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張 旭

Choose when to run jobs | GitLab - 0 views

  • Rules are evaluated in order until the first match.
  • no rules match, so the job is not added to any other pipeline.
  • define a set of rules to exclude jobs in a few cases, but run them in all other cases
  • ...32 more annotations...
  • use all rules keywords, like if, changes, and exists, in the same rule. The rule evaluates to true only when all included keywords evaluate to true.
  • use parentheses with && and || to build more complicated variable expressions.
  • Use workflow to specify which types of pipelines can run.
  • every push to an open merge request’s source branch causes duplicated pipelines.
  • avoid duplicate pipelines by changing the job rules to avoid either push (branch) pipelines or merge request pipelines.
  • do not mix only/except jobs with rules jobs in the same pipeline.
  • For behavior similar to the only/except keywords, you can check the value of the $CI_PIPELINE_SOURCE variable
  • commonly used variables for if clauses
  • rules:changes expressions to determine when to add jobs to a pipeline
  • Use !reference tags to reuse rules in different jobs.
  • Use except to define when a job does not run.
  • only or except used without refs is the same as only:refs / except/refs
  • If you change multiple files, but only one file ends in .md, the build job is still skipped.
  • If you use multiple keywords with only or except, the keywords are evaluated as a single conjoined expression.
  • only includes the job if all of the keys have at least one condition that matches.
  • except excludes the job if any of the keys have at least one condition that matches.
  • With only, individual keys are logically joined by an AND
  • With except, individual keys are logically joined by an OR
  • To specify a job as manual, add when: manual to the job in the .gitlab-ci.yml file.
  • Use protected environments to define a list of users authorized to run a manual job.
  • Use when: delayed to execute scripts after a waiting period, or if you want to avoid jobs immediately entering the pending state.
  • To split a large job into multiple smaller jobs that run in parallel, use the parallel keyword
  • run a trigger job multiple times in parallel in a single pipeline, but with different variable values for each instance of the job.
  • The @ symbol denotes the beginning of a ref’s repository path. To match a ref name that contains the @ character in a regular expression, you must use the hex character code match \x40.
  • Compare a variable to a string
  • Check if a variable is undefined
  • Check if a variable is empty
  • Check if a variable exists
  • Check if a variable is empty
  • Matches are found when using =~.
  • Matches are not found when using !~.
  • Join variable expressions together with && or ||
  •  
    "Rules are evaluated in order until the first match."
張 旭

Auto DevOps | GitLab - 0 views

  • Auto DevOps provides pre-defined CI/CD configuration which allows you to automatically detect, build, test, deploy, and monitor your applications
  • Just push your code and GitLab takes care of everything else.
  • Auto DevOps will be automatically disabled on the first pipeline failure.
  • ...78 more annotations...
  • Your project will continue to use an alternative CI/CD configuration file if one is found
  • Auto DevOps works with any Kubernetes cluster;
  • using the Docker or Kubernetes executor, with privileged mode enabled.
  • Base domain (needed for Auto Review Apps and Auto Deploy)
  • Kubernetes (needed for Auto Review Apps, Auto Deploy, and Auto Monitoring)
  • Prometheus (needed for Auto Monitoring)
  • scrape your Kubernetes cluster.
  • project level as a variable: KUBE_INGRESS_BASE_DOMAIN
  • A wildcard DNS A record matching the base domain(s) is required
  • Once set up, all requests will hit the load balancer, which in turn will route them to the Kubernetes pods that run your application(s).
  • review/ (every environment starting with review/)
  • staging
  • production
  • need to define a separate KUBE_INGRESS_BASE_DOMAIN variable for all the above based on the environment.
  • Continuous deployment to production: Enables Auto Deploy with master branch directly deployed to production.
  • Continuous deployment to production using timed incremental rollout
  • Automatic deployment to staging, manual deployment to production
  • Auto Build creates a build of the application using an existing Dockerfile or Heroku buildpacks.
  • If a project’s repository contains a Dockerfile, Auto Build will use docker build to create a Docker image.
  • Each buildpack requires certain files to be in your project’s repository for Auto Build to successfully build your application.
  • Auto Test automatically runs the appropriate tests for your application using Herokuish and Heroku buildpacks by analyzing your project to detect the language and framework.
  • Auto Code Quality uses the Code Quality image to run static analysis and other code checks on the current code.
  • Static Application Security Testing (SAST) uses the SAST Docker image to run static analysis on the current code and checks for potential security issues.
  • Dependency Scanning uses the Dependency Scanning Docker image to run analysis on the project dependencies and checks for potential security issues.
  • License Management uses the License Management Docker image to search the project dependencies for their license.
  • Vulnerability Static Analysis for containers uses Clair to run static analysis on a Docker image and checks for potential security issues.
  • Review Apps are temporary application environments based on the branch’s code so developers, designers, QA, product managers, and other reviewers can actually see and interact with code changes as part of the review process. Auto Review Apps create a Review App for each branch. Auto Review Apps will deploy your app to your Kubernetes cluster only. When no cluster is available, no deployment will occur.
  • The Review App will have a unique URL based on the project ID, the branch or tag name, and a unique number, combined with the Auto DevOps base domain.
  • Review apps are deployed using the auto-deploy-app chart with Helm, which can be customized.
  • Your apps should not be manipulated outside of Helm (using Kubernetes directly).
  • Dynamic Application Security Testing (DAST) uses the popular open source tool OWASP ZAProxy to perform an analysis on the current code and checks for potential security issues.
  • Auto Browser Performance Testing utilizes the Sitespeed.io container to measure the performance of a web page.
  • add the paths to a file named .gitlab-urls.txt in the root directory, one per line.
  • After a branch or merge request is merged into the project’s default branch (usually master), Auto Deploy deploys the application to a production environment in the Kubernetes cluster, with a namespace based on the project name and unique project ID
  • Auto Deploy doesn’t include deployments to staging or canary by default, but the Auto DevOps template contains job definitions for these tasks if you want to enable them.
  • Apps are deployed using the auto-deploy-app chart with Helm.
  • For internal and private projects a GitLab Deploy Token will be automatically created, when Auto DevOps is enabled and the Auto DevOps settings are saved.
  • If the GitLab Deploy Token cannot be found, CI_REGISTRY_PASSWORD is used. Note that CI_REGISTRY_PASSWORD is only valid during deployment.
  • If present, DB_INITIALIZE will be run as a shell command within an application pod as a helm post-install hook.
  • a post-install hook means that if any deploy succeeds, DB_INITIALIZE will not be processed thereafter.
  • DB_MIGRATE will be run as a shell command within an application pod as a helm pre-upgrade hook.
    • 張 旭
       
