Writing clean and efficient code can be time consuming, but with the right tools, it can be much easier. In this blog post, we will explore how to use Copilot for code autocompletion and JFrog Artifactory for your package management.

As software architects and developers, we’re always looking for best practices and lessons learned to enhance application development. Is there a best practice application reference architecture? What are the challenges other developers are also facing in application development?

Amazon Elastic Kubernetes Service — or Amazon EKS — is a managed service that enables you to run Kubernetes on AWS without having to manage your own Kubernetes clusters. The JFrog Platform is available on AWS, making it super simple to deploy applications reliably and predictably, scale them quickly, roll out new features easily, and make the most of hardware resources.

Many processes in our daily software development chain require data analysis in real-time. Ensuring the reliability of the data is vital, since multiple processes may rely on it. While taking into account the performance and fetching only the relevant data that is required for our specific use case.

We all know that artifact management is an important part of our development lifecycle, and if you’re using Jenkins you’ll also need to store your builds and binaries. In the world of DevOps, efficient integration and management of artifacts and dependencies are crucial for successful software delivery. Together, Jenkins and JFrog Artifactory offer a powerful combination for streamlined build processes.

Are you tired of using security tools that generate endless results, making it impossible to identify actual risks? Do you struggle with inefficient prioritization due to a lack of context, making the process of assessing and remediating vulnerabilities a time-consuming nightmare? Look no further than JFrog’s Contextual Analysis, available as part of the “jf audit” command in the JFrog CLI.

Every organization has a process for building and releasing software. Smaller organizations may run a few automated tests before releasing, while larger organizations may have 100s of scans, validations, and approvals spanning everything from technical to legal. Whatever the process is, the end goal is the same: software that’s mature enough for release. The challenge is that this process is complicated, messy, and often created in an ad hoc way, changing as organizations evolve.

For DevOps, 2023 is the year to reduce tool sprawl and start tool consolidation efforts. Sprawl is often seen as a natural result of the flexibility and empowerment of dev teams to choose their own tools, but organizations now understand the need for a single, streamlined system. While flexibility to choose the right tool for the job has enabled teams to move quickly, the result is a complex web of systems and processes to deliver software.