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Author: Javier Perez

  • 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.

  • Friend or Foe? ChatGPT’s Impact on Open Source Software

    Friend or Foe? ChatGPT’s Impact on Open Source Software

    OpenAI’s ChatGPT took the world by storm, amassing 100 million users in the first two months after its public launch. The continued interest in the tool has created a buzz among developers, especially those in the open source community. But this begs the question: How will ChatGPT impact open source software?

    Amid the excitement and promise that ChatGPT holds, many wonder whether the open source community, just like any other organization, should fear or embrace the technology. Certain concerns for open source contributors and developers are sparking debate as questions surrounding the origin of generated source code surface, and the possible ethical and legal implications are discussed. While valid, developers should not fear or stray away from using ChatGPT but rather shift their focus to understanding how to embrace it for positive outcomes.

    The Top Three Open Source ChatGPT Concerns

    Collaboration between contributors is the cornerstone of open source projects, which some fear will be disrupted with the increased use of AI-based tools. However, the level of synergy within the community cannot be easily taken away or replaced by tools. Instead, ChatGPT or other AI-based tools, including GitHub Copilot, allow developers to produce code more quickly and more efficiently.

    As developers increasingly use AI tooling to assist with new or enhanced code, project collaboration and oversight will help improve the AI-generated code.

    Debunking and navigating the top concerns will be imperative to take full advantage of the technology’s promise and potential.

    Validity. While the creation of code by ChatGPT has generated excitement among developers, critics argue that—without context—the validity of code can be questioned. Some open source developers worry that teams will begin to rely entirely on ChatGPT to generate code, but this concern fails to consider the humans involved in the process—today and far into the future.

    Developers don’t take ChatGPT’s output as the final word; rather, they use it as a baseline and jumping-off point to streamline their code. In fact, code is rarely created from scratch anymore. Developers rely on others’ source code. For example, code from Stack Overflow, GitHub and thousands of open source libraries that are available on public registries like npm, Maven, Nuget and PyPI. Bringing ChatGPT into the fold will not significantly change how developers source their code, but will improve development velocity, saving valuable time and associated cost.

    Training Data. Machine learning (ML) and deep learning (DL) model training must be fair, robust and explainable to avoid biases. If the data is wrong, the results will be as well. Garbage in, garbage out. Coming from ML/DL models, the code ChatGPT returns in response to prompts could raise concerns surrounding its accuracy. Like any other source (Stack Overflow, GitHub, etc.), ChatGPT’s code outputs are not guaranteed to be perfect, and developers must be mindful of this.

    However, there are more benefits of ChatGPT-trained models concerning code outputs. ChatGPT can also explain new or existing code, it can also effectively provide unit tests for code, which will help with writing better software faster.

    Ownership. Questions of ownership have surfaced regarding the use and distribution of the code that the AI tool generates. While the code that ChatGPT generates is the result of ML/DL inference from many sources, it’s the developer’s responsibility to use that code ethically and safely. It should be treated as any other public data or open source software, as not a final product and must be used in the context of your requirements. It’s also important to carefully review any code generated by ChatGPT and ensure that it doesn’t introduce vulnerabilities.

    Similar to GitHub Copilot, ChatGPT is trained by millions of lines of open source software. Code posted in prompts is likely to make it to models, too. Unlike copyrighted pieces of art and writing, the code that ChatGPT outputs should not be considered in a final state and should not be used in a way that is subject to licensing restrictions or legal implications that have dominated the conversations around its use.

    Ownership closely relates to the ethical dilemma of using AI-generated text, code and more. To address that, there are new tools that help detect whether AI generated the content and how much, which will be useful for educators concerned with students overusing the tool. This emerging area of checks and balances exemplifies the constantly evolving and improving technologies that allow humans, and in the case of open source, contributing developers to improve their craft and produce better open source software.

    ChatGPT’s Impact on Open Source Talent

    Discussions about whether ChatGPT will require new skills for existing positions or new jobs with specialized experts are ongoing. While new and exciting, ChatGPT won’t immediately create new or different jobs. Like any new tool introduced to developers, it takes time for developers to become familiar with the technology and understand how to use it best. ChatGPT is no different. For example, consider the previous push to use low-code/no-code technology. While this great technology is used to speed up the creation of apps and improve the usability for non-developers, it has taken time for organizations to properly use low-code/no-code technology. A similar perspective and trajectory will extend to the use of ChatGPT for all software development, including open source projects.

    In the coming weeks and months, it will be essential to encourage the open source community to embrace ChatGPT and explore its possibilities. Technology has already proven to be an effective educational tool. Consider asking ChatGPT for book recommendations about programming languages and coding; it delivers short descriptions for each book. Or, prompt it for the top takeaways from one specific book. By doing this, individuals can make learning so much easier. By learning from other developers and sharing resources, including results from ChatGPT, the community roots of open source will keep thriving.

    Human Involvement is Always Needed

    The public’s reaction to ChatGPT may be novel, but the idea behind the tool’s relationship to open source is not. Analyzing how ChatGPT works within the open source community reveals that it will be useful because it enhances the capabilities of developers, it doesn’t replace them.

    Whether it’s reviewing code, pair programming or learning from fellow developers, humans will not be replaced by generative AI, only enhanced. Leveraging the tool will decrease the time and effort needed to complete tasks, increasing developer quality and efficiency. The use of ChatGPT does not create new positions or overhaul current skill sets; it makes them better and empowers developers to expand their opportunities and enhance their abilities.

    Soon, ChatGPT and other AI tools will be standard practice within the open source community—or until a new technology is created and shakes up software development once again.