      如果專案類型不同,就要去查 buildpacks 裡面如何叫用該指令,例如 laravel 的 migration
    • 張 旭
       
      如果是自己的 Dockerfile 建立起來的,看來就不用鳥 buildpacks 的作法
  • Once your application is deployed, Auto Monitoring makes it possible to monitor your application’s server and response metrics right out of the box.
  • annotate the NGINX Ingress deployment to be scraped by Prometheus using prometheus.io/scrape: "true" and prometheus.io/port: "10254"
  • If you are also using Auto Review Apps and Auto Deploy and choose to provide your own Dockerfile, make sure you expose your application to port 5000 as this is the port assumed by the default Helm chart.
  • While Auto DevOps provides great defaults to get you started, you can customize almost everything to fit your needs; from custom buildpacks, to Dockerfiles, Helm charts, or even copying the complete CI/CD configuration into your project to enable staging and canary deployments, and more.
  • If your project has a Dockerfile in the root of the project repo, Auto DevOps will build a Docker image based on the Dockerfile rather than using buildpacks.
  • Auto DevOps uses Helm to deploy your application to Kubernetes.
  • Bundled chart - If your project has a ./chart directory with a Chart.yaml file in it, Auto DevOps will detect the chart and use it instead of the default one.
  • Create a project variable AUTO_DEVOPS_CHART with the URL of a custom chart to use or create two project variables AUTO_DEVOPS_CHART_REPOSITORY with the URL of a custom chart repository and AUTO_DEVOPS_CHART with the path to the chart.
  • make use of the HELM_UPGRADE_EXTRA_ARGS environment variable to override the default values in the values.yaml file in the default Helm chart.
  • specify the use of a custom Helm chart per environment by scoping the environment variable to the desired environment.
    • 張 旭
       
      Auto DevOps 就是一套人家寫好好的傳便便的 .gitlab-ci.yml
  • Your additions will be merged with the Auto DevOps template using the behaviour described for include
  • copy and paste the contents of the Auto DevOps template into your project and edit this as needed.
  • In order to support applications that require a database, PostgreSQL is provisioned by default.
  • Set up the replica variables using a project variable and scale your application by just redeploying it!
  • You should not scale your application using Kubernetes directly.
  • Some applications need to define secret variables that are accessible by the deployed application.
  • Auto DevOps detects variables where the key starts with K8S_SECRET_ and make these prefixed variables available to the deployed application, as environment variables.
  • Auto DevOps pipelines will take your application secret variables to populate a Kubernetes secret.
  • Environment variables are generally considered immutable in a Kubernetes pod.
  • if you update an application secret without changing any code then manually create a new pipeline, you will find that any running application pods will not have the updated secrets.
  • Variables with multiline values are not currently supported
  • The normal behavior of Auto DevOps is to use Continuous Deployment, pushing automatically to the production environment every time a new pipeline is run on the default branch.
  • If STAGING_ENABLED is defined in your project (e.g., set STAGING_ENABLED to 1 as a CI/CD variable), then the application will be automatically deployed to a staging environment, and a production_manual job will be created for you when you’re ready to manually deploy to production.
  • If CANARY_ENABLED is defined in your project (e.g., set CANARY_ENABLED to 1 as a CI/CD variable) then two manual jobs will be created: canary which will deploy the application to the canary environment production_manual which is to be used by you when you’re ready to manually deploy to production.
  • If INCREMENTAL_ROLLOUT_MODE is set to manual in your project, then instead of the standard production job, 4 different manual jobs will be created: rollout 10% rollout 25% rollout 50% rollout 100%
  • The percentage is based on the REPLICAS variable and defines the number of pods you want to have for your deployment.
  • To start a job, click on the play icon next to the job’s name.
  • Once you get to 100%, you cannot scale down, and you’d have to roll back by redeploying the old version using the rollback button in the environment page.
  • With INCREMENTAL_ROLLOUT_MODE set to manual and with STAGING_ENABLED
  • not all buildpacks support Auto Test yet
  • When a project has been marked as private, GitLab’s Container Registry requires authentication when downloading containers.
  • Authentication credentials will be valid while the pipeline is running, allowing for a successful initial deployment.
  • After the pipeline completes, Kubernetes will no longer be able to access the Container Registry.
  • We strongly advise using GitLab Container Registry with Auto DevOps in order to simplify configuration and prevent any unforeseen issues.
張 旭

