[{"data":1,"prerenderedAt":794},["ShallowReactive",2],{"/en-us/blog/cd-automated-integrated":3,"navigation-en-us":39,"banner-en-us":439,"footer-en-us":449,"blog-post-authors-en-us-Cesar Saavedra":689,"blog-related-posts-en-us-cd-automated-integrated":703,"assessment-promotions-en-us":745,"next-steps-en-us":784},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":26,"isFeatured":12,"meta":27,"navigation":28,"path":29,"publishedDate":20,"seo":30,"stem":34,"tagSlugs":35,"__hash__":38},"blogPosts/en-us/blog/cd-automated-integrated.yml","Cd Automated Integrated",[7],"cesar-saavedra",null,"unfiltered",{"slug":11,"featured":12,"template":13},"cd-automated-integrated",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"GitLab’s automated and integrated continuous delivery","Learn about how the power of GitLab Auto DevOps can help increase productivity and speed up releases.",[18],"Cesar Saavedra","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749681872/Blog/Hero%20Images/CD-2st-mkt-diff-cover-1275x849.jpg","2021-01-22","\n\n{::options parse_block_html=\"true\" /}\n\n\n\nOrganizations adopting DevOps best practices to software delivery spend time and effort designing, building, testing, integrating, and maintaining CI/CD pipelines for their different projects. Just as they must spend some of their time maintaining their business applications instead of innovating, they must do the same for their pipelines. Freeing your developers so that they can spend more of their time creating new business applications and differentiating value to the business is of utmost importance to remain competitive in a world where organizations must be digital leaders to succeed in the marketplace.\n\nGitLab provides [Auto DevOps](/topics/devops/), which are prescribed out-of-the-box CI/CD templates that auto-discover the source code you have. Based on best practices, they automatically detect, build, test, deploy, and monitor your applications. Auto DevOps save your developers from implementing their own pipelines so that they can spend more time innovating. In the following paragraphs, we go over how the power of Auto DevOps automates and integrates your continuous delivery to help increase productivity and speed up releases.\n\n## Enabling Auto DevOps\n\nIt’s very easy to enable Auto DevOps for your application. All you need to do is go to your Project Settings and select the configuration you desire for Auto DevOps. As the picture below depicts, you can select the deployment strategy to “Automatic deployment to staging, manual deployment to production”:\n\n![autodevops-on](https://about.gitlab.com/images/blogimages/cd-automated-integrated/autodevops-on.png){: .shadow.medium.center.wrap-text}\n\nThe Auto DevOps pipeline shifts work left to find and prevent defects as early as possible in the software delivery process.\n\nThe pipeline then deploys the application to staging for verification and then to production in an incremental fashion. Auto DevOps saves you and your developers from implementing your own pipelines so that you can spend more time innovating.\n\n## Auto DevOps stages and jobs\n\nThe stages and jobs of the Auto DevOps pipeline vary according to the way you configured it. You can also customize the prescribed Auto DevOps pipeline or reuse only portions of it. Let’s review the prescribed stages and jobs for a simple Java application.\n\n1) First you find the Build stage. Auto Build creates a build of the application using an existing Dockerfile or buildpacks. The resulting Docker image is pushed to the built-in Container Registry.\n\n![auto-build](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-build.png){: .shadow.medium.center.wrap-text}\n\nAll these steps are automatically executed on your application so that you can spend more time delivering value to the business.\n\n2) Next is a variety of tests under the Test stage. Auto DevOps 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, And for specific unit tests for the language and framework.\n\n![auto-test](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-test.png){: .shadow.medium.center.wrap-text}\n\nAll these tests increase the quality of code, compliance and reliability that translate into a highly resilient production environment.\n\n3) The review stage 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, Auto Dynamic Application Security Testing, which analyzes the current code and checks for potential security issues by running (Open Web Application Security Project) OWASP-related tests.\n\n![auto-review-dast](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-review-dast.png){: .shadow.medium.center.wrap-text}\n\n4) The prescribed stages and jobs in Auto DevOps vary depending on how you configure it. In this example, the user has selected “Automatic deployment to staging, manual deployment to production” when enabling Auto DevOps, so towards the CD portion of the pipeline, we see the staging stage, which contains a single job. The staging job deploys the user’s application to the staging environment. It will also instantiate the staging environment, if needed.