist is applying many of the concepts Johnson used to create the widely employed Spring framework as an alternative to Java Enterprise Edition (J2EE), which is now being developed under the auspices of Pivotal Software, a unit of Dell Technologies. Atomist created a domain model for software delivery based on an API server and GraphQL, an open source data query and manipulation language.

    This approach eliminates the need to work within the construct of more cumbersome framework based on, for example, YAML files, Johnson said. Rather, Atomist is making use of code to develop an alternative framework that is optimized around a more familiar API construct, which frees developers to extend the SDM in any direction that best reflects how they want to work.

    Atomist currently provides a service based on SDM to large enterprises that have aggressively embraced DevOps. Johnson said that service enables organizations to allow developers a maximum amount of flexibility within the context of policies that can be defined by an IT operations team. The local instance of SDM is intended as an open source tool for increasing individual developer productivity.

    Most organizations are becoming increasingly obsessesed with developer productivity at a time when companies recognize how dependent they are on software to differentiate themselves. The rate at which new and existing applications are being rolled out and updated has expanded considerably. For developers face to rise to that challenge, many of them embraced microservices that make it easier to add and replace new functionality using Docker containers. Those microservices, however, create a massive number of dependencies across different code bases that must be tracked. SDM can be employed to not only spin up containers images and Kubernetes clusters, but also update all the interdependent microservices spanning multiple clusters.

    Asking developers to keep track of and manually update all those dependencies involving multiple projects is not the best use of their time, Johnson said. Real DevOps progress will be achieved only when organizations provide tools that make it easier for developers to do the right thing in a way that doesn’t try to impose an inflexible framework.

    Most of the processes that organizations rely on to build code today are not nearly as automated as they should be. In fact, DevOps adoption arguably would be much further along than it is today if it didn’t require so much manual effort.

    — Mike Vizard

  • WhiteHat Security Looks to AI to Advance DevSecOps

    WhiteHat Security Looks to AI to Advance DevSecOps

    WhiteHat Security is now embedding artificial intelligence (AI) into the application security review services it provides, as part of an effort to advance adoption of DevSecOps processes.

    Joseph Feiman, chief strategy officer for WhiteHat Security, said the biggest resistance factor to DevSecOps has been the amount of time it takes to test applications for vulnerabilities. By injecting machine learning into that process via a suite of WhiteHat Sentinel Dynamic tools, which are being made accessible as a software-as-a-service (SaaS) application, developers will be more inclined to conduct security reviews as part of an integrated DevSecOps process, he said.

    The AI engine identifies vulnerability patterns in a code-based data lake of 95 million identified vulnerabilities that WhiteHat Security has identified via its dynamic application testing service (DAST). WhiteHat Sentinel Dynamic identifies known vulnerabilities in seconds, Feiman said, and any anomalies indicative of potential unknown vulnerabilities are then reviewed by human WhiteHat Security cybersecurity experts.

    Feiman said DevSecOps is going through a period of disillusionment because security reviews of code are taking too long. AI technologies represent an opportunity to reignite interest in DevSecOps by giving developers more control over an application security review process that no longer slows down development.

    In addition, WhiteHat Sentinel Dynamic enables developers to learn about their potential mistakes without necessarily requiring them to disclose them to the entire DevOps team. Any humiliation a developer might experience is avoided when the developer conducts the security review prior to committing code. IT security teams are still in charge of creating the policies that need to be implemented, but processes associated with implementing those policies make a decidedly shift left to the developer, he said.

    Feiman noted that the rise of AI within DevSecOps processes may help alleviate some of the current chronic shortage of cybersecurity expertise. There will always be a need for human cybersecurity researchers to train AI models what to look for as new vulnerabilities are discovered. But algorithms never take a day off or decide to abruptly quit because they suddenly got a better offer.