The Asset Pipeline - Ruby on Rails Guides - 0 views

  • provides a framework to concatenate and minify or compress JavaScript and CSS assets
  • adds the ability to write these assets in other languages and pre-processors such as CoffeeScript, Sass and ERB
  • invalidate the cache by altering this fingerprint
  • ...80 more annotations...
  • Rails 4 automatically adds the sass-rails, coffee-rails and uglifier gems to your Gemfile
  • reduce the number of requests that a browser makes to render a web page
  • Starting with version 3.1, Rails defaults to concatenating all JavaScript files into one master .js file and all CSS files into one master .css file
  • In production, Rails inserts an MD5 fingerprint into each filename so that the file is cached by the web browser
  • The technique sprockets uses for fingerprinting is to insert a hash of the content into the name, usually at the end.
  • asset minification or compression
  • The sass-rails gem is automatically used for CSS compression if included in Gemfile and no config.assets.css_compressor option is set.
  • Supported languages include Sass for CSS, CoffeeScript for JavaScript, and ERB for both by default.
  • When a filename is unique and based on its content, HTTP headers can be set to encourage caches everywhere (whether at CDNs, at ISPs, in networking equipment, or in web browsers) to keep their own copy of the content
  • asset pipeline is technically no longer a core feature of Rails 4
  • Rails uses for fingerprinting is to insert a hash of the content into the name, usually at the end
  • With the asset pipeline, the preferred location for these assets is now the app/assets directory.
  • Fingerprinting is enabled by default for production and disabled for all other environments
  • The files in app/assets are never served directly in production.
  • Paths are traversed in the order that they occur in the search path
  • You should use app/assets for files that must undergo some pre-processing before they are served.
  • By default .coffee and .scss files will not be precompiled on their own
  • app/assets is for assets that are owned by the application, such as custom images, JavaScript files or stylesheets.
  • lib/assets is for your own libraries' code that doesn't really fit into the scope of the application or those libraries which are shared across applications.
  • vendor/assets is for assets that are owned by outside entities, such as code for JavaScript plugins and CSS frameworks.
  • Any path under assets/* will be searched
  • By default these files will be ready to use by your application immediately using the require_tree directive.
  • By default, this means the files in app/assets take precedence, and will mask corresponding paths in lib and vendor
  • Sprockets uses files named index (with the relevant extensions) for a special purpose
  • Rails.application.config.assets.paths
  • causes turbolinks to check if an asset has been updated and if so loads it into the page
  • if you add an erb extension to a CSS asset (for example, application.css.erb), then helpers like asset_path are available in your CSS rules
  • If you add an erb extension to a JavaScript asset, making it something such as application.js.erb, then you can use the asset_path helper in your JavaScript code
  • The asset pipeline automatically evaluates ERB
  • data URI — a method of embedding the image data directly into the CSS file — you can use the asset_data_uri helper.
  • Sprockets will also look through the paths specified in config.assets.paths, which includes the standard application paths and any paths added by Rails engines.
  • image_tag
  • the closing tag cannot be of the style -%>
  • asset_data_uri
  • app/assets/javascripts/application.js
  • sass-rails provides -url and -path helpers (hyphenated in Sass, underscored in Ruby) for the following asset classes: image, font, video, audio, JavaScript and stylesheet.
  • Rails.application.config.assets.compress
  • In JavaScript files, the directives begin with //=
  • The require_tree directive tells Sprockets to recursively include all JavaScript files in the specified directory into the output.
  • manifest files contain directives — instructions that tell Sprockets which files to require in order to build a single CSS or JavaScript file.
  • You should not rely on any particular order among those
  • Sprockets uses manifest files to determine which assets to include and serve.
  • the family of require directives prevents files from being included twice in the output
  • which files to require in order to build a single CSS or JavaScript file
  • Directives are processed top to bottom, but the order in which files are included by require_tree is unspecified.
  • In JavaScript files, Sprockets directives begin with //=
  • If require_self is called more than once, only the last call is respected.
  • require directive is used to tell Sprockets the files you wish to require.
  • You need not supply the extensions explicitly. Sprockets assumes you are requiring a .js file when done from within a .js file
  • paths must be specified relative to the manifest file
  • require_directory
  • Rails 4 creates both app/assets/javascripts/application.js and app/assets/stylesheets/application.css regardless of whether the --skip-sprockets option is used when creating a new rails application.
  • The file extensions used on an asset determine what preprocessing is applied.
  • app/assets/stylesheets/application.css
  • Additional layers of preprocessing can be requested by adding other extensions, where each extension is processed in a right-to-left manner
  • require_self
  • use the Sass @import rule instead of these Sprockets directives.
  • Keep in mind that the order of these preprocessors is important
  • In development mode, assets are served as separate files in the order they are specified in the manifest file.
  • when these files are requested they are processed by the processors provided by the coffee-script and sass gems and then sent back to the browser as JavaScript and CSS respectively.
  • css.scss.erb
  • js.coffee.erb
  • Keep in mind the order of these preprocessors is important.
  • By default Rails assumes that assets have been precompiled and will be served as static assets by your web server
  • with the Asset Pipeline the :cache and :concat options aren't used anymore
  • Assets are compiled and cached on the first request after the server is started
  • RAILS_ENV=production bundle exec rake assets:precompile
  • Debug mode can also be enabled in Rails helper methods
  • If you set config.assets.initialize_on_precompile to false, be sure to test rake assets:precompile locally before deploying
  • By default Rails assumes assets have been precompiled and will be served as static assets by your web server.
  • a rake task to compile the asset manifests and other files in the pipeline
  • RAILS_ENV=production bin/rake assets:precompile
  • a recipe to handle this in deployment
  • links the folder specified in config.assets.prefix to shared/assets
  • config/initializers/assets.rb
  • The initialize_on_precompile change tells the precompile task to run without invoking Rails
  • The X-Sendfile header is a directive to the web server to ignore the response from the application, and instead serve a specified file from disk
  • the jquery-rails gem which comes with Rails as the standard JavaScript library gem.
  • Possible options for JavaScript compression are :closure, :uglifier and :yui
  • concatenate assets
張 旭