\n\n![auto-staging](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-staging.png){: .shadow.medium.center.wrap-text}\n\n5) 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 of production can be updated.\n\n![auto-prod](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-prod.png){: .shadow.medium.center.wrap-text}\n\n6) The user has been prescribed a performance stage with a single job with the same name. Auto Browser Performance Testing measures the browser performance of each web page and reports on any degradation or improvement so that appropriate action can be taken.\n\n![auto-browser-perf](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-browser-perf.png){: .shadow.medium.center.wrap-text}\n\n7) The last stage is 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.\n\n![auto-cleanup](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-cleanup.png){: .shadow.medium.center.wrap-text}\n\nThis entire prescribed CI/CD pipeline, with all its stages and jobs, is based on best practices and is automatically run for the user’s project saving them time and effort from developing their own pipeline.\n\n## Auto Review Apps\n\nAs developers collaborate on a project, Auto DevOps automatically includes Auto Review Apps, which stands up an ephemeral environment for stakeholders to review the running application with proposed changes before they are merged 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.\n\n![auto-review-apps](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-review-apps.png){: .shadow.medium.center.wrap-text}\n\n## Modifying Auto DevOps\n\nHere are some ways that you can modify Auto DevOps.\n\n1) **Customization via environment variables**. If you would like to skip some of the stages and jobs in Auto DevOps, you can do this via project variables. For example, say you are using all open source licensed software within your project and you are pretty confident about your web application performance, and you’d also like to add the ability to do canary deployments. You can customize Auto DevOps via environment variables to skip the license-scanning and performance jobs and add canary deployments to your project by creating and setting specific environment variables as shown below.\n\n![auto-env-vars](https://about.gitlab.com/images/blogimages/cd-automated-integrated/auto-env-vars.png){: .shadow.medium.center.wrap-text}\n\nYou could also use the GitLab APIs to script these modifications if he so desired.\n\n2) **Customization by editing the DevOps pipeline**. Another way to customize the Auto DevOps pipeline is by adding it to your own project and then making changes to it.\nBelow you can see a screen snapshot of an Auto DevOps pipeline edit where LICENSE_MANAGEMENT and web PERFORMANCE tests are being disabled.\n\n![autodevops-pipeline-edit](https://about.gitlab.com/images/blogimages/cd-automated-integrated/autodevops-pipeline-edit.png){: .shadow.medium.center.wrap-text}\n\n3) **Customization by using only portions of Auto DevOps**. You could also leverage portions of Auto DevOps in your own pipeline by including specific templates. In the smaller pipeline below, only the Auto Build and Auto Test capabilities of Auto DevOps are being reused.\n\n![autodevops-portions](https://about.gitlab.com/images/blogimages/cd-automated-integrated/autodevops-portions.png){: .shadow.medium.center.wrap-text}\n\nThe power of Auto DevOps automates and integrates your continuous delivery to help speed up your releases by saving you time from having to write your own pipelines. 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Shadow Takeaways from Jacie","Recap of my experience in the CEO Shadow Program.",[709],"Jacie Bandur","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664102/Blog/Hero%20Images/gitlab-values-cover.png","2021-05-18","\n\n{::options parse_block_html=\"true\" /}\n\n\nHi! I’m Jacie Bandur. I completed GitLab’s CEO Shadow program from 2021-04-26 through 2021-05-07. It was a really enlightening experience. I generally work in Learning and Development and consider myself a lifelong learner. I can’t even explain how much I learned in such a short about of time. I learned a lot about the business. I learned a lot about the product. But learned even more about the importance of iteration in everything we do.\n\n### Qualifications to Participate\n\nI wanted to start this off with touching on qualifications to participate in the program.\n\nI am the type of person that has gone through most of my life thinking I’m not qualified for things. I’m not qualified for that job, that promotion, that program. The list goes on and on.