    It may take a while for IT organizations to completely trust AI engines to scan code for vulnerabilities. But currently many applications are not being reviewed at all because any time set aside to conduct that reviews is being eaten up by an application development process that has fallen behind schedule. Too many developers would still prefer to take a chance on a breach than be reprimanded for delivering code late, especially when there’s a chance to address vulnerabilities that might get discovered in the next scheduled release of a patch. WhiteHat Security is making the case for eliminating much of that risk by making it feasible for developers to quietly address vulnerabilities long before an application is deployed in a production environment.

    There’s no doubt that AI soon will be employed to automate large swaths of cybersecurity. But it may turn out that the most effective place to apply AI from a cybersecurity perspective early in the DevOps process as possible.

    — Mike Vizard

  • Atlassian Acquires OpsGenie to Automate Incident Management

    Atlassian Acquires OpsGenie to Automate Incident Management

    Atlassian this week announced its plans to acquire OpsGenie as part of an effort to apply DevOps principles to incident management. The announcement was made at the Altassian Summit Europe 2018 conference.

    Atlassian plans to integrate OpsGenie, which provides incident alerting and communications software, with its Jira service desk software to enable organizations to automate responses to a major incident such as a site outage using a Jira Ops incident management command center unveiled this week.

    Jens Schumacher, head of software teams for Atlassian, said that while most organizations today have processes in place to respond to minor incidents, very few have incident management processes in place to deal with significant catastrophic events. OpsGenie already has been adopted by more than 3,000 customers to enable organizations to put together a set of structure processes to recover as quickly as possible.

    Schumacher said a more structured approach to recovery is now required because so much more of a modern organization’s ability to drive revenue is tied to the availability of IT. Whenever there is a significant amount of downtime, the urgency attached to recovery process is now much greater. The combination of OpsGenie and Jira, available now via an early access program, makes it possible to predefine a structured set of workflow processes to be followed in the event of an emergency, he said, adding that by defining those processes within a common framework, IT organizations also will be able to significantly reduce the number of point products they need to navigate during a crisis.

    The combination of the two products will also aid in applying forensics to discover the root cause of any outage, Schumacher said.

    Incident management within IT environments over the last few years has been evolving into a science. There are several dedicated incident management platforms that mange everything from who needs to be alerted in what order to providing detailed instructions bringing applications back online. The challenge many organizations wrestle with today is that all the silos of IT make it difficult to approach incident management comprehensively.

    But as it becomes easier for finance officers to draw a straight line between IT downtime and lost revenues, interest in more structured approaches to recovery is on the rise. In fact, regardless of whether the root cause of an issue is a cybersecurity breach or a geological event, the recovery process is usually consistent. Incident management platforms provide the means to capture those processes in a way that creates institutional memory. Access to those best practices is often critical, because organizations can never be sure which members of the IT staff will be available during a crisis. If the one person who knows how to provision a storage system is unavailable, there should be enough information in an incident management system to enable another member of the IT team to accomplish that task.

    As is often the case when it comes to IT, the tools at hand only enables the battle to be joined. It’s the quality of the processes attached to those tools that decides whether the battle will be won or lost.

    — Mike Vizard

  • Open Mainframe Project Launches Zowe to Advance DevOps

    Open Mainframe Project Launches Zowe to Advance DevOps

    The Open Mainframe Project has launched Zowe, an effort to make mainframes running z/OS both more accessible and programmable using REST application programming interfaces (APIs).

    Announced at the Open Source Summit, the Zowe project is being led by IBM, CA Technologies and Rocket Software.

    Matt Hogstrom, chief architect for z/OS Systems at IBM, said the goal of the Zowe project is to attract a new generation of IT administrators to the mainframe platforms and make it simpler to include mainframes within the larger scope of an integrated set of DevOps process spanning multiple platforms.

    In addition, IBM, CA Technologies and Rocket Software collectively are trying to create an ecosystem around the mainframe that resembles more of the types of interactions that occur between companies that participate in the Linux community, Hogstrom said. The Open Mainframe Project operates under the auspices of the Linux Foundation.

    Now that IBM mainframes are more than 50 years old, IBM and its allies are increasingly relying on open source tools to make sure mainframes stay relevant for another 50 years, he said.

