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張 旭

Probably Done Before: Visualizing Docker Containers and Images - 0 views

  •  In my opinion, understanding how a technology works under the hood is the best way to achieve learning speed and to build confidence that you are using the tool in the correct way.
  • union view
    • 張 旭
       
      把多層 image layer 串接起來,看上去就像是在讀一個 image 檔案而已。
  • The top-level layer may be read by a union-ing file system (AUFS on my docker implementation) to present a single cohesive view of all the changes as one read-only file system
  • ...36 more annotations...
  • it is nearly the same thing as an image, except that the top layer is read-write
  • A container is defined only as a read-write layer atop an image (of read-only layers itself).  It does not have to be running.
  • a running container
    • 張 旭
       
      之前一直搞錯了!不是 run 起來的才會叫 container,只要有 read-write layer 就是了!
  • the the isolated process-space and processes within
  • A running container is defined as a read-write "union view" and
  • kernel-level technologies like cgroups, namespaces
  • The processes within this process-space may change, delete or create files within the "union view" file that will be captured in the read-write layer
  • there is no longer a running container
    • 張 旭
       
      這行指令執行結束之後,running container 就停掉了,但是該 container 還在!
  • each layer contains a pointer to a parent layer using the Id
  • The 'docker create' command adds a read-write layer to the top stack based on the image id.  It does not run this container.
  • The command 'docker start' creates a process space around the union view of the container's layers.
  • can only be one process space per container.
  • the docker run command starts with an image, creates a container, and starts the container
  • 'git pull' (which is a combination of 'git fetch' and 'git merge')
  • 'docker ps' lists out the inventory of running containers on your system
  • 'docker ps -a' where the 'a' is short for 'all' lists out all the containers on your system, whether stopped or running.
  • Only those images that have containers attached to them or that have been pulled are considered top-level.
  • 'docker stop' issues a SIGTERM to a running container which politely stops all the processes in that process-space.
  • results is a normal, but non-running, container
  • 'docker kill' issues a non-polite SIGKILL command to all the processes in a running container.
  • 'docker stop' and 'docker kill' which send actual UNIX signals to a running process
  • 'docker pause' uses a special cgroups feature to freeze/pause a running process-space
  • 'docker rm' removes the read-write layer that defines a container from your host system
  • It effectively deletes files
  • 'docker rmi' removes the read-layer that defines a "union view" of an image.
  • 'docker commit' takes a container's top-level read-write layer and burns it into a read-only layer.
  • turns a container (whether running or stopped) into an immutable image
  • uses the FROM directive in the Dockerfile file as the starting image and iteratively 1) runs (create and start) 2) modifies and 3) commits.
  • At each step in the iteration a new layer is created.
  • 'docker exec' command runs on a running container and executes a process in that running container's process space
  • 'docker inspect' fetches the metadata that has been associated with the top-layer of the container or image
  • 'docker save' creates a single tar file that can be used to import on a different host system
  • only be run on an image
  • 'docker export' command creates a tar file of the contents of the "union view" and flattens it for consumption for non-Docker usages
  • This command removes the metadata and the layers.  This command can only be run on containers.
  • 'docker history' command takes an image-id and recursively prints out the read-only layers
張 旭

phusion/baseimage-docker - 1 views

    • 張 旭
       
      原始的 docker 在執行命令時,預設就是將傳入的 COMMAND 當成 PID 1 的程序,執行完畢就結束這個  docker,其他的 daemons 並不會執行,而 baseimage 解決了這個問題。
    • crazylion lee
       
