The last year was undeniably a different year for everybody. At the start of 2020, Coronavirus spread all over the world, resulting in a global pandemic. Covid affected the way we live, work, meet other people, and has drastically changed everyone’s lives in ways that we could not ever imagine. In a world of uncertainty, DevOps has undeniably become even more important.

Data from monitoring tools like Datadog are useful for developers to help them understand whether the code they've deployed is healthy or needs to be fixed or rolled back, or when there is an incident to investigate. As a deployment mission control, Sleuth helps developers see metrics data from a developer-centric point of view - by deployment - and interpret such data for them. ‍‍

One of the most typical challenges when deploying a complex application is the handling of different deployment environments during the software lifecycle. The most typical setup is the trilogy of QA/Staging/Production environments. An application developer needs an easy way to deploy to the different environments and also to understand what version is deployed where. Specifically for Kubernetes deployments, the Helm package manager is a great solution for handling environment configuration.

Coveralls is a web service that allows users to track the code coverage of their application over time in order to optimize the effectiveness of their unit tests. Once you are managing your application and associated resources within a CI/CD platform like Codefresh, you want to receive insights on the test coverage automatically with every pipeline build. This post provides an overview of how this can be achieved with Coveralls and Codefresh.

A typical modern DevOps pipeline includes eight major stages, and unfortunately, a release bottleneck can appear at any point: These may slow down productivity and limit a company’s ability to progress. This could damage their reputation, especially if a bug fix needs to be immediately deployed into production. This article will cover three key ways using data gathered from your DevOps pipeline can help you find and alleviate bottlenecks in your DevOps pipeline.

Codecov is a code analysis tool with which users can group, merge, archive, and compare coverage reports. Code coverage describes which lines of code were executed by the test suite and which ones were not. However, this is not to be confused with a testing tool. Codecov does not run your tests, that is the job of your testing tools. The analysis that Codecov provides will classify code in either of the following states: Additionally, In this tutorial, we will.