Successful DevOps implementation is critical for enhancing the efficiency, reliability, and quality of software development and delivery. To evaluate the effectiveness of DevOps practices, various metrics can be used. Below is a detailed overview of key metrics.

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 also important to be able to store datasets and versioned models together.

Widespread adoption of containerized infrastructure has been closely followed by an explosion of container-native tools for each layer of the stack, including new solutions for managing CI/CD pipelines in container-based environments, such as the Argo suite, FluxCD, and Tekton. This is because these lightweight solutions make it easier to automate builds, testing, deployments, and more on Kubernetes, as well as other platforms that manage containerized workloads and services.

In the fast-paced world of software development, the ability to quickly and reliably deliver software is paramount. This need has led to the evolution of CI/CD—Continuous Integration, Continuous Delivery, and Continuous Deployment—practices that streamline and automate the development lifecycle. Below, we explore these core CI/CD concepts and related automation practices that are transforming the software industry.

In today’s fast-paced software development landscape, the need to deliver high-quality software rapidly and reliably is paramount. Continuous Integration (CI) and Continuous Delivery/Deployment (CD) have emerged as essential practices that enable development teams to meet these demands. Central to the success of CI/CD pipelines is a robust framework for testing and quality assurance (QA).

Continuous integration and continuous deployment (CI/CD) are the backbone of modern software delivery, but there’s still limited visibility into their processes. Here’s how that’s changing with OpenTelemetry (OTel), and why those changes are so exciting.

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.

React is an open source JavaScript library known for its simplicity and incredible performance when creating an interactive user interface. React has gained wide adoption from web developers and reputable companies. While there are other frameworks in the JavaScript ecosystem, React is often the first choice when it comes to user interface and frontend business logic.

As we delve deeper into the era of software reliance, the 2024 JFrog Software Supply Chain report emerges as required reading for developers and DevOps professionals who are at the frontline of today’s technological innovations.

Kubernetes at the edge has become extremely popular with retail companies like Chik-Fil-A and Starbucks, leading the way as famous examples to the more exotic US Air Force deploying Kubernetes on F-16s. At Codefresh we’ve seen and helped implement every kind of edge deployment from clusters in retail stores, mobile clusters in vehicles, air-gapped clusters for telecoms, and lots more.