    To achieve that goal, Zowe provides access to an extensible z/OS framework that provides new APIs and z/OS REST services. The Open Mainframe Project, as part of Zowe, has also created a unifying workspace based on a desktop app container accessed via a browser and a scriptable command line interface (CLI) that makes it easier to integrate z/OS into cloud and distributed environments using a set of low-code tools.

    Greg Lotko, General Manager for Mainframe at CA Technologies, said the contributions to the Zowe Project made by CA Technologies are based on CA Brightside, a set of DevOps tools developed specifically for mainframe environments.

    The biggest challenge the mainframe community now faces is a dwindling pool of talent. Most college graduates today have limited exposure to mainframes at a time when many of the IT professionals who do have mainframe skills are retiring. In the absence of skills to manage mainframes, IT organizations wind up making decisions regarding where to put workloads based on the availability of expertise available to run those platforms. IBM, CA Technologies and Rocket Software all have a vested interest in leveraging DevOps tools and processes to eliminate the silo that currently exists between mainframes and other platforms by making it easier to call services residing on a mainframe using REST APIs, while at the same time making it easier to manage mainframes within the context of a common set of DevOps processes spanning multiple platforms.

    Mainframes, of course, are still comparatively expensive platforms to acquire. IBM has sharply reduced the cost of mainframes over the years. But the primary economic value proposition of mainframes is that the total cost of operating a mainframe is less than a distributing computing environment running a comparable set of workloads. Mainframes are highly automated, so IT organizations that can afford the cost of entry tend to still favor mainframes for complex transaction processing and analytics applications. The challenge—and opportunity—for mainframe shops now is in turning those applications into a set of reusable services that can be readily invoked from anywhere in the enterprise.

    — Mike Vizard

  • Moogsoft Extends AI Reach into IT Operations

    Moogsoft Extends AI Reach into IT Operations

    Moogsoft, at a Moogsoft 2018 AIOps Symposium last week, extended the reach of its IT operations analytics software out to where applications are deployed, rather than requiring data to be moved into a Big Data platform.

    Will Cappelli, CTO and vice president of product strategy for Moogsoft, said Moogsoft Observe, available in beta, discovers anomalies by applying algorithms where data is generated, versus requiring IT organizations go to the trouble and expense of moving massive amounts of data into a central data lake.

    Moogsoft Observe ingests time-series and metrics data in real-time and then applies artificial intelligence (AI) to detect incidents at the source of the problem. The single-agent technology can deployed anywhere, including cloud instances and on-premises systems and applications running containers and virtual machines.

    Cappelli noted Moogsoft Observe doesn’t require data scientists to configure it. IT generalists can employ Moogsoft Observe on their own without having to rely on a centrally managed IT operations analytics platform managed by someone else. Moogsoft claims this approach reduces the time to detect a problem by up to 60 percent while cutting nearly 90 percent of the storage and communication costs.

    Analytics generated by Moogsoft Observe can then be stored in the Moogsoft AIOps platform to enable IT organizations to run additional analysis against data collected from multiple data sources.

    Moogsoft also announced that version 7.0 of the Moogsoft AIOps platform will be available this October. This update adds Vertex Entropy and Situation Topology Visualization, algorithms that enable IT teams to visualize the root cause of an issue via a system topology map. That capability makes it possible to apply algorithms capable of generating contextual analysis that pinpoints the source of issues rather than generating a series of probabilities based on when a set of events occurred, said Cappelli.

    Advances in how AI can be applied to automate IT operations are now coming at a rapid rate. Those advances increasingly are becoming affordable for the average IT organization to employ. Most IT teams spend more time trying to determine the source of problem than they do fixing it once the root cause is discovered. AI technologies promise to eliminate many of the rote tasks that IT administrators are required to manually perform time and again, which will make it simpler to manage IT at scale. It also means more IT teams can expect to not have work as many odd hours of the day because fewer things are likely to go wrong. There may never be a perfect IT environment. But IT environments should be a lot more predictably reliable.

