From the course: Data Pipeline Automation with GitHub Actions Using R and Python

Reviewing workflows logs - GitHub Tutorial

From the course: Data Pipeline Automation with GitHub Actions Using R and Python

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Reviewing workflows logs

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- [Instructor] In the previous video, we created our first workflow, Hello World. Let's now go back to the Action section on the repository and see how can we explore the job logs. First, on the repository, click the Action tab. On the left side, you can see the list of all the actions that are available in this repository. So for example, you can see here our action that we created in the previous video, Hello World. On the main screen, you can see the most recent jobs that ran and their status. A green check mark indicates that the job was completed successfully, and a red X indicates a failure. You can access the log of the Hello World either by going to the workflow name on the left side, or click on the job name if available on the main screen. Let's go ahead and click over here on the Hello World job. And as you can see here, there is a description of the specific job that ran, the time, duration of the runtime. And we can access it by clicking this box. And here you can see the steps of running the job. The job start by setting up the machine and then loading the container. It then run the job. And you can see here the name that we set for the job, print-hello-world. And once it's done, stop the containers and complete the job. We can expand each step by clicking the arrow. So you can see here this is the process of creating, setting the machine. And over here loading the image. Let's go ahead and check the job that we set. And as you can see here, the command that was running was run echo Hell World, and this is the output. And as you can see, the job completely successfully as expected.

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