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crazylion lee

Want to Write a Compiler? Just Read These Two Papers. - 0 views

  •  
    "Compiler"
crazylion lee

crystal-lang/crystal: The Crystal Programming Language - 1 views

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    "Crystal is a programming language with the following goals: Have a syntax similar to Ruby (but compatibility with it is not a goal) Statically type-checked but without having to specify the type of variables or method arguments. Be able to call C code by writing bindings to it in Crystal. Have compile-time evaluation and generation of code, to avoid boilerplate code. Compile to efficient native code. "
crazylion lee

Dotty - 0 views

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    "A next generation compiler for Scala"
crazylion lee

Babel · The compiler for writing next generation JavaScript - 0 views

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    "Babel is a JavaScript compiler. Use next generation JavaScript, today."
張 旭

1. Introduction · swooletw/laravel-swoole Wiki - 0 views

  • when you run PHP script every time, PHP needs to initialize modules and launch Zend Engine for your running environment. And your PHP script needs to be compiled to OpCodes and then Zend Engine can finally execute them.
  • in traditional PHP lifecycle, it wastes a bunch of time building and destroying resources for your script execution.
  • have a built-in server on top of Swoole, and all the scripts can be kept in memory after the first load
  •  
    "when you run PHP script every time, PHP needs to initialize modules and launch Zend Engine for your running environment. And your PHP script needs to be compiled to OpCodes and then Zend Engine can finally execute them."
張 旭

mvn clean install - a short guide to Maven - 0 views

  • An equivalent in other languages would be Javascript’s npm, Ruby’s gems or PHP’s composer.
  • Maven expects a certain directory structure for your Java source code to live in and when you later do a mvn clean install , the whole compilation and packaging work will be done for you.
  • any directory that contains a pom.xml file is also a valid Maven project.
  • ...17 more annotations...
  • A pom.xml file contains everything needed to describe your Java project.
  • Java source code is to be meant to live in the "/src/main/java" folder
  • Maven will put compiled Java classes into the "target/classes" folder
  • Maven will also build a .jar or .war file, depending on your project, that lives in the "target" folder.
  • Maven has the concept of a build lifecycle, which is made up of different phases.
  • clean is not part of Maven’s default lifecycle, you end up with commands like mvn clean install or mvn clean package. Install or package will trigger all preceding phases, but you need to specify clean in addition.
  • Maven will always download your project dependencies into your local maven repository first and then reference them for your build.
  • local repositories (in your user’s home directory: ~/.m2/)
  • clean: deletes the /target folder.
  • mvn clean package
  • mvn clean install
  • package: Converts your .java source code into a .jar/.war file and puts it into the /target folder.
  • install: First, it does a package(!). Then it takes that .jar/.war file and puts it into your local Maven repository, which lives in ~/.m2/repository.
  • calling 'mvn install' would be enough if Maven was smart enough to do reliable, incremental builds.
  • figuring out what Java source files/modules changed and only compile those.
  • developers got it ingrained to always call 'mvn clean install' (even though this increases build time a lot in bigger projects).
  • make sure that Maven always tries to download the latest snapshot dependency versions
張 旭

Language Server Protocol - Wikipedia - 0 views

  • Modern IDEs provide developers with sophisticated features like code completion, refactoring, navigating to a symbol's definition, syntax highlighting, and error and warning markers.
  • an IDE needs a sophisticated understanding of the programming language that the program's source is written in.
  • Conventional compilers or interpreters for a specific programming language are typically unable to provide these language services, because they are written with the goal of either transforming the source code into object code or immediately executing the code.
  • ...5 more annotations...
  • Prior to the design and implementation of the Language Server Protocol for the development of Visual Studio Code, most language services were generally tied to a given IDE or other editor.
  • The Language Server Protocol allows for decoupling language services from the editor so that the services may be contained within a general purpose language server.
  • LSP is not restricted to programming languages. It can be used for any kind of text-based language, like specifications[7] or domain-specific languages (DSL).
  • When a user edits one or more source code files using a language server protocol-enabled tool, the tool acts as a client that consumes the language services provided by a language server.
  • The protocol does not make any provisions about how requests, responses and notifications are transferred between client and server.
crazylion lee

BearSSL - 0 views

shared by crazylion lee on 11 Nov 16 - No Cached
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    "BearSSL is an implementation of the SSL/TLS protocol (RFC 5246) written in C. It aims at offering the following features: Be correct and secure. In particular, insecure protocol versions and choices of algorithms are not supported, by design; cryptographic algorithm implementations are constant-time by default. Be small, both in RAM and code footprint. For instance, a minimal server implementation may fit in about 20 kilobytes of compiled code and 25 kilobytes of RAM. Be highly portable. BearSSL targets not only "big" operating systems like Linux and Windows, but also small embedded systems and even special contexts like bootstrap code. Be feature-rich and extensible. SSL/TLS has many defined cipher suites and extensions; BearSSL should implement most of them, and allow extra algorithm implementations to be added afterwards, possibly from third parties."
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

javascript - How do I "think in AngularJS" if I have a jQuery background? - Stack Overflow - 0 views

