In today’s world of heterogeneous data ecosystems, managing and consuming data can be cumbersome. Organizations often have multiple systems of truth in corresponding to the applications managing the data. While data engineers dream of software that would make it easy to consume and digest different data streams from disparate systems, that scenario rarely comes to fruition.

Testing in isolation is known to be expensive. It’s time-consuming to execute thoroughly, and it typically requires a testing environment — sometimes multiple testing environments. That said, testing in isolation is undeniably effective.

If you work anywhere near the field of software development, you’ve likely already heard that you should always write code that is well-tested. Everyone wants to have well-tested code and for a good reason! Testing ensures our code is working as intended and protects against regression. Thoroughly testing code helps teams confidently ship software faster and with fewer issues.

With KubeCon 2021 upon us, we look forward to seeing many exciting announcements from our peers in the open-source DevOps community in the days ahead. Codefresh is honored to make some exciting news of our own. Today we officially unveiled the Codefresh Argo Platform – a fully featured, enterprise-class implementation of Argo.

Infrastructure as Code (IaC) is the practice of recording the desired state of your infrastructure using a declarative language. In this article, I’m going to assume that your team is starting from scratch. Maybe some of your build process has been scripted, and maybe there is some manual testing and quality assurance work happening. Many readers will find that they are midway through the IaC adoption journey I’ll describe, or that they have missed some steps.

In my interactions at industry events like AWS re:invent and KubeCon, I talk with a lot of developers. Devs often tell stories of things that prevent them from working quickly and efficiently. Many involve frustrating interactions with sys admins, SREs, or DevOps colleagues. One story I have heard several times involves a conversation like this: dev: Hey, SRE team. My build is failing and I don’t know what’s happening with the app in the build node.

While DevOps automation aims to eliminate most human intervention in the CI/CD DevOps pipeline, you can’t always cut people completely out of the process. There are still times when you’ll want an expert, hands-on review to assure that everything is as it should be before allowing your pipeline to proceed further.

Modern software development increasingly relies on distributed, service-based architectural patterns to achieve scalability, reliability, and rapid build, test, and release cycles. Two of the most popular service-based approaches are service-oriented architecture (SOA) and microservices. In this article, we will examine both approaches to identify their similarities and differences as well as some use cases for each.

Kotlin is one of the most versatile programming languages available, in large part because of the Kotlin team’s focus on bringing it to as many platforms as possible. It is the primary language for developing Android applications and is popular for JVM backends. Kotlin also features targets for native binary compilation with Kotlin/Native, and for web through Kotlin/JS. One of its most promising features is the ability to target multiple platforms it compiles to.

JFrog security research team (formerly Vdoo) has recently disclosed a code injection issue in Yamale, a popular schema validator for YAML that’s used by over 200 repositories. The issue has been assigned to CVE-2021-38305.