Asset Pipeline - Ruby on Rails 指南 - 0 views

  • 清单文件或帮助方法
    • 張 旭
       
      清單文件是指:application.css 跟 application.js
  • Sprockets 会按照搜索路径中各路径出现的顺序进行搜索。默认情况下,这意味着 app/assets 文件夹中的静态资源优先级较高,会遮盖 lib 和 vendor 文件夹中的相应文件
  • 如果静态资源不会在清单文件中引入,就要添加到预编译的文件列表中,否则在生产环境中就无法访问文件。
  • ...36 more annotations...
  • 程序中使用了 jQuery 代码库和许多模块,都保存在 lib/assets/javascripts/library_name 文件夹中,那么 lib/assets/javascripts/library_name/index.js 文件的作用就是这个代码库的清单。清单文件中可以按顺序列出所需的文件,或者干脆使用 require_tree 指令。
  • 如果使用 Turbolinks(Rails 4 默认启用),加上 data-turbolinks-track 选项后,Turbolinks 会检查静态资源是否有更新,如果更新了就会将其载入页面
  • config.assets.paths 包含标准路径和其他 Rails 引擎添加的路径。
  • 链接不存在的资源(也包括链接到空字符串的情况)会在调用页面抛出异常。
  • 关闭标签不能使用 -%> 形式
  • Sprockets 通过清单文件决定要引入和伺服哪些静态资源
  • 在 JavaScript 文件中,Sprockets 的指令以 //= 开头。在上面的文件中,用到了 require 和 the require_tree 指令。
  • app/assets/javascripts/application.js
  • require_tree 指令告知 Sprockets 递归引入指定文件夹中的所有 JavaScript 文件。文件夹的路径必须相对于清单文件。也可使用 require_directory 指令加载指定文件夹中的所有 JavaScript 文件,但不会递归。
  • Sprockets 会按照从上至下的顺序处理指令,但 require_tree 引入的文件顺序是不可预期的,不要设想能得到一个期望的顺序。
  • app/assets/stylesheets/application.css
  • 不管创建新程序时有没有指定 --skip-sprockets 选项,Rails 4 都会生成 app/assets/javascripts/application.js 和 app/assets/stylesheets/application.css
  • 如果多次调用 require_self,只有最后一次调用有效
  • 如果想使用多个 Sass 文件,应该使用 Sass 中的 @import 规则,不要使用 Sprockets 指令。
  • 清单文件可以有多个。
  • 如果使用默认的 gem,生成控制器或脚手架时,会生成 CoffeeScript 和 SCSS 文件,而不是普通的 JavaScript 和 CSS 文件。
  • 在开发环境中,或者禁用 Asset Pipeline 时,这些文件会使用 coffee-script 和 sass 提供的预处理器处理,然后再发给浏览器
  • 启用 Asset Pipeline 时,这些文件会先使用预处理器处理,然后保存到 public/assets 文件夹中,再由 Rails 程序或网页服务器伺服
  • 添加额外的扩展名可以增加预处理次数,预处理程序会按照扩展名从右至左的顺序处理文件内容。所以,扩展名的顺序要和处理的顺序一致
  • 预处理器的执行顺序很重要
  • 在开发环境中也可启用压缩功能,检查是否能正常运行。需要调试时再禁用压缩即可。
  • 默认情况下,Rails 认为静态资源已经事先编译好了,直接由网页服务器伺服。
  • 般情况下,请勿修改 config.assets.digest 的默认值
  • 可在部署时编译静态资源
  • 在多次部署之间共用这个文件夹是十分重要的,这样只要缓存的页面可用,其中引用的编译后的静态资源就能正常使用。
  • 默认编译的文件包括 application.js、application.css 以及 gem 中 app/assets 文件夹中的所有非 JS/CSS 文件(会自动加载所有图片)
  • 如果想编译其他清单,或者单独的样式表和 JavaScript,可以添加到 config/application.rb 文件中的 precompile 选项
  • 设置编译所有静态资源
  • manifest-md5hash.json 的文件,列出所有静态资源和对应的指纹
  • 把 Expires 报头设置为很久以后
  • 在本地预编译后,可以把编译好的文件纳入版本控制系统,再按照常规的方式部署
  • 实时编译消耗的内存更多,比默认的编译方式性能更低,因此不推荐使用
  • 如果用 CDN 分发静态资源,要确保文件不会被缓存,因为缓存会导致问题。如果设置了 config.action_controller.perform_caching = true,Rack::Cache 会使用 Rails.cache 存储静态文件,很快缓存空间就会用完。
  • Sprockets 默认使用的公开路径是 /assets
  • X-Sendfile 报头的作用是让服务器忽略程序的响应,直接从硬盘上伺服指定的文件
  • 为 Rails 提供标准 JavaScript 代码库的 jquery-rails gem 是个很好的例子。这个 gem 中有个引擎类,继承自 Rails::Engine。添加这层继承关系后,Rails 就知道这个 gem 中可能包含静态资源文件,会把这个引擎中的 app/assets、lib/assets 和 vendor/assets 三个文件夹加入 Sprockets 的搜索路径中。
crazylion lee

EntilZha/ScalaFunctional - 0 views

  •  
    "Python library for creating working with data in a pipeline/LINQ/functional programming way"
crazylion lee

GitHub - checkr/codeflow: Open-source deployment pipeline from the future - 0 views

  •  
    "Open-source deployment pipeline from the future"
張 旭

GitLab Auto DevOps 深入淺出,自動部署,連設定檔不用?! | 五倍紅寶石・專業程式教育 - 0 views

  • 一個 K8S 的 Cluster,Auto DevOps 將會把網站部署到這個 Cluster
  • 需要有一個 wildcard 的 DNS 讓部署在這個環境的網站有 Domain name
  • 一個可以跑 Docker 的 GitLab Runner,將會為由它來執行 CI / CD 的流程。
  • ...37 more annotations...
  • 其實 Auto DevOps 就是一份官方寫好的 gitlab-ci.yml,在啟動 Auto DevOps 的專案裡,如果找不到 gitlab-ci.yml 檔,那就會直接用官方 gitlab-ci.yml 去跑 CI / CD 流程。
  • Pod 是 K8S 中可以被部署的最小元件,一個 Pod 是由一到多個 Container 組成,同個 Pod 的不同 Container 之間彼此共享網路資源。
  • 每個 Pod 都會有它的 yaml 檔,用以描述 Pod 會使用的 Image 還有連接的 Port 等資訊。
  • Node 又分成 Worker Node 和 Master Node 兩種
  • Helm 透過參數 (parameter) 跟模板 (template) 的方式,讓我們可以在只修改參數的方式重複利用模板。
  • 為了要有 CI CD 的功能我們會把 .gitlab-ci.yml 放在專案的根目錄裡, GitLab 會依造 .gitlab-ci.yml 的設定產生 CI/CD Pipeline,每個 Pipeline 裡面可能有多個 Job,這時候就會需要有 GitLab Runner 來執行這些 Job 並把執行的結果回傳給 GitLab 讓它知道這個 Job 是否有正常執行。
  • 把專案打包成 Docker Image 這工作又或是 helm 的操作都會在 Container 內執行
  • CI/CD Pipeline 是由 stage 還有 job 組成的,stage 是有順序性的,前面的 stage 完成後才會開始下一個 stage。
  • 每個 stage 裡面包含一到多個 Job
  • Auto Devops 裡也會大量用到這種在指定 Container 內運行的工作。
  • 可以通過 health checks
  • 開 private 的話還要注意使用 Container Registry 的權限問題
  • 申請好的 wildcard 的 DNS
  • Auto Devops 也提供只要設定環境變數就能一定程度客製化的選項
  • 特別注意 namespace 有沒有設定對,不然會找不到資料喔
  • Auto Devops,如果想要進一步的客製化,而且是改 GitLab 環境變數都無法實現的客製化,這時候還是得回到 .gitlab-ci.yml 設定檔
  • 在 Docker in Docker 的環境用 Dockerfile 打包 Image
  • 用 helm upgrade 把 chart 部署到 K8S 上
  • GitLab CI 的環境變數主要有三個來源,優先度高到低依序為Settings > CI/CD 介面定義的變數gitlab_ci.yml 定義環境變數GitLab 預設環境變數
  • 把專案打包成 Docker Image 首先需要在專案下新增一份 Dockerfile
  • Auto Devops 裡面的做法,用 herokuish 提供的 Image 來打包專案
  • 在 Runner 的環境中是沒有 docker 指令可以用的,所以這邊啟動一個 Docker Container 在裡面執行就可以用 docker 指令了。
  • 其中 $CI_COMMIT_SHA $CI_COMMIT_BEFORE_SHA 這兩個都是 GitLab 預設環境變數,代表這次 commit 還有上次 commit 的 SHA 值。
  • dind 則是直接啟動 docker daemon,此外 dind 還會自動產生 TLS certificates
  • 為了在 Docker Container 內運行 Docker,會把 Host 上面的 Docker API 分享給 Container。
  • docker:stable 有執行 docker 需要的執行檔,他裡面也包含要啟動 docker 的程式(docker daemon),但啟動 Container 的 entrypoint 是 sh
  • docker:dind 繼承自 docker:stable,而且它 entrypoint 就是啟動 docker 的腳本,此外還會做完 TLS certificates
  • Container 要去連 Host 上的 Docker API 。但現在連線失敗卻是找 http://docker:2375,現在的 dind 已經不是被當做 services 來用了,而是要直接在裡面跑 Docker,所以他應該是要 unix:///var/run/docker.sock 用這種連線,於是把環境變數 DOCKER_HOST 從 tcp://docker:2375 改成空字串,讓 docker daemon 走預設連線就能成功囉!
  • auto-deploy preparationhelm init 建立 helm 專案設定 tiller 在背景執行設定 cluster 的 namespace
  • auto-deploy deploy使用 helm upgrade 部署 chart 到 K8S 上透過 --set 來設定要注入 template 的參數
  • set -x,這樣就能在執行前,顯示指令內容。
  • 用 helm repo list 看看現在有註冊哪些 Chart Repository
  • helm fetch gitlab/auto-deploy-app --untar
  • nohup 可以讓你在離線或登出系統後,還能夠讓工作繼續進行
  • 在不特別設定 CI_APPLICATION_REPOSITORY 的情況下,image_repository 的值就是預設環境變數 CI_REGISTRY_IMAGE/CI_COMMIT_REF_SLUG
  • A:-B 的意思是如果有 A 就用它,沒有就用 B
  • 研究 Auto Devops 難度最高的地方就是太多工具整合在一起,搞不清楚他們之間的關係,出錯也不知道從何查起
張 旭

