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  • The Great CentOS Linux Migration: How We Got Here and What’s Next

    The Great CentOS Linux Migration: How We Got Here and What’s Next

    The recent news regarding Red Hat’s decision to limit access to the source code of their Red Hat Enterprise Linux (RHEL) distribution has garnered considerable attention. In order to understand the ramifications and subsequent changes, it is important to look back at CentOS, its historical alignment with RHEL and the options moving forward.

    CentOS Then and Now

    Starting in 2004, right from its inception, every iteration of the commercial RHEL offering triggered a corresponding release of CentOS. These iterations mirrored RHEL, albeit with modifications to eliminate the Red Hat branding and other minor updates. The presence of open source CentOS Linux facilitated swift installation of a free RHEL variant, rendering it accessible for diverse purposes spanning from development to production environments.

    In January 2014, Red Hat joined the CentOS project. Under a new CentOS governing board, they became the main sponsor and driver of the CentOS project. They continued to be an open source downstream alternative to RHEL.

    On December 8, 2020, the CentOS project and Red Hat set a new end-of-life (EOL) date for CentOS Linux 8. They shifted focus and investment into a new Linux distribution, CentOS Stream, with a rolling release model. EOL means that the community stops releases regardless of the severity of a bug or a vulnerability. Today, CentOS versions 6 and 8 are already EOL, and version 7 is the last, with EOL set for June 30, 2024. This announcement immediately sparked new projects to fill the CentOS gap. New open source projects such as Rocky Linux and AlmaLinux took off quickly, gaining contributors, sponsors and users.

    Fast forward to June 21, 2023, when Red Hat announced it would no longer publicly publish RHEL on git.centos.org.

    Previously, the source code was accessible to all, and it was used by various RHEL-compatible alternative open source projects such as Rocky Linux and AlmaLinux. It also affected other distributions, including Oracle Linux, which was a RHEL derivative for many years. All of these open source Linux distributions offered an alternative for applications; they were equally compatible with both free open source Linux and the commercial RHEL offering.

    According to the 2023 State of Open Source Report, 15% of all organizations and 20% of large organizations globally still have CentOS Linux deployed in their environments. Organizations have to move off EOL CentOS 6 and 8 and, in less than a year, off CentOS 7. Running EOL versions of any software can pose a substantial risk and cause failure in IT internal and external compliance. New vulnerabilities are constantly disclosed, and without updates or patches to CentOS, it is critical to plan for the “Great CentOS Linux Migration.”

    CentOS Migration Planning and Challenges

    Migration can be challenging. If organizations have legacy applications, they might encounter significant challenges making them work properly on a different Linux distribution. Even a small change in the individual packages that form the Linux distribution can impact and delay testing. While every application is different, and many are not dependent on low-level Linux functions, others could be significantly impacted. The number of CentOS deployments and applications has an exponential impact on the migration efforts. Evaluating different Linux distributions also takes time and will depend on the use cases, the skills developers have within each organization and the results of testing. The actual installation of a new Linux distribution is the easy part—the testing of all the layers on top of the operating system is what will take time. Some might be straightforward while others will require significant changes. Those are the reasons why it is helpful to stay with compatible distributions that will minimize the migration challenges.

    As organizations navigate the CentOS EOL and the migration period, it will be helpful to find options to extend CentOS long-term support. This means finding the expertise to generate patches that address newly disclosed high-severity vulnerabilities post-EOL. In other words, organizations must expand the community’s long-term support to address security.

    Wait for What’s Next

    The biggest question about alternative distributions is how closely they resemble RHEL. Are they going to continue to be bug-for-bug compatible? Or are there enough differences to no longer consider them application-compatible? The Rocky Linux Enterprise Software Foundation announced its plan to access RHEL source code and its intentions to continue to be bug-for-bug compatible. AlmaLinux OS Foundation announced a different approach. It is working with the CentOS Stream community while maintaining binary compatibility. This means not strictly bug-for-bug but focusing on applications to continue to be compatible.

    It is possible we’ll see other potential changes from Red Hat with regard to the access to RHEL’s source code. Today, it’s only available to customers under a commercial license agreement.