      好棒棒
  • docker exec
  • Through SSH
  • ...57 more annotations...
  • docker exec -t -i YOUR-CONTAINER-ID bash -l
  • Login to the container
  • Baseimage-docker only advocates running multiple OS processes inside a single container.
  • Password and challenge-response authentication are disabled by default. Only key authentication is allowed.
  • A tool for running a command as another user
  • The Docker developers advocate the philosophy of running a single logical service per container. A logical service can consist of multiple OS processes.
  • All syslog messages are forwarded to "docker logs".
  • Baseimage-docker advocates running multiple OS processes inside a single container, and a single logical service can consist of multiple OS processes.
  • Baseimage-docker provides tools to encourage running processes as different users
  • sometimes it makes sense to run multiple services in a single container, and sometimes it doesn't.
  • Splitting your logical service into multiple OS processes also makes sense from a security standpoint.
  • using environment variables to pass parameters to containers is very much the "Docker way"
  • Baseimage-docker provides a facility to run a single one-shot command, while solving all of the aforementioned problems
  • the shell script must run the daemon without letting it daemonize/fork it.
  • All executable scripts in /etc/my_init.d, if this directory exists. The scripts are run in lexicographic order.
  • variables will also be passed to all child processes
  • Environment variables on Unix are inherited on a per-process basis
  • there is no good central place for defining environment variables for all applications and services
  • centrally defining environment variables
  • One of the ideas behind Docker is that containers should be stateless, easily restartable, and behave like a black box.
  • a one-shot command in a new container
  • immediately exit after the command exits,
  • However the downside of this approach is that the init system is not started. That is, while invoking COMMAND, important daemons such as cron and syslog are not running. Also, orphaned child processes are not properly reaped, because COMMAND is PID 1.
  • add additional daemons (e.g. your own app) to the image by creating runit entries.
  • Nginx is one such example: it removes all environment variables unless you explicitly instruct it to retain them through the env configuration option.
  • Mechanisms for easily running multiple processes, without violating the Docker philosophy
  • Ubuntu is not designed to be run inside Docker
  • According to the Unix process model, the init process -- PID 1 -- inherits all orphaned child processes and must reap them
  • Syslog-ng seems to be much more stable
  • cron daemon
  • Rotates and compresses logs
  • /sbin/setuser
  • A tool for installing apt packages that automatically cleans up after itself.
  • a single logical service inside a single container
  • A daemon is a program which runs in the background of its system, such as a web server.
  • The shell script must be called run, must be executable, and is to be placed in the directory /etc/service/<NAME>. runsv will switch to the directory and invoke ./run after your container starts.
  • If any script exits with a non-zero exit code, the booting will fail.
  • If your process is started with a shell script, make sure you exec the actual process, otherwise the shell will receive the signal and not your process.
  • any environment variables set with docker run --env or with the ENV command in the Dockerfile, will be picked up by my_init
  • not possible for a child process to change the environment variables of other processes
  • they will not see the environment variables that were originally passed by Docker.
  • We ignore HOME, SHELL, USER and a bunch of other environment variables on purpose, because not ignoring them will break multi-user containers.
  • my_init imports environment variables from the directory /etc/container_environment
  • /etc/container_environment.sh - a dump of the environment variables in Bash format.
  • modify the environment variables in my_init (and therefore the environment variables in all child processes that are spawned after that point in time), by altering the files in /etc/container_environment
  • my_init only activates changes in /etc/container_environment when running startup scripts
  • environment variables don't contain sensitive data, then you can also relax the permissions
  • Syslog messages are forwarded to the console
  • syslog-ng is started separately before the runit supervisor process, and shutdown after runit exits.
  • RUN apt-get update && apt-get upgrade -y -o Dpkg::Options::="--force-confold"
  • /sbin/my_init --skip-startup-files --quiet --
  • By default, no keys are installed, so nobody can login
  • provide a pregenerated, insecure key (PuTTY format)
  • RUN /usr/sbin/enable_insecure_key
  • docker run YOUR_IMAGE /sbin/my_init --enable-insecure-key
  • RUN cat /tmp/your_key.pub >> /root/.ssh/authorized_keys && rm -f /tmp/your_key.pub
  • The default baseimage-docker installs syslog-ng, cron and sshd services during the build process
張 旭

Best practices for writing Dockerfiles | Docker Documentation - 0 views

  • building efficient images
  • Docker builds images automatically by reading the instructions from a Dockerfile -- a text file that contains all commands, in order, needed to build a given image.
  • A Docker image consists of read-only layers each of which represents a Dockerfile instruction.
  • ...47 more annotations...
  • The layers are stacked and each one is a delta of the changes from the previous layer
  • When you run an image and generate a container, you add a new writable layer (the “container layer”) on top of the underlying layers.
  • By “ephemeral,” we mean that the container can be stopped and destroyed, then rebuilt and replaced with an absolute minimum set up and configuration.
  • Inadvertently including files that are not necessary for building an image results in a larger build context and larger image size.
  • To exclude files not relevant to the build (without restructuring your source repository) use a .dockerignore file. This file supports exclusion patterns similar to .gitignore files.
  • minimize image layers by leveraging build cache.
  • if your build contains several layers, you can order them from the less frequently changed (to ensure the build cache is reusable) to the more frequently changed
  • avoid installing extra or unnecessary packages just because they might be “nice to have.”
  • Each container should have only one concern.
  • Decoupling applications into multiple containers makes it easier to scale horizontally and reuse containers
  • Limiting each container to one process is a good rule of thumb, but it is not a hard and fast rule.
  • Use your best judgment to keep containers as clean and modular as possible.
  • do multi-stage builds and only copy the artifacts you need into the final image. This allows you to include tools and debug information in your intermediate build stages without increasing the size of the final image.
  • avoid duplication of packages and make the list much easier to update.
  • When building an image, Docker steps through the instructions in your Dockerfile, executing each in the order specified.
  • the next instruction is compared against all child images derived from that base image to see if one of them was built using the exact same instruction. If not, the cache is invalidated.
  • simply comparing the instruction in the Dockerfile with one of the child images is sufficient.
  • For the ADD and COPY instructions, the contents of the file(s) in the image are examined and a checksum is calculated for each file.
  • If anything has changed in the file(s), such as the contents and metadata, then the cache is invalidated.
  • cache checking does not look at the files in the container to determine a cache match.
  • In that case just the command string itself is used to find a match.
    • 張 旭
       