\n\nWhen I saw the [CEO Shadow program](/blog/ceo-shadow-impressions-takeaways/) kick off in 2019, I really wanted to participate. I was a little intimidated. Who wouldn’t be, spending 2 weeks with the CEO of any company? But time passed and all the sudden it was 2021 and I had not taken any steps to participating in the program.\n\nIf you are sitting there waiting for someone to tell you that you are qualified to participate in this program, I’m not big on giving “pep talks,” but here’s me telling you - You are qualified for this program. There’s never going to be a good or perfect time to do it. Tell your manager you want to do the CEO Shadow program. Stop waiting. Sign up today.\n\nNote: Take a look at the [eligibility](https://handbook.gitlab.com/handbook/ceo/shadow/#eligibility) section of the CEO Shadow page for more information on signing up.\n\n### Pre-Program Tips\n\nThere are many things recommended for shadows to do pre-program outlined on the CEO Shadow handbook page. As I was going through the program there were things that I thought helped me (or would have helped me).\n\nHere are my top 6 recommendations:\n\n1. Make sure your team knows you will be unavailable for 2 weeks. This isn’t a program that can or should be done alongside your normal day to day work. I found catching up from the 2 weeks away kind of difficult because I was trying to keep up on what was going on and I had a bunch of half done things.\n1. Talk with people who have done the shadow program - schedule at least 3 coffee chats with CEO Shadow Alumni.\n1. Have food that is easy to eat quickly. Sid’s meetings are back to back most days, so you will have small amounts of time to eat throughout the day. Sid does eat during calls, which you are welcome to do, too, but if you are taking notes, it is difficult to eat. And this will make you realize why speedy meetings are so important!\n1. Listen to the [Executive Leadership LinkedIn Learning course](https://www.linkedin.com/learning/executive-leadership/).\n1. Be prepared to ask questions. When doing the program virtually, there isn’t a ton of time for asking questions, so when one would come up, I would add it to a note on my computer and ask if there was ever time with just the shadows and Sid.\n1. Take at least 1 day off after the program. Take even a couple of days off if you can! This is recommended on the handbook page, but I can’t stress this enough.\n\n\n### Takeaways\n\n**Group Conversations**\n\nI’ve been at GitLab for almost 4 years. When I joined, I made it a point to attend as many GC’s as I could. I had gotten out of the habit of attending Group Conversations. After attending them again for 2 weeks, I realized how important they are to understand better what is going on across the business. Everything in the organization is so intertwined. It’s helpful to understand what other teams are working on and succeeding in.\n\n**Feedback**\n\nWe should all be giving and receiving feedback often. We have a whole [handbook page on giving and receiving feedback](https://handbook.gitlab.com/handbook/people-group/guidance-on-feedback/). Read the handbook page and watch the videos, as well. Practice giving feedback. I recommend using the [1-1 agenda](https://handbook.gitlab.com/handbook/leadership/1-1/suggested-agenda-format/) Sid uses, because Feedback is an essential piece of that agenda, and it makes feedback more of a routine thing.\n\n**Biggest Takeaway**\n\nWe have an incredible team here at GitLab, from Engineering to Product to Sales to People and all the groups in between. There are so many great ideas. I observed the constant reinforcement by Sid to start with something small and build on it. You can ALWAYS make something more complex. It’s hard to go back to something more simple when you start with something complex.\n\nA couple of quotes that I heard from Sid during the program that reinforced this point:\n\n- “Every complex system evolves from a simple system that worked.”\n- “It’s very clear what is the simple solution. We can always make it more complicated as we go on.”\n\nI know they are very similar, but they happened in different meetings on different days, so the point was reinforced repeatedly.\n\nDuring the program, I reflected on the projects that I’am working on. How many of them am I trying to do too much on before releasing. Probably all of them. When I’m working on projects in the future, I will break them down into smaller, more doable chunks. Iteration is hard - it’s a skill to be practicing constantly.\n\n\n### Overall\n\nOverall, the program was really insightful and impactful. If you haven’t participated in it yet, I cannot encourage you enough to do so!\n",{"slug":714,"featured":12,"template":13},"ceo-shadow-recap",{"content":716,"config":728},{"title":717,"description":718,"authors":719,"heroImage":721,"date":722,"body":723,"category":9,"tags":724},"Why I love contributing to GitLab","Making small meaningful changes is what it's all about.",[720],"Austin Regnery","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749679501/Blog/Hero%20Images/new-feature.png","2021-05-11","It was mid-morning on a Tuesday in February, and I had 10 minutes in between meetings. So I decided to try and solve a pain point of mine.