    Of course, the rise of AI undoubtedly will have a significant impact on the IT staff. Many IT administrators will need to be retrained as more processes become automated. It’s not likely the need for IT administrators will go away anytime soon. But as some tasks become automated, many entry-level IT roles will change dramatically or, in some cases, be eliminated. At this point, those changes are now all but inevitable.

    — Mike Vizard

  • VMware Looks to ‘Ruthlessly’ Automate IT

    VMware Looks to ‘Ruthlessly’ Automate IT

    VMware, at VMworld 2018 this week, advanced an ambitious campaign to automate IT management by announcing a deal to acquire CloudHealth Technologies and then previewing a Project Magna initiative that employs machine learning algorithms and other forms of artificial intelligence (AI) to create what VMware describes as self-driven data centers.

    VMware CEO Pat Gelsinger told conference attendees that, as part of achieving that goal in the era of the cloud, every aspect of IT now needs to be automated.

    “The rule of the cloud is to ruthlessly automate everything,” he said.

    Project Magna represents an effort to centralize AI research and development to enable IT organizations to reallocate resources to building applications by eliminating many of the manual tasks that conspire to make IT inflexible.

    At the same time, increased levels of automation will serve to reduce the cost of labor associated with managing IT, which remains the single highest cost within most IT budgets. Without increased levels of automation, those costs inevitably will rise as IT organizations embrace not only public clouds but also emerging new platforms such as Kubernetes.

    Gelsinger this week made it clear VMware views being able to automate the management of Kubernetes as an opportunity to expand the reach and scope of its management offerings.

    The addition of CloudHealth Technologies to the VMware portfolio adds a cloud operations platform that spans Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP). Once the acquisition is formally closed, VMware has pledged to integrate its cloud automation services, Secure State and Wavefront cloud services with the CloudHealth platform. The CloudHealth platform will be rebranded VMware Cloud Operations. Those moves come on the heels of a significant expansion of the portfolio of DevOps tools the company also announced this week.

    VMware also revealed its is working on the Dimension project with Dell EMC and Lenovo, which will create a hyperconverged architecture optimized for deployment at the network edge. Project Dimension will make use of VMware NSX network virtualization software and the software-defined wide area networking (SD-WAN) platform gained by the company’s acquisition of VeloCloud to connect servers running at the network edge. That initiative complements the existing Pulse project for managing internet of things (IoT) devices, for which VMware announced REST application programming interface (API) support and which will be available as an on-premises or a software-as-a-service (SaaS) application.

    VMware this week also unveiled updates to updates to its vRealize automation portfolio that enable organizations to rightsize workflows and automate host-based placement of those workloads. The core vRealize Automation platform also sports a new user interface and integration with open source Ansible Tower automation software and integration with Pivotal Container Service (PKS), an instance of Kubernetes. Version 7.5 of vRealize Automation 7.5 also features enhanced AWS and Azure support.

    It’s unclear to what degree increased automation will transform how IT is managed within the context of modern DevOps processes. But the one thing that is clear is the economics of IT are being altered. Via automation VMware is sharply reducing the need for IT specialists in favor of “super” administrators capable of managing compute, storage, networking and security at unprecedented levels of scale in a much more integrated fashion. How much of that will be accomplished by AI is still anyone’s guess. But it’s already clear the job of the average IT administrator will soon be transformed utterly.

    — Mike Vizard

  • Mirantis Modeling Tool Extends SDI Scope and Reach

    Mirantis Modeling Tool Extends SDI Scope and Reach

    Mirantis has added a modeling tool to its portfolio that enables users to allocate IT infrastructure that has been distributed across multiple data centers to a common set of workloads.

    Company CEO Adrian Ionel said the latest edition of the Mirantis Cloud Platform (MCP) for building provide clouds on OpenStack or Kubernetes platforms now includes a Mirantis Infrastructure Model Designer tool that makes it possible to manage IT infrastructure residing in multiple data centers as though they were one logical resource. In effect, slices of distributed data centers can be allocated to run specific classes of application workloads, he said.

