The adoption of cloud-based solutions has become increasingly common. The proof for this is evident – according to Gartner, Inc., the worldwide public cloud services market is expected to grow by 6.3% in 2020, up to a staggering $257.9 billion in value. The Flexera 2020 State of the Cloud Report, released on April 28, 2020, states that more than 90% of respondents have adopted cloud computing, with the top three cloud service providers being – AWS, Azure, and Google Cloud Platform.

In our previous guide, we documented 10 Docker anti-patterns. This guide has been very popular as it can help you in your first steps with container images. Creating container images for your application, however, is only half the story. You still need a way to deploy these containers in production, and the de facto solution for doing this is by using Kubernetes clusters. We soon realized that we must also create a similar guide for Kubernetes deployments.

This is the second part in our Kubernetes Anti-patterns series. See also part 1 for for the previous part and part 3 for the next part. You can also download all 3 parts in a PDF ebook.

This is the third and last part in our Kubernetes Anti-patterns series. See also part 1 and part 2 for the previous anti-patterns. You can also download all 3 parts in a PDF ebook.

I’ve recently started working on a new project to build a Discord bot in Go, mostly as a way to learn more Go but also so I can use it to manage various things in Azure and potentially elsewhere. I figured it’d be useful to document some of this project to give some insights as to what I’ve done and why. First up was setting up the CI/CD pipeline for it so that I don’t need to worry about it later and can save myself a bunch of time when testing.

Bitbucket Cloud’s pull request sidebar is useful because it displays all the relevant details of the pull request you’re looking at. However, with so much information present, it can be hard to find the information you need. To address feedback we’ve received about its readability and usability, we’ve given it a redesign.

Where do you usually track your code coverage? If you are not sure about the answer to this question or you would like to explore other options to the ones that you are currently using, then this post is for you. Specifically, this post details how you can use Codacy in your Codefresh pipeline to create and send coverage reports of your repository with every pipeline build. To follow along, make sure to have a Codacy and a Codefresh account. If not, now is the time to set-up a fresh account for free!

At Cloudsmith, we are proud of our partnership network. We work hard to collaborate and integrate with the best DevOps tools available. Building performant, modern workflows requires frictionless integrations between tooling. Integrating Cloudsmith repositories with your CI/CD processes facilitates rapid development. Build, test, and deploy/distribute your software in repeatable, performant ways.

At the beginning of 2020, none of us could have imagined what we would be talking and thinking about at the end of the year. At JFrog, we began by talking about unifying everything in the DevOps lifecycle. Of course very quickly, the message of unity and togetherness would soon become even bigger than we could imagine in light of the global pandemic.

The appearance of containers and their performance benefits compared to the existing paradigm of virtual machines has forced several companies to rethink their software lifecycle, especially the delivery part. Continuous integration and deployment tools (CI/CD) are passing through a second renaissance phase which is characterized by new approaches centered around short-lived environments that are launched and destroyed in a much more dynamic way.