 Hi, I'm Sista Savera, Technical Marketing Manager at GitLab. In this video, I'm going to show you how the power out of DevOps automates and integrates your continuous delivery to help increase productivity and speed up your releases. Let's get started. Devon is a DevOps engineer whose organization has been looking for ways to eliminate the complexities of software delivery. Their developers spend a lot of time setting up pipelines and integrations instead of developing innovative and differentiating features and applications for the business. Devon wants to use GitLab's AutoDevOps to address these challenges. He has an application he needs to deliver to the business and he proceeds to enable AutoDevOps. AutoDevOps are prescribed out-of-the-box CICT templates that auto-discover the source code you have. Based on best practices, they automatically detect, build, test, deploy and monitor your applications. The AutoDevOps pipeline shifts work left to find and prevent defects as early as possible in the software delivery process. The pipeline then deploys the application to staging for verification and then to production in incremental fashion. AutoDevOps saves Devon and developers in his organization from implementing their own pipelines so that they can spend more time innovating. Devon goes over the AutoDevOps stages that have been prescribed to his project for his configuration options. First, he sees the build stage. AutoBuild creates a build of the application using an existing Docker file or build packs. The resulting Docker image is pushed to the built-in container registry. All these steps are armatically executed on Devon's application so that he can spend more time delivering value to the business. Devon sees a variety of tests under the test stage. AutoDevOps includes jobs for static analysis and code checks, for identifying security issues in containers, for analyzing project dependencies and security issues, for scanning license dependencies, for detecting credentials and secrets exposure, for running security analysis of Java code, language which DevOps auto-detected in Devon's project, and for specific unit tests for the language and framework. All these tests increase the quality of code, compliance and reliability that translate into a highly resilient production environment. Devon moves on to inspect the review stage, which contains a single job that spins up an ephemeral environment to be used by the Dynamic Application Security Testing, or DAST. Likewise, the DAST stage has the job Autodynamic Application Security Testing, which analyzes the current code and checks for potential security issues by running OWAS-related tests. Since Devon selected automatic deployment to staging, manual deployment to production when he enabled AutoDevOps, towards the CD portion of the pipeline, he sees the staging stage, which contains a single job. The staging job deploys Devon's application to the staging environment. It will also instantiate the staging environment if needed. Per Devon's selection, the production stage is manual and contains four jobs to incrementally deploy his application to production. An incremental rollout decreases the risk of a production outage or downtime. By releasing production changes gradually, error rates or performance degradation can be monitored, and if there are no problems, all the production can be updated. Devon's project has been prescribed a performance stage with a single job with the same name. Auto Browser Performance Testing measures the browser performance of each webpage and reports on any degradation or improvement so that appropriate action can be taken. Lastly, Devon inspects the cleanup stage, which contains a job that brings down and frees all resources of the ephemeral DAST environment that was brought up earlier in the CI portion of the pipeline. This entire prescribed CI CD pipeline, with all its stages and jobs, is based on best practices and is automatically run for Devon's project, saving him time and effort from developing his own. As Devon and other developers collaborate on this project, Auto Devops automatically includes auto review apps, which stands up an ephemeral environment for stakeholders to review their running application with proposed changes before they emerge to the main branch. The teardown and freeing of the resources of the ephemeral review environment are also automatically done by Auto Devops once the merge takes place. Devon would like to modify the Auto Devops pipeline by skipping some of its stages and jobs. He knows he's using all open source license software within his project and he's pretty confident about his web application performance. He'd also like to add the ability to do canary deployments. He proceeds to customize Auto Devops via environment variables to skip the license scanning and performance jobs and add canary deployments to his project. Devon could also use the GitLab APIs to script these modifications if he so desired. Another way Devon could customize the Auto Devops pipeline is by adding it to his own project and then making changes to it. He adds a pipeline to his project by reusing the Auto Devops template. He then disables all license management and web performance tests. Devon could also leverage portions of Auto Devops in his own pipeline by including specific templates. In this smaller pipeline, he only reuses the Auto Build and Auto Test capabilities of Auto Devops. In this video we have seen how the power of Auto Devops automates and integrates your continuous delivery to help speed up your releases by saving you time from having to run your own pipelines. By using Auto Devops, you can accelerate your product delivery times and bring differentiating application features faster to market. I hope you enjoyed this video and until next time.