  • in AngularJS, we have a separate model layer that we can manage in any way we want, completely independently from the view.
  • keep your concerns separate
  • do DOM manipulation and augment your view with directives
  • ...34 more annotations...
  • DI means that you can declare components very freely and then from any other component, just ask for an instance of it and it will be granted
  • do test-driven development iteratively in AngularJS!
  • only do DOM manipulation in a directive
  • with ngClass we can dynamically update the class;
  • ngBind allows two-way data binding;
  • ngShow and ngHide programmatically show or hide an element;
  • The less DOM manipulation, the easier directives are to test, the easier they are to style, the easier they are to change in the future, and the more re-usable and distributable they are.
  • still wrong.
  • Before doing DOM manipulation anywhere in your application, ask yourself if you really need to.
  • a few things wrong with this
  • jQuery was never necessary
  • use angular.element and our component will still work when dropped into a project that doesn't have jQuery.
  • just use angular.element
  • the element that is passed to the link function would already be a jQuery element!
  • directives aren't just collections of jQuery-like functions
  • Directives are actually extensions of HTML
  • If HTML doesn't do something you need it to do, you write a directive to do it for you, and then use it just as if it was part of HTML.
  • think how the team would accomplish it to fit right in with ngClick, ngClass, et al.
  • Don't even use jQuery. Don't even include it.
  • ry to think about how to do it within the confines the AngularJS.
  • In jQuery, selectors are used to find DOM elements and then bind/register event handlers to them.
  • Views are (declarative) HTML that contain AngularJS directives
  • Directives set up the event handlers behind the scenes for us and give us dynamic databinding.
  • Views are tied to models (via scopes). Views are a projection of the model
  • In AngularJS, think about models, rather than jQuery-selected DOM elements that hold your data.
  • AngularJS uses controllers and directives (each of which can have their own controller, and/or compile and linking functions) to remove behavior from the view/structure (HTML). Angular also has services and filters to help separate/organize your application.
  • Think about your models
  • Think about how you want to present your models -- your views.
  • using the necessary directives to get dynamic databinding.
  • Attach a controller to each view (using ng-view and routing, or ng-controller)
  • Make controllers as thin as possible.
  • You can do a lot with jQuery without knowing about how JavaScript prototypal inheritance works.
  • jQuery is a library
  • AngularJS is a beautiful client-side framework
張 旭

The Rails Command Line - Ruby on Rails Guides - 0 views

  • rake --tasks
  • Think of destroy as the opposite of generate.
  • runner runs Ruby code in the context of Rails non-interactively
  • ...28 more annotations...
  • rails dbconsole figures out which database you're using and drops you into whichever command line interface you would use with it
  • The console command lets you interact with your Rails application from the command line. On the underside, rails console uses IRB
  • rake about gives information about version numbers for Ruby, RubyGems, Rails, the Rails subcomponents, your application's folder, the current Rails environment name, your app's database adapter, and schema version
  • You can precompile the assets in app/assets using rake assets:precompile and remove those compiled assets using rake assets:clean.
  • rake db:version is useful when troubleshooting
  • The doc: namespace has the tools to generate documentation for your app, API documentation, guides.
  • rake notes will search through your code for comments beginning with FIXME, OPTIMIZE or TODO.
  • You can also use custom annotations in your code and list them using rake notes:custom by specifying the annotation using an environment variable ANNOTATION.
  • rake routes will list all of your defined routes, which is useful for tracking down routing problems in your app, or giving you a good overview of the URLs in an app you're trying to get familiar with.
  • rake secret will give you a pseudo-random key to use for your session secret.
  • Custom rake tasks have a .rake extension and are placed in Rails.root/lib/tasks.
  • rails new . --git --database=postgresql
  • All commands can run with -h or --help to list more information
  • The rails server command launches a small web server named WEBrick which comes bundled with Ruby
  • rails server -e production -p 4000
  • You can run a server as a daemon by passing a -d option
  • The rails generate command uses templates to create a whole lot of things.
  • Using generators will save you a large amount of time by writing boilerplate code, code that is necessary for the app to work.
  • All Rails console utilities have help text.
  • generate controller ControllerName action1 action2.
  • With a normal, plain-old Rails application, your URLs will generally follow the pattern of http://(host)/(controller)/(action), and a URL like http://(host)/(controller) will hit the index action of that controller.
  • A scaffold in Rails is a full set of model, database migration for that model, controller to manipulate it, views to view and manipulate the data, and a test suite for each of the above.
  • Unit tests are code that tests and makes assertions about code.
  • Unit tests are your friend.
  • rails console --sandbox
  • rails db
  • Each task has a description, and should help you find the thing you need.
  • rake tmp:clear clears all the three: cache, sessions and sockets.
張 旭