      RUN apt-get 這樣的指令,直接比對指令內容的意思。
  • Whenever possible, use current official repositories as the basis for your images.
  • Using RUN apt-get update && apt-get install -y ensures your Dockerfile installs the latest package versions with no further coding or manual intervention.
  • cache busting
  • Docker executes these commands using the /bin/sh -c interpreter, which only evaluates the exit code of the last operation in the pipe to determine success.
  • set -o pipefail && to ensure that an unexpected error prevents the build from inadvertently succeeding.
  • The CMD instruction should be used to run the software contained by your image, along with any arguments.
  • CMD should almost always be used in the form of CMD [“executable”, “param1”, “param2”…]
  • CMD should rarely be used in the manner of CMD [“param”, “param”] in conjunction with ENTRYPOINT
  • The ENV instruction is also useful for providing required environment variables specific to services you wish to containerize,
  • Each ENV line creates a new intermediate layer, just like RUN commands
  • COPY is preferred
  • COPY only supports the basic copying of local files into the container
  • the best use for ADD is local tar file auto-extraction into the image, as in ADD rootfs.tar.xz /
  • If you have multiple Dockerfile steps that use different files from your context, COPY them individually, rather than all at once.
  • using ADD to fetch packages from remote URLs is strongly discouraged; you should use curl or wget instead
  • The best use for ENTRYPOINT is to set the image’s main command, allowing that image to be run as though it was that command (and then use CMD as the default flags).
  • the image name can double as a reference to the binary as shown in the command
  • The VOLUME instruction should be used to expose any database storage area, configuration storage, or files/folders created by your docker container.
  • use VOLUME for any mutable and/or user-serviceable parts of your image
  • If you absolutely need functionality similar to sudo, such as initializing the daemon as root but running it as non-root), consider using “gosu”.
  • always use absolute paths for your WORKDIR
  • An ONBUILD command executes after the current Dockerfile build completes.
  • Think of the ONBUILD command as an instruction the parent Dockerfile gives to the child Dockerfile
  • A Docker build executes ONBUILD commands before any command in a child Dockerfile.
  • Be careful when putting ADD or COPY in ONBUILD. The “onbuild” image fails catastrophically if the new build’s context is missing the resource being added.
張 旭

Baseimage-docker: A minimal Ubuntu base image modified for Docker-friendliness - 0 views

  • We encourage you to use multiple processes.
  • Baseimage-docker is a special Docker image that is configured for correct use within Docker containers.
  • When your Docker container starts, only the CMD command is run.
  • ...16 more annotations...
  • You're not running them, you're only running your app.
  • You have Ubuntu installed in Docker. The files are there. But that doesn't mean Ubuntu's running as it should.
  • The only processes that will be running inside the container is the CMD command, and all processes that it spawns.
  • A proper Unix system should run all kinds of important system services.
  • Ubuntu is not designed to be run inside Docker
  • When a system is started, the first process in the system is called the init process, with PID 1. The system halts when this processs halts.
  • Runit (written in C) is much lighter weight than supervisord (written in Python).
  • Docker runs fine with multiple processes in a container.
  • Baseimage-docker encourages you to run multiple processes through the use of runit.
  • If your init process is your app, then it'll probably only shut down itself, not all the other processes in the container.
  • a Docker container, which is a locked down environment with e.g. no direct access to many kernel resources.
  • Used for service supervision and management.
  • A custom tool for running a command as another user.
  • add additional daemons (e.g. your own app) to the image by creating runit entries.
  • write a small shell script which runs your daemon, and runit will keep it up and running for you, restarting it when it crashes, etc.
  • the shell script must run the daemon without letting it daemonize/fork it.
張 旭