    The big test will be the next minor version, RHEL 9.3. It will be interesting to review the corresponding 9.3 versions of Rocky Linux, AlmaLinux, Oracle and others, including SUSE, who announced their intention to offer an open source compatible Linux distribution. The analysis and comparison of how applications run with the new minor version will reveal how close they are to RHEL.

    To mitigate uneasiness, organizations have to plan and test alternatives. Finding post-EOL support and patches will allow organizations to have a runway for migrating CentOS to different Linux distributions.

    As everyone in the industry with CentOS deployments waits for the next release or the next few releases, extending long-term support becomes a very viable solution. It is wise to make sure security and IT compliance aspects are addressed. Perhaps more open source Linux distributions will appear in the near future and offer another alternative to CentOS Linux.

  • Forking RHEL! Oracle and SUSE Join the Fight ¦ Silverman Sues AI Firms

    Forking RHEL! Oracle and SUSE Join the Fight ¦ Silverman Sues AI Firms

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: SUSE announces a Red Hat Enterprise Linux fork after Oracle said a similar thing, and Sarah Silverman says OpenAI and Meta have stolen her words. (more…)

  • IBM/Red Hat Sparks Anger at GPL ‘breach’ as RHEL Source Locked Up

    IBM/Red Hat Sparks Anger at GPL ‘breach’ as RHEL Source Locked Up

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: Red Hat Enterprise Linux (RHEL) goes closed source. Well—no, not really; but IBM’s lawyers are accused of skating so close to the edge of legality that they risk violating the GNU Public License. (more…)

  • Supercharging Ansible Automation With AI

    Supercharging Ansible Automation With AI

    Whether the latest incarnations of generative AI will live up to their seemingly great promise remains to be seen. This does not always happen with new technology, but the torrent of AI advancements is promising disruption across nearly every industry. Instead of posing a threat to human roles, AI now aims to make tasks easier, faster and more efficient. “This is precisely what we have been trying to achieve with Ansible and automation through generative AI models,” according to Richard Henshall, senior manager of Ansible Product Management at Red Hat. “At the end of the day, AI is another form of automation, and while we do not have thinking computers yet, we do have highly advanced and powerful models that can automate access to data.”

    Case for Integration

    Picture two scenarios: Consider a user who is already skilled in using Ansible. Their limitation is often the amount of time it takes to find the right way to do something, as Ansible is very broad and encompasses many different technologies. The user may be an expert in one or a few of these technologies, but not all of them. In this case, AI can act as an assistant, helping the user find answers more quickly and efficiently. For example, if they want to automate something in AWS, the AI can help them find the necessary resources, and the user can then tweak and curate the automation to create a final product that can be distributed to a large number of people. “This essentially superpowers the individual user,” said Henshall.

    Another type of user may not know how to automate, but they do know how to use a specific technology. “They may not automate that technology because it’s difficult for them to learn something new,” Henshall added. “AI capabilities can help these users get started with automation more quickly, enabling more people to write automation and manage both new and existing technologies.”

    In both cases, the purpose of automation is to help users solve problems. AI serves as an accelerator for these capabilities. “Once users have created automation, the AI model can be trained on the organization’s DNA, including best practices, security posture, policies and enforcement points,” Henshall asserted. This allows the AI to become a co-worker, empowering users and helping them maintain and manage their technologies more effectively.

    “As the AI model learns from the organization and its users, it can help train junior engineers, who will eventually become senior engineers, continuing the cycle of knowledge transfer and improvement,” Henshall predicted. “In this way, generative AI technologies can be integrated into the Ansible ecosystem, benefiting users and organizations in a wide range of contexts.”

    Solving Problems With AI

    As the DevOps leader of cloud testing organization LambdaTest, Shahid Ali Khan has led the company through open-source engagements and investments in next-generation automation solutions, addressing key challenges with Ansible. “We are dealing with a very large scale inventory in terms of geologically separated data centers and multiple OS. Managing this inventory on the basis of these characteristics becomes a hefty task and requires continuous efforts from the team,” he said. “With AI, Ansible can analyze the inventory and automatically group the hosts based on their characteristics, such as their operating system or their geographical location. This makes it easier to manage the inventory and apply changes across multiple hosts at once.”