Boosting your kubectl productivity ♦︎ Learnk8s - 0 views

  • kubectl is your cockpit to control Kubernetes.
  • kubectl is a client for the Kubernetes API
  • Kubernetes API is an HTTP REST API.
  • ...75 more annotations...
  • This API is the real Kubernetes user interface.
  • Kubernetes is fully controlled through this API
  • every Kubernetes operation is exposed as an API endpoint and can be executed by an HTTP request to this endpoint.
  • the main job of kubectl is to carry out HTTP requests to the Kubernetes API
  • Kubernetes maintains an internal state of resources, and all Kubernetes operations are CRUD operations on these resources.
  • Kubernetes is a fully resource-centred system
  • Kubernetes API reference is organised as a list of resource types with their associated operations.
  • This is how kubectl works for all commands that interact with the Kubernetes cluster.
  • kubectl simply makes HTTP requests to the appropriate Kubernetes API endpoints.
  • it's totally possible to control Kubernetes with a tool like curl by manually issuing HTTP requests to the Kubernetes API.
  • Kubernetes consists of a set of independent components that run as separate processes on the nodes of a cluster.
  • components on the master nodes
  • Storage backend: stores resource definitions (usually etcd is used)
  • API server: provides Kubernetes API and manages storage backend
  • Controller manager: ensures resource statuses match specifications
  • Scheduler: schedules Pods to worker nodes
  • component on the worker nodes
  • Kubelet: manages execution of containers on a worker node
  • triggers the ReplicaSet controller, which is a sub-process of the controller manager.
  • the scheduler, who watches for Pod definitions that are not yet scheduled to a worker node.
  • creating and updating resources in the storage backend on the master node.
  • The kubelet of the worker node your ReplicaSet Pods have been scheduled to instructs the configured container runtime (which may be Docker) to download the required container images and run the containers.
  • Kubernetes components (except the API server and the storage backend) work by watching for resource changes in the storage backend and manipulating resources in the storage backend.
  • However, these components do not access the storage backend directly, but only through the Kubernetes API.
    • 張 旭
       
      很精彩,相互之間都是使用 API call 溝通,良好的微服務行為。
  • double usage of the Kubernetes API for internal components as well as for external users is a fundamental design concept of Kubernetes.
  • All other Kubernetes components and users read, watch, and manipulate the state (i.e. resources) of Kubernetes through the Kubernetes API
  • The storage backend stores the state (i.e. resources) of Kubernetes.
  • command completion is a shell feature that works by the means of a completion script.
  • A completion script is a shell script that defines the completion behaviour for a specific command. Sourcing a completion script enables completion for the corresponding command.
  • kubectl completion zsh
  • /etc/bash_completion.d directory (create it, if it doesn't exist)
  • source <(kubectl completion bash)
  • source <(kubectl completion zsh)
  • autoload -Uz compinit compinit
  • the API reference, which contains the full specifications of all resources.
  • kubectl api-resources
  • displays the resource names in their plural form (e.g. deployments instead of deployment). It also displays the shortname (e.g. deploy) for those resources that have one. Don't worry about these differences. All of these name variants are equivalent for kubectl.
  • .spec
  • custom columns output format comes in. It lets you freely define the columns and the data to display in them. You can choose any field of a resource to be displayed as a separate column in the output
  • kubectl get pods -o custom-columns='NAME:metadata.name,NODE:spec.nodeName'
  • kubectl explain pod.spec.
  • kubectl explain pod.metadata.
  • browse the resource specifications and try it out with any fields you like!
  • JSONPath is a language to extract data from JSON documents (it is similar to XPath for XML).
  • with kubectl explain, only a subset of the JSONPath capabilities is supported
  • Many fields of Kubernetes resources are lists, and this operator allows you to select items of these lists. It is often used with a wildcard as [*] to select all items of the list.
  • kubectl get pods -o custom-columns='NAME:metadata.name,IMAGES:spec.containers[*].image'
  • a Pod may contain more than one container.
  • The availability zones for each node are obtained through the special failure-domain.beta.kubernetes.io/zone label.
  • kubectl get nodes -o yaml kubectl get nodes -o json
  • The default kubeconfig file is ~/.kube/config
  • with multiple clusters, then you have connection parameters for multiple clusters configured in your kubeconfig file.
  • Within a cluster, you can set up multiple namespaces (a namespace is kind of "virtual" clusters within a physical cluster)
  • overwrite the default kubeconfig file with the --kubeconfig option for every kubectl command.
  • Namespace: the namespace to use when connecting to the cluster
  • a one-to-one mapping between clusters and contexts.
  • When kubectl reads a kubeconfig file, it always uses the information from the current context.
  • just change the current context in the kubeconfig file
  • to switch to another namespace in the same cluster, you can change the value of the namespace element of the current context
  • kubectl also provides the --cluster, --user, --namespace, and --context options that allow you to overwrite individual elements and the current context itself, regardless of what is set in the kubeconfig file.
  • for switching between clusters and namespaces is kubectx.
  • kubectl config get-contexts
  • just have to download the shell scripts named kubectl-ctx and kubectl-ns to any directory in your PATH and make them executable (for example, with chmod +x)
  • kubectl proxy
  • kubectl get roles
  • kubectl get pod
  • Kubectl plugins are distributed as simple executable files with a name of the form kubectl-x. The prefix kubectl- is mandatory,
  • To install a plugin, you just have to copy the kubectl-x file to any directory in your PATH and make it executable (for example, with chmod +x)
  • krew itself is a kubectl plugin
  • check out the kubectl-plugins GitHub topic
  • The executable can be of any type, a Bash script, a compiled Go program, a Python script, it really doesn't matter. The only requirement is that it can be directly executed by the operating system.
  • kubectl plugins can be written in any programming or scripting language.
  • you can write more sophisticated plugins with real programming languages, for example, using a Kubernetes client library. If you use Go, you can also use the cli-runtime library, which exists specifically for writing kubectl plugins.
  • a kubeconfig file consists of a set of contexts
  • changing the current context means changing the cluster, if you have only a single context per cluster.
張 旭