How To Install and Use Docker: Getting Started | DigitalOcean - 0 views

  • docker as a project offers you the complete set of higher-level tools to carry everything that forms an application across systems and machines - virtual or physical - and brings along loads more of great benefits with it
  • docker daemon: used to manage docker (LXC) containers on the host it runs
  • docker CLI: used to command and communicate with the docker daemon
  • ...20 more annotations...
  • containers: directories containing everything-your-application
  • images: snapshots of containers or base OS (e.g. Ubuntu) images
  • Dockerfiles: scripts automating the building process of images
  • Docker containers are basically directories which can be packed (e.g. tar-archived) like any other, then shared and run across various different machines and platforms (hosts).
  • Linux Containers can be defined as a combination various kernel-level features (i.e. things that Linux-kernel can do) which allow management of applications (and resources they use) contained within their own environment
  • Each container is layered like an onion and each action taken within a container consists of putting another block (which actually translates to a simple change within the file system) on top of the previous one.
  • Each docker container starts from a docker image which forms the base for other applications and layers to come.
  • Docker images constitute the base of docker containers from which everything starts to form
  • a solid, consistent and dependable base with everything that is needed to run the applications
  • As more layers (tools, applications etc.) are added on top of the base, new images can be formed by committing these changes.
  • a Dockerfile for automated image building
  • Dockerfiles are scripts containing a successive series of instructions, directions, and commands which are to be executed to form a new docker image.
  • As you work with a container and continue to perform actions on it (e.g. download and install software, configure files etc.), to have it keep its state, you need to “commit”.
  • Please remember to “commit” all your changes.
  • When you "run" any process using an image, in return, you will have a container.
  • When the process is not actively running, this container will be a non-running container. Nonetheless, all of them will reside on your system until you remove them via rm command.
  • To create a new container, you need to use a base image and specify a command to run.
  • you can not change the command you run after having created a container (hence specifying one during "creation")
  • If you would like to save the progress and changes you made with a container, you can use “commit”
  • turns your container to an image
crazylion lee

BFH ImagePlay - Rapid Prototyping for Image Processing - 0 views

  •  
    "ImagePlay is a rapid prototyping tool for building and testing image processing algorithms. It comes with a variety of over 70 individual image processors which can be combined into complex process chains. ImagePlay is completely open source and can be built for Windows, Mac and Linux."
crazylion lee

anthonynsimon/bild: A collection of parallel image processing algorithms in pure Go - 0 views

  •  
    "A collection of parallel image processing algorithms in pure Go"
crazylion lee

Image Kernels explained visually - 0 views

  •  
    "An image kernel is a small matrix used to apply effects like the ones you might find in Photoshop or Gimp, such as blurring, sharpening, outlining or embossing. They're also used in machine learning for 'feature extraction', a technique for determining the most important portions of an image. In this context the process is referred to more generally as "convolution" (see: convolutional neural networks.)"
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

Docker Explained: Using Dockerfiles to Automate Building of Images | DigitalOcean - 0 views

  • CMD would be running an application upon creation of a container which is already installed using RUN (e.g. RUN apt-get install …) inside the image
  • ENTRYPOINT argument sets the concrete default application that is used every time a container is created using the image.
  • ENV command is used to set the environment variables (one or more).
  • ...6 more annotations...
  • EXPOSE command is used to associate a specified port to enable networking between the running process inside the container and the outside world
  • defines the base image to use to start the build process
  • Unlike CMD, it actually is used to build the image (forming another layer on top of the previous one which is committed).
  • VOLUME command is used to enable access from your container to a directory on the host machine
  • set where the command defined with CMD is to be executed
  • To detach yourself from the container, use the escape sequence CTRL+P followed by CTRL+Q
張 旭

Best practices for writing Dockerfiles - Docker Documentation - 0 views

  • Run only one process per container
  • use current Official Repositories as the basis for your image
  • put long or complex RUN statements on multiple lines separated with backslashes.
  • ...16 more annotations...
  • CMD instruction should be used to run the software contained by your image, along with any arguments
  • CMD should be given an interactive shell (bash, python, perl, etc)
  • COPY them individually, rather than all at once
  • COPY is preferred
  • using ADD to fetch packages from remote URLs is strongly discouraged
  • always use COPY
  • The best use for ENTRYPOINT is to set the image's main command, allowing that image to be run as though it was that command (and then use CMD as the default flags).
  • the image name can double as a reference to the binary as shown in the command above
  • ENTRYPOINT instruction can also be used in combination with a helper script
  • The VOLUME instruction should be used to expose any database storage area, configuration storage, or files/folders created by your docker container.
  • use USER to change to a non-root user
  • avoid installing or using sudo
  • avoid switching USER back and forth frequently.
  • always use absolute paths for your WORKDIR
  • ONBUILD is only useful for images that are going to be built FROM a given image
  • The “onbuild” image will fail catastrophically if the new build's context is missing the resource being added.
張 旭