Helm | - 0 views

  • Templates generate manifest files, which are YAML-formatted resource descriptions that Kubernetes can understand.
  • service.yaml: A basic manifest for creating a service endpoint for your deployment
  • In Kubernetes, a ConfigMap is simply a container for storing configuration data.
  • ...88 more annotations...
  • deployment.yaml: A basic manifest for creating a Kubernetes deployment
  • using the suffix .yaml for YAML files and .tpl for helpers.
  • It is just fine to put a plain YAML file like this in the templates/ directory.
  • helm get manifest
  • The helm get manifest command takes a release name (full-coral) and prints out all of the Kubernetes resources that were uploaded to the server. Each file begins with --- to indicate the start of a YAML document
  • Names should be unique to a release
  • The name: field is limited to 63 characters because of limitations to the DNS system.
  • release names are limited to 53 characters
  • {{ .Release.Name }}
  • A template directive is enclosed in {{ and }} blocks.
  • The values that are passed into a template can be thought of as namespaced objects, where a dot (.) separates each namespaced element.
  • The leading dot before Release indicates that we start with the top-most namespace for this scope
  • The Release object is one of the built-in objects for Helm
  • When you want to test the template rendering, but not actually install anything, you can use helm install ./mychart --debug --dry-run
  • Using --dry-run will make it easier to test your code, but it won’t ensure that Kubernetes itself will accept the templates you generate.
  • Objects are passed into a template from the template engine.
  • create new objects within your templates
  • Objects can be simple, and have just one value. Or they can contain other objects or functions.
  • Release is one of the top-level objects that you can access in your templates.
  • Release.Namespace: The namespace to be released into (if the manifest doesn’t override)
  • Values: Values passed into the template from the values.yaml file and from user-supplied files. By default, Values is empty.
  • Chart: The contents of the Chart.yaml file.
  • Files: This provides access to all non-special files in a chart.
  • Files.Get is a function for getting a file by name
  • Files.GetBytes is a function for getting the contents of a file as an array of bytes instead of as a string. This is useful for things like images.
  • Template: Contains information about the current template that is being executed
  • BasePath: The namespaced path to the templates directory of the current chart
  • The built-in values always begin with a capital letter.
  • Go’s naming convention
  • use only initial lower case letters in order to distinguish local names from those built-in.
  • If this is a subchart, the values.yaml file of a parent chart
  • Individual parameters passed with --set
  • values.yaml is the default, which can be overridden by a parent chart’s values.yaml, which can in turn be overridden by a user-supplied values file, which can in turn be overridden by --set parameters.
  • While structuring data this way is possible, the recommendation is that you keep your values trees shallow, favoring flatness.
  • If you need to delete a key from the default values, you may override the value of the key to be null, in which case Helm will remove the key from the overridden values merge.
  • Kubernetes would then fail because you can not declare more than one livenessProbe handler.
  • When injecting strings from the .Values object into the template, we ought to quote these strings.
  • quote
  • Template functions follow the syntax functionName arg1 arg2...
  • While we talk about the “Helm template language” as if it is Helm-specific, it is actually a combination of the Go template language, some extra functions, and a variety of wrappers to expose certain objects to the templates.
  • Drawing on a concept from UNIX, pipelines are a tool for chaining together a series of template commands to compactly express a series of transformations.
  • pipelines are an efficient way of getting several things done in sequence
  • The repeat function will echo the given string the given number of times
  • default DEFAULT_VALUE GIVEN_VALUE. This function allows you to specify a default value inside of the template, in case the value is omitted.
  • all static default values should live in the values.yaml, and should not be repeated using the default command
  • Operators are implemented as functions that return a boolean value.
  • To use eq, ne, lt, gt, and, or, not etcetera place the operator at the front of the statement followed by its parameters just as you would a function.
  • if and
  • if or
  • with to specify a scope
  • range, which provides a “for each”-style loop
  • block declares a special kind of fillable template area
  • A pipeline is evaluated as false if the value is: a boolean false a numeric zero an empty string a nil (empty or null) an empty collection (map, slice, tuple, dict, array)
  • incorrect YAML because of the whitespacing
  • When the template engine runs, it removes the contents inside of {{ and }}, but it leaves the remaining whitespace exactly as is.
  • {{- (with the dash and space added) indicates that whitespace should be chomped left, while -}} means whitespace to the right should be consumed.
  • Newlines are whitespace!
  • an * at the end of the line indicates a newline character that would be removed
  • Be careful with the chomping modifiers.
  • the indent function
  • Scopes can be changed. with can allow you to set the current scope (.) to a particular object.
  • Inside of the restricted scope, you will not be able to access the other objects from the parent scope.
  • range
  • The range function will “range over” (iterate through) the pizzaToppings list.
  • Just like with sets the scope of ., so does a range operator.
  • The toppings: |- line is declaring a multi-line string.
  • not a YAML list. It’s a big string.
  • the data in ConfigMaps data is composed of key/value pairs, where both the key and the value are simple strings.
  • The |- marker in YAML takes a multi-line string.
  • range can be used to iterate over collections that have a key and a value (like a map or dict).
  • In Helm templates, a variable is a named reference to another object. It follows the form $name
  • Variables are assigned with a special assignment operator: :=
  • {{- $relname := .Release.Name -}}
  • capture both the index and the value
  • the integer index (starting from zero) to $index and the value to $topping
  • For data structures that have both a key and a value, we can use range to get both
  • Variables are normally not “global”. They are scoped to the block in which they are declared.
  • one variable that is always global - $ - this variable will always point to the root context.
  • $.
  • $.
  • Helm template language is its ability to declare multiple templates and use them together.
  • A named template (sometimes called a partial or a subtemplate) is simply a template defined inside of a file, and given a name.
  • when naming templates: template names are global.
  • If you declare two templates with the same name, whichever one is loaded last will be the one used.
  • you should be careful to name your templates with chart-specific names.
  • templates in subcharts are compiled together with top-level templates
  • naming convention is to prefix each defined template with the name of the chart: {{ define "mychart.labels" }}
  • Helm has over 60 available functions.
張 旭

