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.

As the prevalence of containers continues to expand, managing the push and pull of containers without an enterprise-grade container registry is unwieldy. Many companies utilize JFrog Artifactory as a Docker and Helm registry, but also utilize Docker Desktop strategically to manage their container services.

If you’re a developer, DevOps engineer, or security technician, you know the feeling of managing multiple tools at once. It’s a phenomenon so prevalent in software development that it has its own name, “tool sprawl,” and it can make it hard for teams to do their jobs efficiently.

If DevOps is an approach to software development that emphasizes collaboration between Development and Operations teams, then Platform Engineering operationalizes that approach by creating a centralized platform that has specific sets of tools and processes. It’s the discipline of designing and building toolchains and workflows that enable self-service capabilities for software engineering organizations in a cloud-native era.

In part one of this series, we looked at what is a dependency, different types of dependencies, and their benefits in our code. In part two, we’ll look at the risks of using dependencies. Whenever we add a dependency we are increasing the risks of any software development cycle.

As we all know, team collaboration can sometimes be a bit complicated. Especially when different teams in the organization strive to achieve their own individual goals. This is where new organizational practices, such as DevOps and DevSecOps, have paved the path for us to work together and achieve our mutual goals. Take a look at these three trying to make it work… Triple Therapy for your Dev, Sec AND Ops Teams.