The Twelve-Factor App - 1 views

  • separate build and run
  • The build stage is a transform which converts a code repo into an executable bundle known as a build.
  • the build stage fetches vendors dependencies and compiles binaries and assets.
  • ...7 more annotations...
  • The release stage takes the build produced by the build stage and combines it with the deploy’s current config.
  • is ready for immediate execution in the execution environment.
  • The run stage (also known as “runtime”) runs the app in the execution environment
  • strict separation between the build, release, and run stages.
  • the Capistrano deployment tool stores releases in a subdirectory named releases, where the current release is a symlink to the current release directory.
  • Every release should always have a unique release ID
  • Releases are an append-only ledger and a release cannot be mutated once it is created.
張 旭

The Twelve-Factor App - 0 views

  • stateless processes
  • a production deploy of a sophisticated app may use many process types, instantiated into zero or more running processes.
  • Twelve-factor processes are stateless and share-nothing.
  • ...6 more annotations...
  • Any data that needs to persist must be stored in a stateful backing service, typically a database.
  • The memory space or filesystem of the process can be used as a brief, single-transaction cache.
  • wipe out all local (e.g., memory and filesystem) state
  • compiling during the build stage
  • “sticky sessions” – that is, caching user session data in memory of the app’s process and expecting future requests from the same visitor to be routed to the same process.
  • Sticky sessions are a violation of twelve-factor and should never be used or relied upon
張 旭

Scalable architecture without magic (and how to build it if you're not Google) - DEV Co... - 0 views

  • Don’t mess up write-first and read-first databases.
  • keep them stateless.
  • you should know how to make a scalable setup on bare metal.
  • ...29 more annotations...
  • Different programming languages are for different tasks.
  • Go or C which are compiled to run on bare metal.
  • To run NodeJS on multiple cores, you have to use something like PM2, but since this you have to keep your code stateless.
  • Python have very rich and sugary syntax that’s great for working with data while keeping your code small and expressive.
  • SQL is almost always slower than NoSQL
  • databases are often read-first or write-first
  • write-first, just like Cassandra.
  • store all of your data to your databases and leave nothing at backend
  • Functional code is stateless by default
  • It’s better to go for stateless right from the very beginning.
  • deliver exactly the same responses for same requests.
  • Sessions? Store them at Redis and allow all of your servers to access it.
  • Only the first user will trigger a data query, and all others will be receiving exactly the same data straight from the RAM
  • never, never cache user input
  • Only the server output should be cached
  • Varnish is a great cache option that works with HTTP responses, so it may work with any backend.
  • a rate limiter – if there’s not enough time have passed since last request, the ongoing request will be denied.
  • different requests blasting every 10ms can bring your server down
  • Just set up entry relations and allow your database to calculate external keys for you
  • the query planner will always be faster than your backend.
  • Backend should have different responsibilities: hashing, building web pages from data and templates, managing sessions and so on.
  • For anything related to data management or data models, move it to your database as procedures or queries.
  • a distributed database.
  • your code has to be stateless
  • Move anything related to the data to the database.
  • For load-balancing a database, go for cluster.
  • DB is balancing requests, as well as your backend.
  • Users from different continents are separated with DNS.
  • Keep is scalable, keep is stateless.
  •  
    "Don't mess up write-first and read-first databases."
張 旭

Volumes - Kubernetes - 0 views

  • On-disk files in a Container are ephemeral,
  • when a Container crashes, kubelet will restart it, but the files will be lost - the Container starts with a clean state
  • In Docker, a volume is simply a directory on disk or in another Container.
  • ...105 more annotations...
  • A Kubernetes volume, on the other hand, has an explicit lifetime - the same as the Pod that encloses it.
  • a volume outlives any Containers that run within the Pod, and data is preserved across Container restarts.
    • 張 旭
       