Helm | Template Functions and Pipelines - 0 views

  • When injecting strings from the .Values object into the template, we ought to quote these strings.
  • Helm has over 60 available functions. Some of them are defined by the Go template language itself. Most of the others are part of the Sprig template library
  • the "Helm template language" as if it is Helm-specific, it is actually a combination of the Go template language, some extra functions, and a variety of wrappers to expose certain objects to the templates.
  • ...10 more annotations...
  • Drawing on a concept from UNIX, pipelines are a tool for chaining together a series of template commands to compactly express a series of transformations.
  • the default function: default DEFAULT_VALUE GIVEN_VALUE
  • all static default values should live in the values.yaml, and should not be repeated using the default command (otherwise they would be redundant).
  • the default command is perfect for computed values, which can not be declared inside values.yaml.
  • When lookup returns an object, it will return a dictionary.
  • The synopsis of the lookup function is lookup apiVersion, kind, namespace, name -> resource or resource list
  • When no object is found, an empty value is returned. This can be used to check for the existence of an object.
  • The lookup function uses Helm's existing Kubernetes connection configuration to query Kubernetes.
  • Helm is not supposed to contact the Kubernetes API Server during a helm template or a helm install|update|delete|rollback --dry-run, so the lookup function will return an empty list (i.e. dict) in such a case.
  • the operators (eq, ne, lt, gt, and, or and so on) are all implemented as functions. In pipelines, operations can be grouped with parentheses ((, and )).
  •  
    "When injecting strings from the .Values object into the template, we ought to quote these strings. "
張 旭

Optimizing Gitlab pipelines - Basics (1) | PrinsFrank.nl - 0 views

  • When you use specific docker image, make sure you have the Dependency Proxy enabled so the image doesn’t have to be downloaded again for every job.
  • stages are used to group items that can run at the same time.
  • Instead of waiting for all jobs to finish, you can mark jobs as interruptible which signals a job to cancel when a new pipeline starts for the same branch
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  • mark all jobs as interruptible as it doesn’t make sense to wait for builds and tests based on old information.
  • Deployment jobs are the main exception as they should probably finish.
  • only running it when specific files have changed
  • To prevent the ‘vendor’ and ‘node_modules’ folder from being regenerated in every job, we can configure a build job for composer and npm assets.
  • To share assets between multiple stages, Gitlab has caches and artifacts. For dependencies we should use caches.
  • The pull-push policy is the default, but specified here for clarity.
  • All consecutive runs for the build step with the same ‘composer.lock’ file don’t update the cache.
  • composer prevents this by caching packages in a global package cache,
crazylion lee

Blue Ocean - 0 views

  •  
    " Blue Ocean is a new project that rethinks the user experience of Jenkins. Designed from the ground up for Jenkins Pipeline and compatible with Freestyle jobs, Blue Ocean reduces clutter and increases clarity for every member of your team through the following key features:"
張 旭

What is DevOps? | Atlassian - 0 views

  • DevOps is a set of practices that automates the processes between software development and IT teams, in order that they can build, test, and release software faster and more reliably.
  • increased trust, faster software releases, ability to solve critical issues quickly, and better manage unplanned work.
  • bringing together the best of software development and IT operations.
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  • DevOps is a culture, a movement, a philosophy.
  • a firm handshake between development and operations
  • DevOps isn’t magic, and transformations don’t happen overnight.
  • Infrastructure as code
  • Culture is the #1 success factor in DevOps.
  • Building a culture of shared responsibility, transparency and faster feedback is the foundation of every high performing DevOps team.
  •  'not our problem' mentality
  • DevOps is that change in mindset of looking at the development process holistically and breaking down the barrier between Dev and Ops.
  • Speed is everything.
  • Lack of automated test and review cycles block the release to production and poor incident response time kills velocity and team confidence
  • Open communication helps Dev and Ops teams swarm on issues, fix incidents, and unblock the release pipeline faster.
  • Unplanned work is a reality that every team faces–a reality that most often impacts team productivity.
  • “cross-functional collaboration.”
  • All the tooling and automation in the world are useless if they aren’t accompanied by a genuine desire on the part of development and IT/Ops professionals to work together.
  • DevOps doesn’t solve tooling problems. It solves human problems.
  • Forming project- or product-oriented teams to replace function-based teams is a step in the right direction.
  • sharing a common goal and having a plan to reach it together
  • join sprint planning sessions, daily stand-ups, and sprint demos.
  • DevOps culture across every department
  • open channels of communication, and talk regularly
  • DevOps isn’t one team’s job. It’s everyone’s job.
  • automation eliminates repetitive manual work, yields repeatable processes, and creates reliable systems.
  • Build, test, deploy, and provisioning automation
  • continuous delivery: the practice of running each code change through a gauntlet of automated tests, often facilitated by cloud-based infrastructure, then packaging up successful builds and promoting them up toward production using automated deploys.
  • automated deploys alert IT/Ops to server “drift” between environments, which reduces or eliminates surprises when it’s time to release.
  • “configuration as code.”
  • when DevOps uses automated deploys to send thoroughly tested code to identically provisioned environments, “Works on my machine!” becomes irrelevant.
  • A DevOps mindset sees opportunities for continuous improvement everywhere.
  • regular retrospectives
  • A/B testing
  • failure is inevitable. So you might as well set up your team to absorb it, recover, and learn from it (some call this “being anti-fragile”).
  • Postmortems focus on where processes fell down and how to strengthen them – not on which team member f'ed up the code.
  • Our engineers are responsible for QA, writing, and running their own tests to get the software out to customers.
  • How long did it take to go from development to deployment? 
  • How long does it take to recover after a system failure?
  • service level agreements (SLAs)
  • Devops isn't any single person's job. It's everyone's job.
  • DevOps is big on the idea that the same people who build an application should be involved in shipping and running it.
  • developers and operators pair with each other in each phase of the application’s lifecycle.
張 旭