    Khan also highlights the issue of auto-healing in the industry. “Auto-healing has always been a problem, and while tools in the market have somewhat addressed it, they still require defining errors and categorizing fixes,” he said. “With current AI technology in place, Ansible can detect and automatically fix issues on the basis of historic data in the inventory without the need for manual intervention, reducing the risk of human error.”

    “Inventory forecasting has always been a pain in order to calculate how much inventory we will need based on usage and on what fronts like location and OS we need to scale,” Khan shared. “AI here with Ansible can help detect the usage and forecast based on exact demand.”

    Benefits and Challenges for the Ansible Community

    In the Ansible community, which consists of people who want to solve problems, the benefits and challenges of AI-driven automation are similar to those faced by individuals in their jobs, just on a different scale.

    Community members want to see how generative AI can help them accomplish more tasks, whether or not they are part of an enterprise. Having access to a community model allows them to contribute to training the AI, ensuring its usefulness, as they may eventually work in an enterprise setting during their careers. “The access to community services enables them to take advantage of the benefits offered by AI-driven automation,” Henshall remarked. “It is a mutually beneficial relationship between the community and AI-driven automation.”

  • Red Hat Enhances Insights to Simplify RHEL Management

    Red Hat Enhances Insights to Simplify RHEL Management

    This week at its Red Hat Summit event, Red Hat introduced an expanded set of capabilities to Red Hat Insights that simplify management of Red Hat Enterprise Linux (RHEL).

    Managing Linux across the hybrid cloud is complex, and it’s made even more so because of current macroeconomic conditions and the challenge of finding and retaining highly skilled DevOps and IT professionals, said Gunnar Hellekson, vice president and general manager, Red Hat Enterprise Linux, Red Hat.

    The enhanced Insights capabilities add a layer of abstraction to help reduce enterprise Linux complexity across the hybrid cloud and make RHEL management easier by lowering skill level requirements for managing Linux server estates, the company said.

    Using a single UI, entry-level systems administrators and IT support teams can access Red Hat Insights’ predictive analytics to identify potential bugs, misconfigurations or security vulnerabilities and remediate them. Systems administrators of all skill levels can detect, assess and push fixes for potential problems without a deep understanding of Linux management systems like Red Hat Satellite Server and without having to interact with the command line, the company said.

    These enhancements help organizations maintain services and systems even in uncertain macroeconomic times when hiring is constrained. Red Hat research also claimed that these enhanced capabilities enabled IT organizations to find IT issues up to 90% faster and remediate them nearly 66% faster across the hybrid cloud.

    A Red Hat Insights image builder service also helps lower the skills level needed to manage Linux estates by enabling IT teams to build standardized, optimized operating system images, including the creation of their own ‘golden images’ that adhere to organization-specific needs for security and compliance. These images can be deployed across public clouds, hybrid clouds, data centers and the edge using the same console.

    As the economic downturn continues, organizations are looking to do more with less and identify ways to make the most of the resources, talent and skillsets they already have. Red Hat is making the case for adding a layer of abstraction to allow less-highly-skilled IT and DevOps team members to contribute to managing Linux estates across hybrid, multi-cloud and edge deployments.

    “The demands of managing Linux across the hybrid cloud are stretching the ability of resource-constrained IT departments to keep pace,” said Hellekson in a statement. “CIOs need to be able to extend existing skillsets and lower the skill barriers for overseeing Linux estates, which is exactly what the management capabilities of Red Hat Insights are designed to do.”

  • Red Hat Unveils Developer Hub to Boost Dev Productivity

    Red Hat Unveils Developer Hub to Boost Dev Productivity

    At its Red Hat Summit conference today, Red Hat unveiled its Red Hat Developer Hub, a developer portal that provides access to an opinionated set of development tools based on the open source Backstage project.

    The portal pulls together a set of curated tools and resources so that developers encounter less friction and avoid the complexity of numerous optional tools that span disparate vendors. The goal is to increase developer productivity while reducing the volume of optional tools and information that must be sifted through to actually deliver production code.

    Red Hat Developer Hub aims to streamline the development process and allow organizations to maximize existing resources and developer skills while reducing sprawl, said Chris Wright, CTO and SVP for global engineering at Red Hat. This will help organizations maintain application development velocity and drive a consistent user experience for developers based on tools and skills they’re already familiar with, Wright told attendees.