      Kubernetes Volume 是跟著 Pod 的生命週期在走
  • Kubernetes supports many types of volumes, and a Pod can use any number of them simultaneously.
  • To use a volume, a Pod specifies what volumes to provide for the Pod (the .spec.volumes field) and where to mount those into Containers (the .spec.containers.volumeMounts field).
  • A process in a container sees a filesystem view composed from their Docker image and volumes.
  • Volumes can not mount onto other volumes or have hard links to other volumes.
  • Each Container in the Pod must independently specify where to mount each volume
  • localnfs
  • cephfs
  • awsElasticBlockStore
  • glusterfs
  • vsphereVolume
  • An awsElasticBlockStore volume mounts an Amazon Web Services (AWS) EBS Volume into your Pod.
  • the contents of an EBS volume are preserved and the volume is merely unmounted.
  • an EBS volume can be pre-populated with data, and that data can be “handed off” between Pods.
  • create an EBS volume using aws ec2 create-volume
  • the nodes on which Pods are running must be AWS EC2 instances
  • EBS only supports a single EC2 instance mounting a volume
  • check that the size and EBS volume type are suitable for your use!
  • A cephfs volume allows an existing CephFS volume to be mounted into your Pod.
  • the contents of a cephfs volume are preserved and the volume is merely unmounted.
    • 張 旭
       
      相當於自己的 AWS EBS
  • CephFS can be mounted by multiple writers simultaneously.
  • have your own Ceph server running with the share exported
  • configMap
  • The configMap resource provides a way to inject configuration data into Pods
  • When referencing a configMap object, you can simply provide its name in the volume to reference it
  • volumeMounts: - name: config-vol mountPath: /etc/config volumes: - name: config-vol configMap: name: log-config items: - key: log_level path: log_level
  • create a ConfigMap before you can use it.
  • A Container using a ConfigMap as a subPath volume mount will not receive ConfigMap updates.
  • An emptyDir volume is first created when a Pod is assigned to a Node, and exists as long as that Pod is running on that node.
  • When a Pod is removed from a node for any reason, the data in the emptyDir is deleted forever.
  • By default, emptyDir volumes are stored on whatever medium is backing the node - that might be disk or SSD or network storage, depending on your environment.
  • you can set the emptyDir.medium field to "Memory" to tell Kubernetes to mount a tmpfs (RAM-backed filesystem)
  • volumeMounts: - mountPath: /cache name: cache-volume volumes: - name: cache-volume emptyDir: {}
  • An fc volume allows an existing fibre channel volume to be mounted in a Pod.
  • configure FC SAN Zoning to allocate and mask those LUNs (volumes) to the target WWNs beforehand so that Kubernetes hosts can access them.
  • Flocker is an open-source clustered Container data volume manager. It provides management and orchestration of data volumes backed by a variety of storage backends.
  • emptyDir
  • flocker
  • A flocker volume allows a Flocker dataset to be mounted into a Pod
  • have your own Flocker installation running
  • A gcePersistentDisk volume mounts a Google Compute Engine (GCE) Persistent Disk into your Pod.
  • Using a PD on a Pod controlled by a ReplicationController will fail unless the PD is read-only or the replica count is 0 or 1
  • A glusterfs volume allows a Glusterfs (an open source networked filesystem) volume to be mounted into your Pod.
  • have your own GlusterFS installation running
  • A hostPath volume mounts a file or directory from the host node’s filesystem into your Pod.
  • a powerful escape hatch for some applications
  • access to Docker internals; use a hostPath of /var/lib/docker
  • allowing a Pod to specify whether a given hostPath should exist prior to the Pod running, whether it should be created, and what it should exist as
  • specify a type for a hostPath volume
  • the files or directories created on the underlying hosts are only writable by root.
  • hostPath: # directory location on host path: /data # this field is optional type: Directory
  • An iscsi volume allows an existing iSCSI (SCSI over IP) volume to be mounted into your Pod.
  • have your own iSCSI server running
  • A feature of iSCSI is that it can be mounted as read-only by multiple consumers simultaneously.
  • A local volume represents a mounted local storage device such as a disk, partition or directory.
  • Local volumes can only be used as a statically created PersistentVolume.
  • Compared to hostPath volumes, local volumes can be used in a durable and portable manner without manually scheduling Pods to nodes, as the system is aware of the volume’s node constraints by looking at the node affinity on the PersistentVolume.
  • If a node becomes unhealthy, then the local volume will also become inaccessible, and a Pod using it will not be able to run.
  • PersistentVolume spec using a local volume and nodeAffinity
  • PersistentVolume nodeAffinity is required when using local volumes. It enables the Kubernetes scheduler to correctly schedule Pods using local volumes to the correct node.