A Clear, Concise & Comfy Code Review Checklist - DEV Community - 0 views

  • 2 blocks doing similar things might be allowable, but 3 or more is a definitive red cross from me!
  • This would ultimately be integrated into your CI/CD pipelines running on each build/commit/deploy too; stopping any rogue commits getting in.
  • not to say that every code block that is duplicated needs to be refactored
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  • Refactoring is a cyclical process
  • Before accessing variables within objects and collections make sure they are there! PLEASE!
  • If that variable is a constant or won't be changed then use the Const keyword in applicable languages and the CAPITALISATION convention to let users aware of your decisions about them.
  • The name of a method is more important than we give it credit for, when a method changes so should its name.
  • Make sure you are returning the right thing, trying to make it as generic as possible.
  • Void should do something, not change something!
  • Private vs Public, this is a big topic
  • keeping an eye of the access level of a method can stop issues further down the line
  • Gherkin is a Business Readable, Domain Specific Language created especially for behavior descriptions.
  • specify the 3 main points of a test, including what you expect to happen using the following keywords GIVEN,  WHEN / AND , THEN.
  • look at how the code is structured, make sure methods aren't too long, don't have too many branches, and that for and if statements could be simplified.
  • Use your initiative and discuss if a rewrite would benefit maintainability for the future.
  • it's unnecessary to leave commented code when working in and around areas with them.
張 旭

Glossary - CircleCI - 0 views

  • User authentication may use LDAP for an instance of the CircleCI application that is installed on your private server or cloud
  • The first user to log into a private installation of CircleCI
  • Contexts provide a mechanism for securing and sharing environment variables across projects.
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  • The environment variables are defined as name/value pairs and are injected at runtime.
  • The CircleCI Docker Layer Caching feature allows builds to reuse Docker image layers
  • from previous builds.
  • Image layers are stored in separate volumes in the cloud and are not shared between projects.
  • Layers may only be used by builds from the same project.
  • Environment variables store customer data that is used by a project.
  • Defines the underlying technology to run a job.
  • machine to run your job inside a full virtual machine.
  • docker to run your job inside a Docker container with a specified image
  • A job is a collection of steps.
  • The first image listed in config.yml
  • A CircleCI project shares the name of the code repository for which it automates workflows, tests, and deployment.
  • must be added with the Add Project button
  • Following a project enables a user to subscribe to email notifications for the project build status and adds the project to their CircleCI dashboard.
  • A step is a collection of executable commands
  • Users must be added to a GitHub or Bitbucket org to view or follow associated CircleCI projects.
  • Users may not view project data that is stored in environment variables.  
  • A Workflow is a set of rules for defining a collection of jobs and their run order.
  • Workflows are implemented as a directed acyclic graph (DAG) of jobs for greatest flexibility.
  • referred to as Pipelines
  • A workspace is a workflows-aware storage mechanism.
  • A workspace stores data unique to the job, which may be needed in downstream jobs.
張 旭

Introducing Infrastructure as Code | Linode - 0 views

  • Infrastructure as Code (IaC) is a technique for deploying and managing infrastructure using software, configuration files, and automated tools.
  • With the older methods, technicians must configure a device manually, perhaps with the aid of an interactive tool. Information is added to configuration files by hand or through the use of ad-hoc scripts. Configuration wizards and similar utilities are helpful, but they still require hands-on management. A small group of experts owns the expertise, the process is typically poorly defined, and errors are common.
  • The development of the continuous integration and continuous delivery (CI/CD) pipeline made the idea of treating infrastructure as software much more attractive.
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  • Infrastructure as Code takes advantage of the software development process, making use of quality assurance and test automation techniques.
  • Consistency/Standardization
  • Each node in the network becomes what is known as a snowflake, with its own unique settings. This leads to a system state that cannot easily be reproduced and is difficult to debug.
  • With standard configuration files and software-based configuration, there is greater consistency between all equipment of the same type. A key IaC concept is idempotence.
  • Idempotence makes it easy to troubleshoot, test, stabilize, and upgrade all the equipment.
  • Infrastructure as Code is central to the culture of DevOps, which is a mix of development and operations
  • edits are always made to the source configuration files, never on the target.
  • A declarative approach describes the final state of a device, but does not mandate how it should get there. The specific IaC tool makes all the procedural decisions. The end state is typically defined through a configuration file, a JSON specification, or a similar encoding.
  • An imperative approach defines specific functions or procedures that must be used to configure the device. It focuses on what must happen, but does not necessarily describe the final state. Imperative techniques typically use scripts for the implementation.
  • With a push configuration, the central server pushes the configuration to the destination device.
  • If a device is mutable, its configuration can be changed while it is active
  • Immutable devices cannot be changed. They must be decommissioned or rebooted and then completely rebuilt.
  • an immutable approach ensures consistency and avoids drift. However, it usually takes more time to remove or rebuild a configuration than it does to change it.
  • System administrators should consider security issues as part of the development process.
  • Ansible is a very popular open source IaC application from Red Hat
  • Ansible is often used in conjunction with Kubernetes and Docker.
  • Linode offers a collection of several Ansible guides for a more comprehensive overview.
  • Pulumi permits the use of a variety of programming languages to deploy and manage infrastructure within a cloud environment.
  • Terraform allows users to provision data center infrastructure using either JSON or Terraform’s own declarative language.
  • Terraform manages resources through the use of providers, which are similar to APIs.
張 旭