\nYou see, I had to memorize this HTML snippet to create a collapsible section in GitLab Issue descriptions and comments, but I kept forgetting it. Was it `summary` or `section`? I could never remember.\n```html\n\u003Cdetails>\n\u003Csummary>Insert Title\u003C/summary>\nHidden content\n\u003C/details>\n```\nEven though it is not vanilla Markdown, GitLab knows how to interpret some HTML. I used this formatting trick fairly often since full-page screenshots can occupy a lot of screen space, which leads to excessive scrolling.\nSo I decided to poke around our codebase to see how the other Markdown shortcuts worked. To my surprise, it was pretty straightforward. Each shortcut had a simple text input that mapped to each button. This implementation was simple to replicate since I just needed to copy/paste and replace a few words.\n![Image of Vue and Haml files with editor shortcuts](https://about.gitlab.com/images/blogimages/why-i-love-contributing-to-gitlab/vue-haml.png){: .shadow}\nThe Vue and Haml files with the new shortcut\n\nI started a branch and began hacking away at the code. Now, I would never call myself a Software Engineer, but I like to try and make things from time to time. I was able to add a new shortcut to the toolbar to insert this code snippet for me in less than 10 minutes. No more memorizing! Making contributions like this is what makes working at GitLab so special.\nNow, it wasn't ready for production, but I at least had something that worked. I shared it with my UX colleagues in Slack, and it started to gain traction with several up-votes and few constructive comments on how to make it better.\nWith the functionality flushed out, a few other designers helped me get a better icon added to our SVG library. Using clear iconography is critical for communicating information more clearly.\n| Initial Icon | Final Icon |\n| - | - |\n| ![SVG of chevron right icon](https://about.gitlab.com/images/blogimages/why-i-love-contributing-to-gitlab/chevron-right.svg) | ![SVG of details block icon](https://about.gitlab.com/images/blogimages/why-i-love-contributing-to-gitlab/details-block.svg) |\n\nThe last thing to do was resolve my failing tests, and I had several teammates help me do that.\n![Gif of the shortcut being used](https://about.gitlab.com/images/blogimages/why-i-love-contributing-to-gitlab/demo.gif)\n\nToday [this change](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/54938) merged! Now I solved a pain point for me and others. It took a few months to go from idea to production, but the effort was super low. I'd say the return on my initial investment, 10 minutes, is super high.\n> Having a direct impact on a product was never an option for me before joining GitLab.\n\n![Image of participants in the Merge Request](https://about.gitlab.com/images/blogimages/why-i-love-contributing-to-gitlab/participants.png)\n\n\nThank you to everyone that helped me deploy this\n",[725,726,727],"UX","product","AWS",{"slug":729,"featured":12,"template":13},"why-i-love-contributing-to-gitlab",{"content":731,"config":743},{"title":732,"description":733,"authors":734,"heroImage":736,"date":722,"body":737,"category":9,"tags":738},"Placebo Lines on the Pipeline Graph","Have you noticed the connecting lines missing on your pipelines lately? Here's why",[735],"Sam Beckham","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749679507/Blog/Hero%20Images/ci-cd.png","\n\n{::options parse_block_html=\"true\" /}\n\n\n\nHave you ever pressed the close door button on the elevator, in the hope that you'll save a few precious seconds?\nOr got frustrated at the person stood next to you at the cross-walk, neglecting to press the button?\nWell, maybe they know something you don't, or perhaps you know this already.\nMany buttons in our society lie to us.\n[David McRaney](https://youarenotsosmart.com/2010/02/10/placebo-buttons/) dubbed these, \"Placebo buttons\" and they're everywhere.\nThose elevator doors won't close any faster and the cross-walk button has no effect on the lights.\nThe only lights they control are the lights on the buttons themselves.\nThey give you the feedback you crave, but that's all they're doing.\n\nThese placebos aren't constrained to the physical world, they're prevalent in [UI design](/blog/the-evolution-of-ux-at-gitlab/) too.\nFrom literal placebo buttons like [YouTube's downvote](https://www.quora.com/Does-downvoting-a-comment-on-YouTube-even-do-anything), to more subtle effects like Instagram always [pretending to work](https://www.fastcompany.com/1669788/the-3-white-lies-behind-instagrams-lightning-speed), or progress bars that have a [fixed animation](https://www.theatlantic.com/technology/archive/2017/02/why-some-apps-use-fake-progress-bars/517233/).