  • PersistentVolume volumeMode can now be set to “Block” (instead of the default value “Filesystem”) to expose the local volume as a raw block device.
  • When using local volumes, it is recommended to create a StorageClass with volumeBindingMode set to WaitForFirstConsumer
  • An nfs volume allows an existing NFS (Network File System) share to be mounted into your Pod.
  • NFS can be mounted by multiple writers simultaneously.
  • have your own NFS server running with the share exported
  • A persistentVolumeClaim volume is used to mount a PersistentVolume into a Pod.
  • PersistentVolumes are a way for users to “claim” durable storage (such as a GCE PersistentDisk or an iSCSI volume) without knowing the details of the particular cloud environment.
  • A projected volume maps several existing volume sources into the same directory.
  • All sources are required to be in the same namespace as the Pod. For more details, see the all-in-one volume design document.
  • Each projected volume source is listed in the spec under sources
  • A Container using a projected volume source as a subPath volume mount will not receive updates for those volume sources.
  • RBD volumes can only be mounted by a single consumer in read-write mode - no simultaneous writers allowed
  • A secret volume is used to pass sensitive information, such as passwords, to Pods
  • store secrets in the Kubernetes API and mount them as files for use by Pods
  • secret volumes are backed by tmpfs (a RAM-backed filesystem) so they are never written to non-volatile storage.
  • create a secret in the Kubernetes API before you can use it
  • A Container using a Secret as a subPath volume mount will not receive Secret updates.
  • StorageOS runs as a Container within your Kubernetes environment, making local or attached storage accessible from any node within the Kubernetes cluster.
  • Data can be replicated to protect against node failure. Thin provisioning and compression can improve utilization and reduce cost.
  • StorageOS provides block storage to Containers, accessible via a file system.
  • A vsphereVolume is used to mount a vSphere VMDK Volume into your Pod.
  • supports both VMFS and VSAN datastore.
  • create VMDK using one of the following methods before using with Pod.
  • share one volume for multiple uses in a single Pod.
  • The volumeMounts.subPath property can be used to specify a sub-path inside the referenced volume instead of its root.
  • volumeMounts: - name: workdir1 mountPath: /logs subPathExpr: $(POD_NAME)
  • env: - name: POD_NAME valueFrom: fieldRef: apiVersion: v1 fieldPath: metadata.name
  • Use the subPathExpr field to construct subPath directory names from Downward API environment variables
  • enable the VolumeSubpathEnvExpansion feature gate
  • The subPath and subPathExpr properties are mutually exclusive.
  • There is no limit on how much space an emptyDir or hostPath volume can consume, and no isolation between Containers or between Pods.
  • emptyDir and hostPath volumes will be able to request a certain amount of space using a resource specification, and to select the type of media to use, for clusters that have several media types.
  • the Container Storage Interface (CSI) and Flexvolume. They enable storage vendors to create custom storage plugins without adding them to the Kubernetes repository.
  • all volume plugins (like volume types listed above) were “in-tree” meaning they were built, linked, compiled, and shipped with the core Kubernetes binaries and extend the core Kubernetes API.
  • Container Storage Interface (CSI) defines a standard interface for container orchestration systems (like Kubernetes) to expose arbitrary storage systems to their container workloads.
  • Once a CSI compatible volume driver is deployed on a Kubernetes cluster, users may use the csi volume type to attach, mount, etc. the volumes exposed by the CSI driver.
  • The csi volume type does not support direct reference from Pod and may only be referenced in a Pod via a PersistentVolumeClaim object.
  • This feature requires CSIInlineVolume feature gate to be enabled:--feature-gates=CSIInlineVolume=true
  • In-tree plugins that support CSI Migration and have a corresponding CSI driver implemented are listed in the “Types of Volumes” section above.
  • Mount propagation allows for sharing volumes mounted by a Container to other Containers in the same Pod, or even to other Pods on the same node.
  • Mount propagation of a volume is controlled by mountPropagation field in Container.volumeMounts.
  • HostToContainer - This volume mount will receive all subsequent mounts that are mounted to this volume or any of its subdirectories.
  • Bidirectional - This volume mount behaves the same the HostToContainer mount. In addition, all volume mounts created by the Container will be propagated back to the host and to all Containers of all Pods that use the same volume.
  • Edit your Docker’s systemd service file. Set MountFlags as follows:MountFlags=shared
張 旭

