Bitbucket Pipelines provides a Docker caching feature that can help improve build times. However, the limitation is that only compressed caches under 1GB are saved and can be used. In this blog, we outline a process showing how you can use compressed caches that are larger than 1GB. With Docker versions >= 19.03, you can use the BuildKit feature. With BuildKit, you don’t need to keep the cache locally before building the Docker image since it caches each build layer in your image registry.

Like the historic space race, the competition to plant the flag of DevOps is blasting off. According to market intelligence firm IDC, global business will invest $6.8 trillion in digital transformation by 2023. Yet research also suggests that 70 percent of them will fail to meet their goals. JFrog was the first company to offer a universal, hybrid, end-to-end DevOps platform.

It’s often necessary to inject secrets into your build or deployment process so that the deployed service can interact with other services. This can be straightforward if you’re only deploying to a single environment. When deploying to multiple environments, though, you might need to dynamically inject different secrets depending on the environment to which you’re deploying.

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.