    The Mirantis tool is based on open source software spanning Cookiecutter, Reclass and Salt projects that Mirantis is employing to enable users to apply management templates across multiple distributed data centers. The goal is to make it possible for IT organizations to employ a software-defined framework that makes it easier to not only manage distributed IT environments, but also change the configuration of those environments as the nature of application workloads change over time, Ionel said.

    The Mirantis modeling tool provides a declarative approach to managing software-defined infrastructure that doesn’t require IT operations teams to learn how to program, he added.

    Ionel said that as IT organizations invest in IT infrastructure, they need to deploy multiple classes of application workloads on the same systems. Each of those application workloads has distinctly different attributes and requirements. For example, a big data application running on Hadoop today has different infrastructure requirements than an analytics application infused with machine learning data that might be deployed tomorrow. That said, most IT organizations won’t be able to replace IT infrastructure as application workloads evolve, he said, noting the Mirantis tool provides a means to easily reconfigure IT infrastructure from a central location without requiring IT personnel to be present in each local data center.

    Virtualization of servers and now storage and networks is a concept that has now permeated data centers for decades. Mirantis is effectively taking that concept to its next logical conclusion by making it possible to maximize utilization of data centers. In fact, Ionel noted, templates can be configured to prioritize the running of different workloads on the same infrastructure.

    As software-defined infrastructure (SDI) continues to mature, it’s becoming apparent that data centers soon will be managed at much higher levels of abstractions than they typically are today. Instead of trying to navigate individual compute, storage and networking silos, IT organizations will be able to manage data center resources on demand. The implications of the level of automation go well beyond simply enabling IT organizations to be more agile—the entire organizational structure of IT organizations will need to evolve.

    Obviously, organizations that have embraced DevOps are further down than the SDI path than most. But as SDI continues to be able to automate IT infrastructure at levels of unprecedented scale, it’s clear there’s still a long road ahead in terms of how just how extended those DevOps processes can become.

    — Mike Vizard

  • VMware Extends DevOps Reach via SaaS Apps

    VMware Extends DevOps Reach via SaaS Apps

    VMware, at the VMworld 2018 conference today, announced it will be delving deeper in the realm of DevOps with the launch of a continuous delivery pipeline dubbed Code Stream.

    In addition, VMware announced Cloud Assembly, a set of declarative tools that enable IT organizations to spin up a cloud in as little as 10 minutes by managing infrastructure as code, and Service Broker, a catalog through which services residing on multiple clouds can be published, governed and secured.

    Milin Desai, vice president and general manager for the Cloud Services Business Unit of VMware, said these offerings extend the reach of VMware’s Cloud Automation Services that are all invoked as software-as-a-service (SaaS) applications.

    VMware also today announced a beta release of Secure State, a set of tools for tracking security alerts across Amazon Web Services (AWS) and Microsoft Azure that also can be used to investigate when changes to those environments were made. Secure Slate is based on the technology the company gained by acquiring CloudCoreo earlier this year. What’s more, VMware is updating the Wavefront by VMware monitoring service to add support for deeper support for containerized workloads running on Pivotal Kubernetes Service (PKS). Wavefront also now supports the Amazon Lambda serverless computing framework made available by Amazon Web Services (AWS).

    Code Stream is designed to track code across multiple platforms and comes with pre-built plug-ins for Wavefront, Harbor, Nexus, Pivotal Kubernetes Service (PKS), Ansible and Slack. VMware is also committed to providing integrations with continuous integration/continuous deployment (CI/CD) platforms such as Jenkins, Desai said.

    VMware has previously made extensive investments in software-defined data centers (SDDCs) based on a layer of management software deployed on top of VMware vSphere. As part of that effort, VMware today announced version 6.7 of VMware vSphere, which adds tools for verifying the state of a virtual machine, and a new Platinum edition of the platform that includes VMware AppDefense, to secure application workloads running on VMware vSphere.