Kubernetes Components | Kubernetes - 0 views

  • A Kubernetes cluster consists of a set of worker machines, called nodes, that run containerized applications
  • Every cluster has at least one worker node.
  • The control plane manages the worker nodes and the Pods in the cluster.
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  • The control plane's components make global decisions about the cluster
  • Control plane components can be run on any machine in the cluster.
  • for simplicity, set up scripts typically start all control plane components on the same machine, and do not run user containers on this machine
  • The API server is the front end for the Kubernetes control plane.
  • kube-apiserver is designed to scale horizontally—that is, it scales by deploying more instances. You can run several instances of kube-apiserver and balance traffic between those instances.
  • Kubernetes cluster uses etcd as its backing store, make sure you have a back up plan for those data.
  • watches for newly created Pods with no assigned node, and selects a node for them to run on.
  • Factors taken into account for scheduling decisions include: individual and collective resource requirements, hardware/software/policy constraints, affinity and anti-affinity specifications, data locality, inter-workload interference, and deadlines.
  • each controller is a separate process, but to reduce complexity, they are all compiled into a single binary and run in a single process.
  • Node controller
  • Job controller
  • Endpoints controller
  • Service Account & Token controllers
  • The cloud controller manager lets you link your cluster into your cloud provider's API, and separates out the components that interact with that cloud platform from components that only interact with your cluster.
  • If you are running Kubernetes on your own premises, or in a learning environment inside your own PC, the cluster does not have a cloud controller manager.
  • An agent that runs on each node in the cluster. It makes sure that containers are running in a Pod.
  • The kubelet takes a set of PodSpecs that are provided through various mechanisms and ensures that the containers described in those PodSpecs are running and healthy.
  • The kubelet doesn't manage containers which were not created by Kubernetes.
  • kube-proxy is a network proxy that runs on each node in your cluster, implementing part of the Kubernetes Service concept.
  • kube-proxy maintains network rules on nodes. These network rules allow network communication to your Pods from network sessions inside or outside of your cluster.
  • kube-proxy uses the operating system packet filtering layer if there is one and it's available.
  • Kubernetes supports several container runtimes: Docker, containerd, CRI-O, and any implementation of the Kubernetes CRI (Container Runtime Interface).
  • Addons use Kubernetes resources (DaemonSet, Deployment, etc) to implement cluster features
  • namespaced resources for addons belong within the kube-system namespace.
  • all Kubernetes clusters should have cluster DNS,
  • Cluster DNS is a DNS server, in addition to the other DNS server(s) in your environment, which serves DNS records for Kubernetes services.
  • Containers started by Kubernetes automatically include this DNS server in their DNS searches.
  • Container Resource Monitoring records generic time-series metrics about containers in a central database, and provides a UI for browsing that data.
  • A cluster-level logging mechanism is responsible for saving container logs to a central log store with search/browsing interface.
張 旭