Full Cycle Developers at Netflix - Operate What You Build - 1 views

  • Researching issues felt like bouncing a rubber ball between teams, hard to catch the root cause and harder yet to stop from bouncing between one another.
  • In the past, Edge Engineering had ops-focused teams and SRE specialists who owned the deploy+operate+support parts of the software life cycle
  • hearing about those problems second-hand
  • ...17 more annotations...
  • devs could push code themselves when needed, and also were responsible for off-hours production issues and support requests
  • What were we trying to accomplish and why weren’t we being successful?
  • These specialized roles create efficiencies within each segment while potentially creating inefficiencies across the entire life cycle.
  • Grouping differing specialists together into one team can reduce silos, but having different people do each role adds communication overhead, introduces bottlenecks, and inhibits the effectiveness of feedback loops.
  • devops principles
  • develops a system also be responsible for operating and supporting that system
  • Each development team owns deployment issues, performance bugs, capacity planning, alerting gaps, partner support, and so on.
  • Those centralized teams act as force multipliers by turning their specialized knowledge into reusable building blocks.
  • Communication and alignment are the keys to success.
  • Full cycle developers are expected to be knowledgeable and effective in all areas of the software life cycle.
  • ramping up on areas they haven’t focused on before
  • We run dev bootcamps and other forms of ongoing training to impart this knowledge and build up these skills
  • “how can I automate what is needed to operate this system?”
  • “what self-service tool will enable my partners to answer their questions without needing me to be involved?”
  • A full cycle developer thinks and acts like an SWE, SDET, and SRE. At times they create software that solves business problems, at other times they write test cases for that, and still other times they automate operational aspects of that system.
  • the need for continuous delivery pipelines, monitoring/observability, and so on.
  • Tooling and automation help to scale expertise, but no tool will solve every problem in the developer productivity and operations space
張 旭

Overriding Auto Devops - 0 views

  • most customers need to modify the devops pipeline to suit there needs
  • include Auto Devops and override it.
  • include all of Auto Devops, just as if the Auto Devops checkbox were checked for the project
  • ...4 more annotations...
  • skips for all the scans, as a way of speeding up the build process while working on the CI configuration
  • The Auto Devops test job, which uses Herokuish for testing, does not rely on the Docker image that’s generated during the Build job
  • moving the Test job to the Build stage to speed things along
  • Literally any part of Auto Devops can be overridden in your own CI configuration.
張 旭

Docker image building on GitLab CI | $AYMDEV() - 0 views

  • Continuous Integration (or CI) is a practice where you continously test an application to detect errors as soon as possible.
  • Docker is a container technology, many CI tools execute jobs (the tasks of a pipeline) in container to have an isolated environment.
  • Docker in Docker (« DinD » in short) means executing Docker in a Docker container.
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  • images are saved in the host registry, we can benefit from Docker layer caching
  • All jobs will share the same environment, if many of them run simultaneously they might get into conflicts.
  • storage management (accumulating images)
  • The Docker socket binding technique means making a volume of /var/run/docker.sock between host and containers.
  • all containers would share the same Docker daemon.
  • Add privileged = true in the [runners.docker] section, the privileged mode is mandatory to use DinD.
  • To avoid that the runner only run one job at a time, change the concurrent value on the first line.
  • To avoid building a Docker image at each job, it can be built in a first job, pushed to the image registry provided by GitLab, and pulled in the next jobs.
  • functional tests depending on a database.
  • Docker Compose allows you to easily start multiple containers, but it has no more feature than Docker itself
  • Docker in Docker works well, but has its drawbacks, like Docker layer caching which needs some more commands to be used.
張 旭

Using cache in GitLab CI with Docker-in-Docker | $AYMDEV() - 0 views

  • optimize our images.
  • When you build an image, it is made of multiple layers: we add a layer per instruction.
  • If we build the same image again without modifying any file, Docker will use existing layers rather than re-executing the instructions.
  • ...21 more annotations...
  • an image is made of multiple layers, and we can accelerate its build by using layers cache from the previous image version.
  • by using Docker-in-Docker, we get a fresh Docker instance per job which local registry is empty.
  • docker build --cache-from "$CI_REGISTRY_IMAGE:latest" -t "$CI_REGISTRY_IMAGE:new-tag"
  • But if you maintain a CHANGELOG in this format, and/or your Git tags are also your Docker tags, you can get the previous version and use cache the this image version.
  • script: - export PREVIOUS_VERSION=$(perl -lne 'print "v${1}" if /^##\s\[(\d\.\d\.\d)\]\s-\s\d{4}(?:-\d{2}){2}\s*$/' CHANGELOG.md | sed -n '2 p') - docker build --cache-from "$CI_REGISTRY_IMAGE:$PREVIOUS_VERSION" -t "$CI_REGISTRY_IMAGE:$CI_COMMIT_TAG" -f ./prod.Dockerfile .
  • « Docker layer caching » is enough to optimize the build time.
  • Cache in CI/CD is about saving directories or files across pipelines.
  • We're building a Docker image, dependencies are installed inside a container.We can't cache a dependencies directory if it doesn't exists in the job workspace.
  • Dependencies will always be installed from a container but will be extracted by the GitLab Runner in the job workspace. Our goal is to send the cached version in the build context.
  • We set the directories to cache in the job settings with a key to share the cache per branch and stage.
  • - docker cp app:/var/www/html/vendor/ ./vendor
  • after_script
  • - docker cp app:/var/www/html/node_modules/ ./node_modules
  • To avoid old dependencies to be mixed with the new ones, at the risk of keeping unused dependencies in cache, which would make cache and images heavier.
  • If you need to cache directories in testing jobs, it's easier: use volumes !
  • version your cache keys !
  • sharing Docker image between jobs
  • In every job, we automatically get artifacts from previous stages.
  • docker save $DOCKER_CI_IMAGE | gzip > app.tar.gz
  • I personally use the « push / pull » technique,
  • we docker push after the build, then we docker pull if needed in the next jobs.
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