\nThey're everywhere if you know where to look.\n\nAt GitLab, we created a placebo of our own in one of our core features; the pipeline graph.\n\nThose of you who have used our pipeline graph, will be familiar with its appearance.\nThere's a series of jobs, grouped by stages, connected by a series of lines depicting the relationships between the jobs.\nBut these lines might be lying to you.\nThese lines are indiscriminately drawn between each job in a stage, regardless of their relationship.\nThese lines are placebos.\n\n![The old pipeline rendering with lines connecting every job in a stage](https://about.gitlab.com/images/blogimages/placebo-lines_old-graph.png)\n\nThis wasn't a problem to begin with.\nA basic pipeline has several jobs across a handful of stages.\nJobs in each stage would run parallel to each other, but each stage would run sequentially.\nIn the image shown above, all the jobs in the test stage would trigger at the same time. Once those jobs had finished, all the jobs in the build stage would trigger.\nWe used rudimentary CSS to draw lines connecting each job in one stage to each job in the next.\nThese lines weren't calculated based on their connections, but still reflected the story they were telling.\n\nSince the introduction of `needs` relationships in [v12.2](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/47063), pipelines got a bit more complicated.\nNow you could configure a job in a later stage to trigger as soon as a job in an earlier stage completed.\nLooking at our old example, we could set the API deployment to run as soon as our spec tests passed.\nThis skips the remaining tests and the entire build stage, turning our lines into pretty little liars.\n\nWe had many internal discussions about these lines, and how to show the relationships between jobs.\nThere's the [`needs` visualization](https://docs.gitlab.com/ee/ci/directed_acyclic_graph/#needs-visualization), which does an excellent job of displaying these relationships, but the main pipeline graph was still inaccurate.\nFor the past few months, we've been [refactoring the pipeline graph](https://gitlab.com/gitlab-org/gitlab/-/issues/276949), giving it a new lease of life and fixing some of its issues along the way.\nOne of those issues were the faked lines.\nIn the new version, we can accurately draw lines between jobs.\nLines that actually depict the relationships jobs have with each other.\nNow the lines no-longer lie!\n\n![The newer pipeline graph showing the correct needs links between jobs](https://about.gitlab.com/images/blogimages/placebo-lines_new-graph.png)\n\nThe above image shows an unreleased version of the pipeline graph.\nYou can see the lines drawn between the jobs to show that the `deploy:API` job can start as soon as the `rspec` job is successful.\nSomething the old lines (shown earlier in this post) would have been unable to depict.\n\nOne unfortunate downside of this is that these lines can be quite expensive to calculate.\nThey're actual DOM nodes, drawn deliberately and placed precisely.\nOn smaller graphs this isn't a problem, but some of our initial tests have found pipelines with a potential 8000+ job connections.\nThat kind of calculation would grind the browser to a halt, and nobody wants that.\n\nAt GitLab, we believe in boring solutions.\nWe make the simple change that sets us on the path towards where we want to be.\nShip it, get feedback, and iterate.\nSo that's what we did.\nIn the first phase of this rollout, we shipped the new pipeline graph with no lines connecting the jobs.\nWe don't have to worry about the expensive calculations, and we still get to roll out the refactored pipeline graph.\n\n![The current (v13.11) pipeline graph showing no links between jobs](https://about.gitlab.com/images/blogimages/placebo-lines_current-graph.png)\n\nWe know some of you will miss them, but fear not.\nBoring solutions are just technical debt if you don't iterate on them.\nSo the [improved lines are coming](https://gitlab.com/groups/gitlab-org/-/epics/4509) in a future release, along with several other improvements to the pipeline graph.\nWe're already starting to roll out the new [Job Dependencies](https://gitlab.com/gitlab-org/gitlab/-/issues/298973) view which shows the jobs in a (much closer to) execution order.\nStay tuned for more updates, and watch [Sarah Groff Hennigh Palermo's talk](https://www.youtube.com/watch?v=R2EKqKjB7OQ) for the technical side of this effort and a deeper dive into some of the decisions we made.\n",[739,740,741,742],"CI","frontend","agile","design",{"slug":744,"featured":12,"template":13},"placebo-lines-on-the-pipeline-graph",{"promotions":746},[747,761,772],{"id":748,"categories":749,"header":751,"text":752,"button":753,"image":758},"ai-modernization",[750],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":754,"config":755},"Get your AI maturity 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