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Doing DevOps Your Way On SaaS Solutions: Connecting JFrog CLI to Your JFrog Workers

In our previous blog post, we explored JFrog Workers, a JFrog Cloud Platform service that allows you to create customized workers that can respond to events in the platform. These workers can perform various tasks, from running code to adjusting functions, giving you more flexibility and control over your workflows. Allowing you to automate processes and streamline your development pipeline in a serverless execution environment.

JFrog & Qwak: Accelerating Models Into Production - The DevOps Way

We are collectively thrilled to share some exciting news: Qwak will be joining the JFrog family! Nearly four years ago, Qwak was founded with the vision to empower Machine Learning (ML) engineers to drive real impact with their ML-based products and achieve meaningful business results. Our mission has always been to accelerate, scale, and secure the delivery of ML applications.

Taking a GenAI Project to Production

Generative AI and Large Language Models (LLMs) are the new revolution of Artificial Intelligence, bringing the world capabilities that we could only dream about less than two years ago. Unlike previous milestones, such as Deep Learning, in the current AI revolution, everything is happening faster than ever before. Many feel that the train is about to leave the station, and since we are talking about bullet trains – every day matters.

How to Connect the JFrog Platform to Your GitHub Environment to Create a Seamless Integration

The latest JFrog collaboration with GitHub enables you to easily combine your favorite solutions for source code and binaries in a seamless integration. This means you now have a unified comprehensive and secure end-to-end experience that supports your software projects. This integration covers everything from curating open source packages, coding, CI, release management, deployment and production. Including three major improvements to your developer experience.

Ensure your models flow with the JFrog plugin for MLflow

Just a few years back, developing AI/ML (Machine Learning) models was a secluded endeavor, primarily undertaken by small teams of developers and data scientists away from public scrutiny. However, with the surge in GenAI/LLMs, open-source models, and ML development tools, there’s been a significant democratization of model creation, with more developers and organizations engaging in ML model development than ever before.

Supporting Next-Level Enterprise Scale in Software Development

What it means to be “enterprise grade” has changed. In software development, the size of new artifacts and the pace of development has increased dramatically. Developers are now releasing new components daily, if not multiple times a day. With containerization, and now AI/ML models, new pieces of software can be multiple GBs or larger.

Elevate and Streamline Your Developer Experience with JFrog-Coder Fusion

It’s a scenario many developers know all too well: a configuration works flawlessly for one team member but doesn’t work for you. Starting a new job brings with it the excitement of fresh challenges and opportunities. However, it also entails the often painful task of setting up your development environment—a process that can be both time-consuming and complex. This setup phase involves installing dependencies, configuring projects, and troubleshooting issues that might arise.

Software Ate the World, but Digital Transformation Can Give You Indigestion

In today’s digitally-driven world, organizations rely heavily on software applications to streamline services, provide operations, engage customers, and drive innovation through digital transformation. Software has also become the lynchpin for securing an entire business’ services and keeping them up and running. Yet, this omnipresent force comes with its own set of challenges.