Pods - Kubernetes - 0 views

  • Pods are the smallest deployable units of computing
  • A Pod (as in a pod of whales or pea pod) is a group of one or more containersA lightweight and portable executable image that contains software and all of its dependencies. (such as Docker containers), with shared storage/network, and a specification for how to run the containers.
  • A Pod’s contents are always co-located and co-scheduled, and run in a shared context.
  • ...32 more annotations...
  • A Pod models an application-specific “logical host”
  • application containers which are relatively tightly coupled
  • being executed on the same physical or virtual machine would mean being executed on the same logical host.
  • The shared context of a Pod is a set of Linux namespaces, cgroups, and potentially other facets of isolation
  • Containers within a Pod share an IP address and port space, and can find each other via localhost
  • Containers in different Pods have distinct IP addresses and can not communicate by IPC without special configuration. These containers usually communicate with each other via Pod IP addresses.
  • Applications within a Pod also have access to shared volumesA directory containing data, accessible to the containers in a pod. , which are defined as part of a Pod and are made available to be mounted into each application’s filesystem.
  • a Pod is modelled as a group of Docker containers with shared namespaces and shared filesystem volumes
    • 張 旭
       
      類似 docker-compose 裡面宣告的同一坨?
  • Pods are considered to be relatively ephemeral (rather than durable) entities.
  • Pods are created, assigned a unique ID (UID), and scheduled to nodes where they remain until termination (according to restart policy) or deletion.
  • it can be replaced by an identical Pod
  • When something is said to have the same lifetime as a Pod, such as a volume, that means that it exists as long as that Pod (with that UID) exists.
  • uses a persistent volume for shared storage between the containers
  • Pods serve as unit of deployment, horizontal scaling, and replication
  • The applications in a Pod all use the same network namespace (same IP and port space), and can thus “find” each other and communicate using localhost
  • flat shared networking space
  • Containers within the Pod see the system hostname as being the same as the configured name for the Pod.
  • Volumes enable data to survive container restarts and to be shared among the applications within the Pod.
  • Individual Pods are not intended to run multiple instances of the same application
  • The individual containers may be versioned, rebuilt and redeployed independently.
  • Pods aren’t intended to be treated as durable entities.
  • Controllers like StatefulSet can also provide support to stateful Pods.
  • When a user requests deletion of a Pod, the system records the intended grace period before the Pod is allowed to be forcefully killed, and a TERM signal is sent to the main process in each container.
  • Once the grace period has expired, the KILL signal is sent to those processes, and the Pod is then deleted from the API server.
  • grace period
  • Pod is removed from endpoints list for service, and are no longer considered part of the set of running Pods for replication controllers.
  • When the grace period expires, any processes still running in the Pod are killed with SIGKILL.
  • By default, all deletes are graceful within 30 seconds.
  • You must specify an additional flag --force along with --grace-period=0 in order to perform force deletions.
  • Force deletion of a Pod is defined as deletion of a Pod from the cluster state and etcd immediately.
  • StatefulSet Pods
  • Processes within the container get almost the same privileges that are available to processes outside a container.
張 旭

