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Sean Pratt

Senior Manager, Product Marketing, JFrog

Sean leads Platform and DevOps Product Marketing at JFrog. A “Full Stack Marketer,” he’s previously worked at a wide range of technology startups from HR tech to Smart City/IoT. When not reading, writing, and learning about secure software supply chains, he’s spending time with his family, learning Python, and very occasionally playing on his Switch.

The Latest From Sean Pratt

  • Scaling Docker Usage with JFrog
    | 6 min read

    Earlier last month the development industry was preparing for rate limit changes at Docker Hub. Ultimately, any rate limit changes were put on hold. Many JFrog customers have asked us, “How would Docker Hub rate limit changes impact us?” In this post we’ll discuss what you can do to ensure uninterrupted usage of Docker, now…

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  • Now Available: Smart Archiving with the JFrog Platform
    | 5 min read

    Every day development teams around the world release new software. But what happens to prior releases that are no longer in production? Most organizations save them, typically due to internal policies, external regulations, or simply the fear of losing data. Organizations typically take varied approaches to retaining their prior releases. Some use a dedicated repository…

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  • Building a Software Data Retention Strategy and Why You Need One
    | 7 min read

    Every day, your developers are pushing software. Some of that software will make it to production, but many of those incremental builds will not. While you shouldn’t remove those incremental builds and old release versions haphazardly, if left unchecked, they can clog up your software repositories as well as the workflows and systems they serve.…

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  • The State of the Software Supply Chain 2025
    | 6 min read

    Managing and securing the software supply chain is crucial for trusted releases, but as any tech organization knows, it also presents significant challenges. With over 15 years of experience and a dedicated security research team, we at JFrog understand these threats. In a rapidly evolving post-AI world, DevSecOps teams are struggling to keep pace with…

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  • Get to Know JFrog ML
    | 6 min read

    AI/ML development is getting a lot of attention as organizations rush to bring AI services into their business applications. While emerging MLOps practices are designed to make developing AI applications easier, the complexity and fragmentation of available MLOps tools often complicates the work of Data Scientists and ML Engineers, and lessens trust in what’s being…

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  • The Power of Evidence Collection and Release Lifecycle Management
    | 7 min read

    The speed of today’s software development lifecycle is only getting faster. However, the complexity of today’s pipelines make it hard to track and manage the processes software releases must go through. With increasing regulatory pressures, ensuring and proving your software has gone through the necessary quality controls is no longer nice to have – it…

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  • MLOps Your Way with the JFrog Platform
    | 5 min read

    Just like in traditional software development, creating AI applications isn't a one size fits all approach. However, many of the challenges and concerns facing AI/ML development teams share common threads - difficulties getting models to production, tangled infrastructure, data quality, security issues, and so on. Regardless of how you build it, to accelerate production-ready AI,…

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  • Now Available: Evidence Collection with JFrog
    | 5 min read

    There is an increasing need for traceability and attestation of the actions taken as software moves across the SDLC. Emerging regulations and policies around secure software development are rapidly evolving, and it’s important to stay ahead of the changing landscape. Some organizations have taken a proactive approach with home-grown solutions or manual processes, but despite…

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  • Manage Ansible Collections with JFrog Artifactory
    | 4 min read

    If you work with virtual machines or install and configure software on EC2 or leverage dynamic runtimes, chances are you’re also using Ansible. In fact, JFrog has supported installation via Ansible for some time. If they’re not using Red Hat, the way most organizations have managed their Ansible Collections – including Roles – is by…

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  • Expanding Artifactory’s Hugging Face Support with Datasets
    | 3 min read

    When working with ML models, it’s fair to say that a model is only as good as the data it was trained on. Training and testing models on quality datasets of an appropriate size is essential for model performance. Because of the intricate link between a model and the data it was trained on, it’s…

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