    Beyond the virtual machine level, the scope of VMware’s DevOps portfolio has been limited. By adding a range of DevOps tools that are made available as SaaS applications, VMware now can provide tools spanning just about everything, from cloud orchestration to code delivery, Desai said.

    The expanded push into DevOps comes at a time when VMware is also extending the scope of its alliance with AWS. The company earlier this week announced it has lowered the cost of entry of VMware for AWS by 50 percent for a limited time and is making available a three-node configuration option. Previously, VMware required customers to set up a minimum four-node configuration. VMware will enable IT organizations to configure a three-host software-defined data center (SDDC) for the cost of two hosts.

    The company is further helping to reduce costs by make it possible for IT organizations to also specify the number of processor core counts for Oracle and Microsoft applications running on AWS, along with new options for deploying NSX network virtualization software.

    It’s unclear to what degree VMware will be able to leverage its historic strengths in server virtualization to become a significant force in the realm of DevOps. The acquisition of Wavefront in last year was clearly a significant step in that direction. But the individuals with an IT organization who decide what virtual machines to employ are not necessarily the same individuals selecting DevOps tools. VMware is clearly hoping that as more IT organizations embrace DevOps processes spanning multiple clouds, many more of them will view the company’s growing portfolio of SaaS applications as a natural extension.

    — Mike Vizard

  • Red Hat Takes Virtualization Aim at VMware

    Red Hat Takes Virtualization Aim at VMware

    Red Hat, as part of on going drive to wean enterprise IT organizations off proprietary virtualization technologies, today launched a set of Red Hat infrastructure migration tools and services.

    Joe Fernandes, vice president of cloud platforms products at Red Hat, said that as organizations move to modernize their application environments by lifting and shifting them to the cloud, they are simultaneously looking to take greater advantage of open source virtual machines and containers specifically as an alternative to VMware.

    The Red Hat initiative includes a consulting engagement as well as a pilot project that enables legacy application workloads to be deployed on kernel-based virtual machines (KVMs), an instance of OpenStack or the Red Hat OpenShift platform based on the open source Kubernetes container orchestration software. The core tool used to migrate those workloads is the Red Hat Ansible Automation, Fernandes said.

    As management software stack the company now provides on top of those foundations has matured, Red Hat is finding more customers willing to consider transitioning away from commercial virtualization software, he noted. At the same time, he added, wider adoption of KVM by cloud service providers (CSPs) is making open source technologies a much more attractive option to foster deployment of application workloads across a hybrid cloud computing environment without having to refactor them.

    Those two trends in combination, Fernandes said, are making it easier for Red Hat to make a case for organizations to move way from VMware.

    Red Hat may have lost the virtual machine wars to VMware early on, but it’s clear the company is gearing up for a new phase. Many organizations have adopted an open source-first philosophy that Red Hat clearly is trying to exploit at VMware’s expense. At the same time, rising interest in alternative approaches to virtualization in the form of Docker containers and Kubernetes is creating another wedge that Red Hat is looking to exploit. For example, the company is testing Kube-Virt, an open source project that makes it possible to run KMVs within a container. Red Hat has already signaled its intention to apply that technology to other hypervisors as well.

    It’s unclear to what degree containers and Kubernetes will be deployed on virtual machines and used in place of virtual machines altogether. Red Hat is prepared for either eventually, but Fernandes said virtual machines will continue to remain relevant in enterprise IT environments for many years to come. Reliance on container and virtual machines will come down to both the nature of the application workload and the relative cloud-native maturity of the organization deploying them, he said.

    It also remains to be seen the degree to which VMware can stave off a new virtualization challenge from Red Hat. VMware has allied with Amazon Web Services and IBM in the public cloud, while partnering with sister company Pivotal to embrace Kubernetes running on top of VMware. The issue, of course, will be how much enterprise IT organizations are willing to pay for commercial virtual machine licenses in support of the initiatives.

    — Mike Vizard