Kubernetes Deployments: The Ultimate Guide - Semaphore - 1 views

  • Continuous integration gives you confidence in your code. To extend that confidence to the release process, your deployment operations need to come with a safety belt.
  • these Kubernetes objects ensure that you can progressively deploy, roll back and scale your applications without downtime.
  • A pod is just a group of containers (it can be a group of one container) that run on the same machine, and share a few things together.
  • ...34 more annotations...
  • the containers within a pod can communicate with each other over localhost
  • From a network perspective, all the processes in these containers are local.
  • we can never create a standalone container: the closest we can do is create a pod, with a single container in it.
  • Kubernetes is a declarative system (by opposition to imperative systems).
  • All we can do, is describe what we want to have, and wait for Kubernetes to take action to reconcile what we have, with what we want to have.
  • In other words, we can say, “I would like a 40-feet long blue container with yellow doors“, and Kubernetes will find such a container for us. If it doesn’t exist, it will build it; if there is already one but it’s green with red doors, it will paint it for us; if there is already a container of the right size and color, Kubernetes will do nothing, since what we have already matches what we want.
  • The specification of a replica set looks very much like the specification of a pod, except that it carries a number, indicating how many replicas
  • What happens if we change that definition? Suddenly, there are zero pods matching the new specification.
  • the creation of new pods could happen in a more gradual manner.
  • the specification for a deployment looks very much like the one for a replica set: it features a pod specification, and a number of replicas.
  • Deployments, however, don’t create or delete pods directly.
  • When we update a deployment and adjust the number of replicas, it passes that update down to the replica set.
  • When we update the pod specification, the deployment creates a new replica set with the updated pod specification. That replica set has an initial size of zero. Then, the size of that replica set is progressively increased, while decreasing the size of the other replica set.
  • we are going to fade in (turn up the volume) on the new replica set, while we fade out (turn down the volume) on the old one.
  • During the whole process, requests are sent to pods of both the old and new replica sets, without any downtime for our users.
  • A readiness probe is a test that we add to a container specification.
  • Kubernetes supports three ways of implementing readiness probes:Running a command inside a container;Making an HTTP(S) request against a container; orOpening a TCP socket against a container.
  • When we roll out a new version, Kubernetes will wait for the new pod to mark itself as “ready” before moving on to the next one.
  • If there is no readiness probe, then the container is considered as ready, as long as it could be started.
  • MaxSurge indicates how many extra pods we are willing to run during a rolling update, while MaxUnavailable indicates how many pods we can lose during the rolling update.
  • Setting MaxUnavailable to 0 means, “do not shutdown any old pod before a new one is up and ready to serve traffic“.
  • Setting MaxSurge to 100% means, “immediately start all the new pods“, implying that we have enough spare capacity on our cluster, and that we want to go as fast as possible.
  • kubectl rollout undo deployment web
  • the replica set doesn’t look at the pods’ specifications, but only at their labels.
  • A replica set contains a selector, which is a logical expression that “selects” (just like a SELECT query in SQL) a number of pods.
  • it is absolutely possible to manually create pods with these labels, but running a different image (or with different settings), and fool our replica set.
  • Selectors are also used by services, which act as the load balancers for Kubernetes traffic, internal and external.
  • internal IP address (denoted by the name ClusterIP)
  • during a rollout, the deployment doesn’t reconfigure or inform the load balancer that pods are started and stopped. It happens automatically through the selector of the service associated to the load balancer.
  • a pod is added as a valid endpoint for a service only if all its containers pass their readiness check. In other words, a pod starts receiving traffic only once it’s actually ready for it.
  • In blue/green deployment, we want to instantly switch over all the traffic from the old version to the new, instead of doing it progressively
  • We can achieve blue/green deployment by creating multiple deployments (in the Kubernetes sense), and then switching from one to another by changing the selector of our service
  • kubectl label pods -l app=blue,version=v1.5 status=enabled
  • kubectl label pods -l app=blue,version=v1.4 status-
  •  
    "Continuous integration gives you confidence in your code. To extend that confidence to the release process, your deployment operations need to come with a safety belt."
張 旭

Speeding up Docker image build process of a Rails application | BigBinary Blog - 1 views

  • we do not want to execute bundle install and rake assets:precompile tasks while starting a container in each pod which would prevent that pod from accepting any requests until these tasks are finished.
  • run bundle install and rake assets:precompile tasks while or before containerizing the Rails application.
  • Kubernetes pulls the image, starts a Docker container using that image inside the pod and runs puma server immediately.
  • ...7 more annotations...
  • Since source code changes often, the previously cached layer for the ADD instruction is invalidated due to the mismatching checksums.
  • The ARG instruction in the Dockerfile defines RAILS_ENV variable and is implicitly used as an environment variable by the rest of the instructions defined just after that ARG instruction.
  • RUN instructions are used to install gems and precompile static assets using sprockets
  • Instead, Docker automatically re-uses the previously built layer for the RUN bundle install instruction if the Gemfile.lock file remains unchanged.
  • everyday we need to build a lot of Docker images containing source code from varying Git branches as well as with varying environments.
  • it is hard for Docker to cache layers for bundle install and rake assets:precompile tasks and re-use those layers during every docker build command run with different application source code and a different environment.
  • By default, Bundler installs gems at the location which is set by Rubygems.
  •  
    "we do not want to execute bundle install and rake assets:precompile tasks while starting a container in each pod which would prevent that pod from accepting any requests until these tasks are finished."
張 旭