    Rather than building and maintaining their own internal developer portal, Red Hat is making a case for using Developer Hub to deliver a platform approach to addressing the complexity and sprawl DevOps teams face. Red Hat Developer Hub is, in essence, an opinionated and optimized version of Backstage that aims to deliver improved developer experiences across environments, including Kubernetes and container application platforms such as Red Hat OpenShift.

    Developer Hub will offer a single pane of glass to view all available developer tools and resources, developer self-service capabilities and security and compliance guardrails for cloud-native application development that comply with enterprise-wide best practices, according to the company.

    Additionally, Red Hat Developer Hub includes a set of ‘golden path’ templates—pre-defined, pre-architected and supported templates for further accelerating application development.

    The developer hub is based on the Cloud Native Computing Foundation (CNCF) incubating open source project Backstage, originally developed by Spotify and donated to the CNCF in 2020. Backstage is now being advanced by contributions from multiple vendors, including Red Hat.

    Backstage has been gaining traction in cloud-native application environments that are especially challenging to develop using multiple tools. There’s a lot more focus on developer productivity, which Backstage addresses by creating a catalog of blueprints that developers can readily consume rather than requiring them to build these capabilities themselves multiple times over. The goal is to create scaffolds that developers can consistently reuse across multiple application development projects.

    Red Hat has also developed Red Hat Plug-ins for Backstage, a bundle of six plug-ins that integrate various key systems into Backstage, helping to extend the project’s functionality, ensure a consistent user experience and improve workflow efficiency. The plugins can be used across all Backstage installations, providing even more flexibility for developers across platforms and Kubernetes distributions and include:

    • Application Topology for Kubernetes, which enables developers to visualize real-time status of application and infrastructure workloads deployed to any Kubernetes target, including Red Hat OpenShift, with greater consistency.
    • Multi-Cluster View with Open Cluster Manager (OCM), which provides a view into clusters from Open Cluster Manager’s MultiClusterHub and MultiCluster Engine in Backstage.
    • Container Image Registry for Quay, which improves the integration and speed of interactions with Quay registries by providing a view into container image details. This includes security vulnerabilities (CVEs) associated with deployed images.
    • Pipelines with Tekton, which gives users a view into the details of all Tekton pipeline runs and their respective statuses across all services.
    • Authentication and Authorization with Keycloak, which enables platform engineers to load users and groups from Keycloak into Backstage, allowing the use of multiple authentication providers to be applied to Backstage entities.
    • GitOps with Argo CD, which helps track the health and status of the Argo CD status for services within Backstage.

    Red Hat said additional plugins are in the works. Red Hat Developer Hub will be generally available later this year, but Red Hat is offering a ‘test drive’ through the upstream IDP project Janus.

     

  • Red Hat Adds Generative AI and Event-Driven Capabilities to Ansible

    Red Hat Adds Generative AI and Event-Driven Capabilities to Ansible

    Red Hat today unveiled a technical preview of Ansible Lightspeed with IBM Watson Code Assistant, a generative artificial intelligence (AI) service specifically trained on domain-specific data collected via the Ansible automation platform.

    At the same time, Red Hat is also making available an event-driven capability within version 2.4 of the Ansible platform that enables runbooks and other tasks to automatically execute when received from a third-party tool or application.

    Both capabilities were announced at the Red Hat Summit and are part of an ongoing Red Hat effort to democratize IT automation.

    First previewed within the Project Wisdom initiative launched by Red Hat and IBM Research last year, Ansible Lightspeed IBM Watson Code Assistant is based on a large language model (LLM) that was developed using Ansible data. Watson Code Assistant, currently in technical preview, is a service that automatically generates suggestions to improve code as developers create an application. IBM promised to make IBM Watson Code Assistant available later this year.

    Red Hat is now applying that generative AI capability to the YAML code that DevOps teams need to create Ansible playbooks. IT teams can create a simple natural language prompt that will translate their domain expertise into YAML code for creating or editing Ansible Playbooks. Red Hat and IBM, however, will not automatically use the code from an organization to fine-tune their AI model without express consent.

