Cloud CI/CD is a force multiplier for development teams, especially those working remotely. Automated CI/CD takes load off of developers, allowing them to focus on building better products. Hosted CI/CD adds further benefit to this, ensuring that this newfound capacity isn’t spent managing the testing and deployment infrastructure, and that remote team members have easy access to CI/CD tools.
As the complexity of modern software development lifecycles increase, it’s important to have a comprehensive monitoring solution for your continuous integration (CI) pipelines so that you can quickly pinpoint and triage issues, especially when you have a large number of pipelines running.
We talk with numerous teams that want to improve their engineering performance. Here, we explain how to accelerate your progress using DORA metrics — a set of key performance indicators that can help you measure and optimize your team's software development process. You'll learn practical tips on how to leverage these metrics to achieve faster and more efficient team improvement. But first, you'll need your team to see the value in DORA metrics.
Continuous Integration/Continuous Delivery (CI/CD) has now become the de-facto standard for all engineering teams seeking to keep pace with the demands of the modern economy. At Coralogix, we operate some of the most advanced build and deploy pipelines in the world. We’ve baked that knowledge into our platform with a CI/CD Observability feature called Coralogix Tagging.
If you’ve worked in a large, security-minded organization, you know how developers’ need for speed often clashes with the organization’s need for security. Often this conflict erupts into a high-stakes battle between two teams with very different priorities and perspectives. Ok, it may not always be so dramatic, but the challenge of control and empowerment is very real.
As a software engineer, one of your goals is to ensure that your product can be accessed globally by your customers. It’s not enough that an app is bug-free and works flawlessly if it only works on localhost. Docker was introduced to solve the “it works on my machine” problem. For example, the particular version of a programming language a developer is using on Windows or MacOS may not be working on the hosting server.