Secrets - Kubernetes - 0 views

  • Putting this information in a secret is safer and more flexible than putting it verbatim in a PodThe smallest and simplest Kubernetes object. A Pod represents a set of running containers on your cluster. definition or in a container imageStored instance of a container that holds a set of software needed to run an application. .
  • A Secret is an object that contains a small amount of sensitive data such as a password, a token, or a key.
  • Users can create secrets, and the system also creates some secrets.
  • ...63 more annotations...
  • To use a secret, a pod needs to reference the secret.
  • A secret can be used with a pod in two ways: as files in a volumeA directory containing data, accessible to the containers in a pod. mounted on one or more of its containers, or used by kubelet when pulling images for the pod.
  • --from-file
  • You can also create a Secret in a file first, in json or yaml format, and then create that object.
  • The Secret contains two maps: data and stringData.
  • The data field is used to store arbitrary data, encoded using base64.
  • Kubernetes automatically creates secrets which contain credentials for accessing the API and it automatically modifies your pods to use this type of secret.
  • kubectl get and kubectl describe avoid showing the contents of a secret by default.
  • stringData field is provided for convenience, and allows you to provide secret data as unencoded strings.
  • where you are deploying an application that uses a Secret to store a configuration file, and you want to populate parts of that configuration file during your deployment process.
  • a field is specified in both data and stringData, the value from stringData is used.
  • The keys of data and stringData must consist of alphanumeric characters, ‘-’, ‘_’ or ‘.’.
  • Newlines are not valid within these strings and must be omitted.
  • When using the base64 utility on Darwin/macOS users should avoid using the -b option to split long lines.
  • create a Secret from generators and then apply it to create the object on the Apiserver.
  • The generated Secrets name has a suffix appended by hashing the contents.
  • base64 --decode
  • Secrets can be mounted as data volumes or be exposed as environment variablesContainer environment variables are name=value pairs that provide useful information into containers running in a Pod. to be used by a container in a pod.
  • Multiple pods can reference the same secret.
  • Each key in the secret data map becomes the filename under mountPath
  • each container needs its own volumeMounts block, but only one .spec.volumes is needed per secret
  • use .spec.volumes[].secret.items field to change target path of each key:
  • If .spec.volumes[].secret.items is used, only keys specified in items are projected. To consume all keys from the secret, all of them must be listed in the items field.
  • You can also specify the permission mode bits files part of a secret will have. If you don’t specify any, 0644 is used by default.
  • JSON spec doesn’t support octal notation, so use the value 256 for 0400 permissions.
  • Inside the container that mounts a secret volume, the secret keys appear as files and the secret values are base-64 decoded and stored inside these files.
  • Mounted Secrets are updated automatically
  • Kubelet is checking whether the mounted secret is fresh on every periodic sync.
  • cache propagation delay depends on the chosen cache type
  • A container using a Secret as a subPath volume mount will not receive Secret updates.
  • Multiple pods can reference the same secret.
  • env: - name: SECRET_USERNAME valueFrom: secretKeyRef: name: mysecret key: username
  • Inside a container that consumes a secret in an environment variables, the secret keys appear as normal environment variables containing the base-64 decoded values of the secret data.
  • An imagePullSecret is a way to pass a secret that contains a Docker (or other) image registry password to the Kubelet so it can pull a private image on behalf of your Pod.
  • a secret needs to be created before any pods that depend on it.
  • Secret API objects reside in a namespaceAn abstraction used by Kubernetes to support multiple virtual clusters on the same physical cluster. . They can only be referenced by pods in that same namespace.
  • Individual secrets are limited to 1MiB in size.
  • Kubelet only supports use of secrets for Pods it gets from the API server.
  • Secrets must be created before they are consumed in pods as environment variables unless they are marked as optional.
  • References to Secrets that do not exist will prevent the pod from starting.
  • References via secretKeyRef to keys that do not exist in a named Secret will prevent the pod from starting.
  • Once a pod is scheduled, the kubelet will try to fetch the secret value.
  • Think carefully before sending your own ssh keys: other users of the cluster may have access to the secret.
  • volumes: - name: secret-volume secret: secretName: ssh-key-secret
  • Special characters such as $, \*, and ! require escaping. If the password you are using has special characters, you need to escape them using the \\ character.
  • You do not need to escape special characters in passwords from files
  • make that key begin with a dot
  • Dotfiles in secret volume
  • .secret-file
  • a frontend container which handles user interaction and business logic, but which cannot see the private key;
  • a signer container that can see the private key, and responds to simple signing requests from the frontend
  • When deploying applications that interact with the secrets API, access should be limited using authorization policies such as RBAC
  • watch and list requests for secrets within a namespace are extremely powerful capabilities and should be avoided
  • watch and list all secrets in a cluster should be reserved for only the most privileged, system-level components.
  • additional precautions with secret objects, such as avoiding writing them to disk where possible.
  • A secret is only sent to a node if a pod on that node requires it
  • only the secrets that a pod requests are potentially visible within its containers
  • each container in a pod has to request the secret volume in its volumeMounts for it to be visible within the container.
  • In the API server secret data is stored in etcdConsistent and highly-available key value store used as Kubernetes’ backing store for all cluster data.
  • limit access to etcd to admin users
  • Base64 encoding is not an encryption method and is considered the same as plain text.
  • A user who can create a pod that uses a secret can also see the value of that secret.
  • anyone with root on any node can read any secret from the apiserver, by impersonating the kubelet.
張 旭