    Rich Henshall, director of product management for Red Hat Ansible, said as IT environments become more complex, it’s clear many are hitting a ceiling in terms of what can be automated using legacy custom scripts. Ansible Lightspeed IBM Watson Code Assistant, along with an event-driven capability, will make it much simpler to automate the management of IT environments at scale using a declarative framework, he added.

    Ansible, for example, can now receive events from third-party tools, determine next steps and consistently initiate an automated response using Ansible playbooks. Ansible can also consume events from third-party monitoring, observability and IT analytics tools from providers such as Cisco ThousandEyes, CyberArk, Dynatrace, F5, IBM Instana, IBM Turbonomic, Palo Alto Networks and Zabbix with more to come, noted Henshall. Red Hat is also making available supplementary content for Red Hat OpenShift, Red Hat Insights, Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform and ServiceNow, in addition to enabling IT teams to create their own custom integrations.

    At this juncture, it’s not clear why more IT processes have not been automated using Ansible or other frameworks. Many DevOps teams continue to rely on custom scripts that typically don’t scale and are generally poorly documented. Any time the individual who wrote those scripts leaves an organization, it’s incredibly difficult—if not impossible—for the original scripts to be maintained, noted Henshall.

    One way or another, it’s clear that a more scalable approach to IT automation is required, especially with the rise of more complex cloud-native application environments. It’s no longer economically viable for most organizations to rely on legacy processes that require a small army of IT professionals to maintain.

  • Red Hat Moves to Secure Software Supply Chains

    Red Hat Moves to Secure Software Supply Chains

    Red Hat today announced a portfolio of cloud services designed to better secure software supply chains. The expanded portfolio includes Red Hat Trusted Application Pipeline to secure continuous integration/continuous delivery (CI/CD) workflows and Red Hat Trusted Content offerings to better secure software components.

    Announced at the Red Hat Summit, the Red Hat Trusted Software Supply Chain combines a suite of curated open source tools into a cloud service managed by Red Hat. The Red Hat Trusted Application Pipeline service is based on sigstore, an emerging de facto standard for cryptographically signing code to ensure immutability that Red Hat helped drive, while Red Hat Trusted Content provides access to a set of software components that Red Hat has vetted.

    Red Hat Trusted Software Supply Chain also provides access to existing tools such as Quay, a registry for containers, and the Advanced Cluster Security (ACS) platform for securing Kubernetes clusters.

    Red Hat Trusted Software Supply Chain is scheduled to be made available in preview in the next few weeks, and will also track the provenance of components. In addition, the service will monitor emerging threats to software components and alert users of new and emerging risks. The service will also surface recommendations for remediating vulnerabilities it identifies based on best practices defined by Red Hat.

    Finally, Red Hat Trusted Application Pipeline also promises to make it simpler to automate the deployment of secure code with a few clicks within the context of an integrated continuous integration/continuous delivery (CI/CD) pipeline. DevOps team can also import Git repositories and configure container-native continuous build, test and deployment pipelines, inspect source code and transitive dependencies, autogenerate software bill of materials (SBOMs) within builds and verify and promote container images. An enterprise contract policy engine can consistently enforce compliance with the Supply Chain Levels for Software Artifacts (SLSA) framework.

    Finding ways to implement DevSecOps workflows is a major challenge for any organization. Red Hat is making a case for a managed cloud service based on a collection of security software and services that a DevOps team would otherwise have to implement themselves.

    Tasked with securing increasingly complex software development environments, it’s not clear whether DevOps teams will opt to rely on a cloud service, but given the general lack of security expertise among software development teams, the fastest way to secure a software supply chain for most organizations is to rely on a service.

    Regardless of approach, of course, DevSecOps will soon become a standard element of application development workflows. Once that occurs, it’s not clear whether DevOps will simply become DevSecOps or whether security will be assumed to be an integrated element of any set of DevOps best practices.

    Sarwar Raza, vice president and general manager for cloud services at Red Hat, said regardless of approach, it’s clear that implicit trust is no longer good enough. Organizations of all sizes will need to be able to demonstrate that they have maintained a chain of custody for the software components used to build an application, he noted.

    One way or another, the overall security of downstream applications should eventually improve as the processes used to construct software are increasingly locked down.