鳥哥的 Linux 私房菜 -- 第一章、Linux是什麼與如何學習 - 0 views

  • Linux就是核心與系統呼叫介面那兩層
  • 核心與硬體的關係非常的強烈
  • Linux提供了一個完整的作業系統當中最底層的硬體控制與資源管理的完整架構, 這個架構是沿襲Unix良好的傳統來的,所以相當的穩定而功能強大
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  • Linux的核心是由Linus Torvalds在1991年的時候給他開發出來的, 並且丟到網路上提供大家下載,後來大家覺得這個小東西(Linux Kernel)相當的小而精巧, 所以慢慢的就有相當多的朋友投入這個小東西的研究領域裡面去
  • 1960年代初期麻省理工學院(MIT)發展了所謂的: 『相容分時系統(Compatible Time-Sharing System, CTSS)』, 它可以讓大型主機透過提供數個終端機(terminal)以連線進入主機,來利用主機的資源進行運算工作
  • 為了更加強化大型主機的功能,以讓主機的資源可以提供更多使用者來利用,所以在1965年前後, 由貝爾實驗室(Bell)、麻省理工學院(MIT)及奇異公司(GE, 或稱為通用電器)共同發起了Multics的計畫
  • 以組合語言(Assembler)寫出了一組核心程式,同時包括一些核心工具程式, 以及一個小小的檔案系統。那個系統就是Unix的原型! 當時Thompson將Multics龐大的複雜系統簡化了不少,於是同實驗室的朋友都戲稱這個系統為:Unics。(當時尚未有Unix的名稱)
  • 所有的程式或系統裝置都是檔案
  • 不管建構編輯器還是附屬檔案,所寫的程式只有一個目的,且要有效的完成目標。
  • Dennis Ritchie (註3) 將B語言重新改寫成C語言,再以C語言重新改寫與編譯Unics的核心, 最後正名與發行出Unix的正式版本!
  • 由於Unix是以較高階的C語言寫的,相對於組合語言需要與硬體有密切的配合, 高階的C語言與硬體的相關性就沒有這麼大了!所以,這個改變也使得Unix很容易被移植到不同的機器上面喔!
  • AT&T此時對於Unix是採取較開放的態度,此外,Unix是以高階的C語言寫成的, 理論上是具有可移植性的!亦即只要取得Unix的原始碼,並且針對大型主機的特性加以修訂原有的原始碼(Source Code), 就可能將Unix移植到另一部不同的主機上頭了。
  • 柏克萊大學的Bill Joy (註4)在取得了Unix的核心原始碼後,著手修改成適合自己機器的版本, 並且同時增加了很多工具軟體與編譯程式,最終將它命名為Berkeley Software Distribution (BSD)。
  • 每一家公司自己出的Unix雖然在架構上面大同小異,但是卻真的僅能支援自身的硬體, 所以囉,早先的Unix只能與伺服器(Server)或者是大型工作站(Workstation)劃上等號!
  • AT&T在1979年發行的第七版Unix中,特別提到了 『不可對學生提供原始碼』的嚴格限制!
  • 純種的Unix指的就是System V以及BSD
  • AT&T自家的System V
  • 既然1979年的Unix第七版可以在Intel的x86架構上面進行移植, 那麼是否意味著可以將Unix改寫並移植到x86上面了呢?在這個想法上, 譚寧邦教授於是乎自己動手寫了Minix這個Unix Like的核心程式!
  • 『既然作業系統太複雜,我就先寫可以在Unix上面運行的小程式,這總可以了吧?』
  • 如果能夠寫出一個不錯的編譯器,那不就是大家都需要的軟體了嗎? 因此他便開始撰寫C語言的編譯器,那就是現在相當有名的GNU C Compiler(gcc)!
  • 他還撰寫了更多可以被呼叫的C函式庫(GNU C library),以及可以被使用來操作作業系統的基本介面BASH shell! 這些都在1990年左右完成了!
  • 有鑑於圖形使用者介面(Graphical User Interface, GUI) 的需求日益加重,在1984年由MIT與其他協力廠商首次發表了X Window System ,並且更在1988年成立了非營利性質的XFree86這個組織。所謂的XFree86其實是 X Window System + Free + x86的整合名稱呢!
  • 譚寧邦教授為了教育需要而撰寫的Minix系統! 他在購買了最新的Intel 386的個人電腦後,就立即安裝了Minix這個作業系統。 另外,上個小節當中也談到,Minix這個作業系統是有附上原始碼的, 所以托瓦茲也經由這個原始碼學習到了很多的核心程式設計的設計概念喔!
  • 托瓦茲自己也說:『我始終是個性能癖』^_^。 為了徹底發揮386的效能,於是托瓦茲花了不少時間在測試386機器上! 他的重要測試就是在測試386的多功性能。首先,他寫了三個小程式,一個程式會持續輸出A、一個會持續輸出B, 最後一個會將兩個程式進行切換。他將三個程式同時執行,結果,他看到螢幕上很順利的一直出現ABABAB...... 他知道,他成功了! ^_^
  • 為了讓所有的軟體都可以在Linux上執行,於是托瓦茲開始參考標準的POSIX規範。
  • POSIX是可攜式作業系統介面(Portable Operating System Interface)的縮寫,重點在規範核心與應用程式之間的介面, 這是由美國電器與電子工程師學會(IEEE)所發佈的一項標準喔
  • 因為托瓦茲放置核心的那個FTP網站的目錄為:Linux, 從此,大家便稱這個核心為Linux了。(請注意,此時的Linux就是那個kernel喔! 另外,托瓦茲所丟到該目錄下的第一個核心版本為0.02呢!)
  • Linux其實就是一個作業系統最底層的核心及其提供的核心工具。 他是GNU GPL授權模式,所以,任何人均可取得原始碼與可執行這個核心程式,並且可以修改。
  • Linux參考POSIX設計規範,於是相容於Unix作業系統,故亦可稱之為Unix Like的一種
  • 為了讓使用者能夠接觸到Linux,於是很多的商業公司或非營利團體, 就將Linux Kernel(含tools)與可運行的軟體整合起來,加上自己具有創意的工具程式, 這個工具程式可以讓使用者以光碟/DVD或者透過網路直接安裝/管理Linux系統。 這個『Kernel + Softwares + Tools + 可完整安裝程序』的咚咚,我們稱之為Linux distribution, 一般中文翻譯成可完整安裝套件,或者Linux發佈商套件等。
  • 在1994年終於完成的Linux的核心正式版!version 1.0。 這一版同時還加入了X Window System的支援呢!且於1996年完成了2.0版、2011 年釋出 3.0 版,更於 2015 年 4 月釋出了 4.0 版哩! 發展相當迅速喔!此外,托瓦茲指明了企鵝為Linux的吉祥物。
  • Linux本身就是個最陽春的作業系統,其開發網站設立在http://www.kernel.org,我們亦稱Linux作業系統最底層的資料為『核心(Kernel)』。
  • 常見的 Linux distributions 分類有『商業、社群』分類法,或『RPM、DPKG』分類法
  • 事實上鳥哥認為distributions主要分為兩大系統,一種是使用RPM方式安裝軟體的系統,包括Red Hat, Fedora, SuSE等都是這類; 一種則是使用Debian的dpkg方式安裝軟體的系統,包括Debian, Ubuntu, B2D等等。
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.
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  • 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 | Named Templates - 0 views

  • a special-purpose include function that works similarly to the template action.
  • when naming templates: template names are global.
  • templates in subcharts are compiled together with top-level templates, you should be careful to name your templates with chart-specific names.
  • ...14 more annotations...
  • One popular naming convention is to prefix each defined template with the name of the chart: {{ define "mychart.labels" }}
  • using the specific chart name as a prefix we can avoid any conflicts
  • But files whose name begins with an underscore (_) are assumed to not have a manifest inside.
  • The define action allows us to create a named template inside of a template file.
  • include it with the template action
  • a define does not produce output unless it is called with a template
  • define functions should have a simple documentation block ({{/* ... */}}) describing what they do.
  • template names are global.
  • A popular naming convention is to prefix each defined template with the name of the chart
  • When a named template (created with define) is rendered, it will receive the scope passed in by the template call.
  • No scope was passed in, so within the template we cannot access anything in .
  • Note that we pass . at the end of the template call. We could just as easily pass .Values or .Values.favorite or whatever scope we want
  • the template that is substituted in has the text aligned to the left. Because template is an action, and not a function, there is no way to pass the output of a template call to other functions; the data is simply inserted inline.
  • use indent to indent
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    "a special-purpose include function that works similarly to the template action."
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