Ephemeral Containers | Kubernetes - 0 views

  • a special type of container that runs temporarily in an existing Pod to accomplish user-initiated actions such as troubleshooting.
  • you cannot add a container to a Pod once it has been created. Instead, you usually delete and replace Pods in a controlled fashion using deployments.
  • you can run an ephemeral container in an existing Pod to inspect its state and run arbitrary commands.
  • ...4 more annotations...
  • Ephemeral containers differ from other containers in that they lack guarantees for resources or execution, and they will never be automatically restarted, so they are not appropriate for building applications.
  • Ephemeral containers are created using a special ephemeralcontainers handler in the API rather than by adding them directly to pod.spec, so it's not possible to add an ephemeral container using kubectl edit
  • distroless images enable you to deploy minimal container images that reduce attack surface and exposure to bugs and vulnerabilities.
  • enable process namespace sharing so you can view processes in other containers.
  •  
    "a special type of container that runs temporarily in an existing Pod to accomplish user-initiated actions such as troubleshooting. "
crazylion lee

fogleman/primitive: Reproducing images with geometric primitives. - 0 views

  •  
    "Reproducing images with geometric primitives"
張 旭

The differences between Docker, containerd, CRI-O and runc - Tutorial Works - 0 views

  • Docker isn’t the only container contender on the block.
  • Container Runtime Interface (CRI), which defines an API between Kubernetes and the container runtime
  • Open Container Initiative (OCI) which publishes specifications for images and containers.
  • ...20 more annotations...
  • for a lot of people, the name “Docker” itself is synonymous with the word “container”.
  • Docker created a very ergonomic (nice-to-use) tool for working with containers – also called docker.
  • docker is designed to be installed on a workstation or server and comes with a bunch of tools to make it easy to build and run containers as a developer, or DevOps person.
  • containerd: This is a daemon process that manages and runs containers.
  • runc: This is the low-level container runtime (the thing that actually creates and runs containers).
  • libcontainer, a native Go-based implementation for creating containers.
  • Kubernetes includes a component called dockershim, which allows it to support Docker.
  • Kubernetes prefers to run containers through any container runtime which supports its Container Runtime Interface (CRI).
  • Kubernetes will remove support for Docker directly, and prefer to use only container runtimes that implement its Container Runtime Interface.
  • Both containerd and CRI-O can run Docker-formatted (actually OCI-formatted) images, they just do it without having to use the docker command or the Docker daemon.
  • Docker images, are actually images packaged in the Open Container Initiative (OCI) format.
  • CRI is the API that Kubernetes uses to control the different runtimes that create and manage containers.
  • CRI makes it easier for Kubernetes to use different container runtimes
  • containerd is a high-level container runtime that came from Docker, and implements the CRI spec
  • containerd was separated out of the Docker project, to make Docker more modular.
  • CRI-O is another high-level container runtime which implements the Container Runtime Interface (CRI).
  • The idea behind the OCI is that you can choose between different runtimes which conform to the spec.
  • runc is an OCI-compatible container runtime.
  • A reference implementation is a piece of software that has implemented all the requirements of a specification or standard.
  • runc provides all of the low-level functionality for containers, interacting with existing low-level Linux features, like namespaces and control groups.
crazylion lee

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields - 0 views

  •  
    "We present a realtime approach for multi-person 2D pose estimation that predicts vector fields, which we refer to as Part Affinity Fields (PAFs), that directly expose the association between anatomical parts in an image. The architecture is designed to jointly learn part locations and their association, via two branches of the same sequential prediction process."
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