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張 旭

Production environment | Kubernetes - 0 views

kubernetes.io/...production-environment

devops kubernetes

shared by 張 旭 on 25 Jan 23 - No Cached
  • to promote an existing cluster for production use
  • Separating the control plane from the worker nodes.
  • Having enough worker nodes available
  • ...22 more annotations...
  • You can use role-based access control (RBAC) and other security mechanisms to make sure that users and workloads can get access to the resources they need, while keeping workloads, and the cluster itself, secure. You can set limits on the resources that users and workloads can access by managing policies and container resources.
  • you need to plan how to scale to relieve increased pressure from more requests to the control plane and worker nodes or scale down to reduce unused resources.
  • Managed control plane: Let the provider manage the scale and availability of the cluster's control plane, as well as handle patches and upgrades.
  • The simplest Kubernetes cluster has the entire control plane and worker node services running on the same machine.
  • You can deploy a control plane using tools such as kubeadm, kops, and kubespray.
  • Secure communications between control plane services are implemented using certificates.
  • Certificates are automatically generated during deployment or you can generate them using your own certificate authority.
  • Separate and backup etcd service: The etcd services can either run on the same machines as other control plane services or run on separate machines
  • Create multiple control plane systems: For high availability, the control plane should not be limited to a single machine
  • Some deployment tools set up Raft consensus algorithm to do leader election of Kubernetes services. If the primary goes away, another service elects itself and take over.
  • Groups of zones are referred to as regions.
  • if you installed with kubeadm, there are instructions to help you with Certificate Management and Upgrading kubeadm clusters.
  • Production-quality workloads need to be resilient and anything they rely on needs to be resilient (such as CoreDNS).
  • Add nodes to the cluster: If you are managing your own cluster you can add nodes by setting up your own machines and either adding them manually or having them register themselves to the cluster’s apiserver.
  • Set up node health checks: For important workloads, you want to make sure that the nodes and pods running on those nodes are healthy.
  • Authentication: The apiserver can authenticate users using client certificates, bearer tokens, an authenticating proxy, or HTTP basic auth.
  • Authorization: When you set out to authorize your regular users, you will probably choose between RBAC and ABAC authorization.
  • Role-based access control (RBAC): Lets you assign access to your cluster by allowing specific sets of permissions to authenticated users. Permissions can be assigned for a specific namespace (Role) or across the entire cluster (ClusterRole).
  • Attribute-based access control (ABAC): Lets you create policies based on resource attributes in the cluster and will allow or deny access based on those attributes.
  • Set limits on workload resources
  • Set namespace limits: Set per-namespace quotas on things like memory and CPU
  • Prepare for DNS demand: If you expect workloads to massively scale up, your DNS service must be ready to scale up as well.
張 旭

Installing Addons | Kubernetes - 0 views

kubernetes.io/...addons

kubernetes network networking

shared by 張 旭 on 25 Jan 23 - No Cached
  • Calico is a networking and network policy provider. Calico supports a flexible set of networking options so you can choose the most efficient option for your situation, including non-overlay and overlay networks, with or without BGP. Calico uses the same engine to enforce network policy for hosts, pods, and (if using Istio & Envoy) applications at the service mesh layer.
  • Cilium is a networking, observability, and security solution with an eBPF-based data plane. Cilium provides a simple flat Layer 3 network with the ability to span multiple clusters in either a native routing or overlay/encapsulation mode, and can enforce network policies on L3-L7 using an identity-based security model that is decoupled from network addressing. Cilium can act as a replacement for kube-proxy; it also offers additional, opt-in observability and security features.
  • CoreDNS is a flexible, extensible DNS server which can be installed as the in-cluster DNS for pods.
  • ...1 more annotation...
  • The node problem detector runs on Linux nodes and reports system issues as either Events or Node conditions.
張 旭

Flynn: first preview release | Hacker News - 0 views

news.ycombinator.com/item

docker consul system service discovery dns

shared by 張 旭 on 25 Nov 15 - No Cached
  • Etcd and Zookeeper provide essentially the same functionality. They are both a strongly consistent key/value stores that support notifications to clients of changes. These two projects are limited to service discovery
  • So lets say you had a client application that would talk to a node application that could be on any number of servers. What you could do is hard code that list into your application and randomly select one, in order to "fake" load balancing. However every time a machine went up or down you would have to update that list.
  • What Consul provides is you just tell your app to connect to "mynodeapp.consul" and then consul will give you the proper address of one of your node apps.
  • ...9 more annotations...
  • Consul and Skydock are both applications that build on top of a tool like Zookeeper and Etcd.
  • What a developer ideally wants to do is just push code and not have to worry about what servers are running what, and worry about failover and the like
  • What Flynn provides (if I get it), is a diy Heroku like platform
  • Another project that I believe may be similar to Flynn is Apache Mesos.
  • a self hosted Heroku
  • Google Omega is Google's answer to Apache Mesos
  • Omega would need a service like Raft to understand what services are currently available
  • Raft is a consensus algorithm for keeping a set of distributed state machines in a consistent state.
  • I want to use Docker, but it has no easy way to say "take this file that contains instructions and make everything". You can write Dockerfiles, but you can only use one part of the stack in them, otherwise you run into trouble.
  • 張 旭 on 25 Nov 15
     
    " So lets say you had a client application that would talk to a node application that could be on any number of servers. What you could do is hard code that list into your application and randomly select one, in order to "fake" load balancing. However every time a machine went up or down you would have to update that list. What Consul provides is you just tell your app to connect to "mynodeapp.consul" and then consul will give you the proper address of one of your node apps."
張 旭

The Caddyfile Syntax - 0 views

caddyserver.com/caddyfile

caddy proxy HA

shared by 張 旭 on 12 Sep 18 - No Cached
  • A Caddyfile can be used to configure any Caddy server type: HTTP, DNS, etc.
  • The Caddyfile is plain Unicode text encoded with UTF-8.
  • lowercase and uppercase characters are different.
  • ...17 more annotations...
  • A token that starts with quotes " is read literally (including whitespace) until the next instance of quotes " that is not escaped.
  • Only quotes are escapable.
  • Blank, unquoted lines are allowed and ignored.
  • Tokens are then evaluated by the parser for structure.
  • A Caddyfile has no global scope.
  • A label is a string identifier, and a definition is a body (one or more lines) of tokens grouped together in a block
  • a Caddyfile with more than one entry must enclose each definition in curly braces { }.
  • The first line of a Caddyfile is always a label line.
  • If many labels are to head a block, the labels may be suffixed with a comma.
  • as long as the last label of the line has a comma if the next line is to continue the list of labels
  • Commas are not acceptable delimiters for arguments
  • Arguments are delimited solely by same-line whitespace
  • Subdirectives cannot open new blocks.
  • nested directive blocks are not supported
  • Any token (label, directive, argument, etc.) may contain or consist solely of an environment variable
  • Where an import line is, that line will be replaced with the contents of the imported file, unmodified.
  • define snippets to be reused later in your Caddyfile by defining a block with a single-token label surrounded by parentheses
張 旭

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

dev.to/...ld-it-if-youre-not-google-336a

development architecture system google

shared by 張 旭 on 24 Feb 19 - No Cached
  • 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.
  • 張 旭 on 24 Feb 19
     
    "Don't mess up write-first and read-first databases."
張 旭

Keycloak and FreeIPA Intro - scott poore's blog - 0 views

spoore.wordpress.com/...keycloak-and-freeipa-intro

authorization authentication oauth system security freeipa user ldap

shared by 張 旭 on 12 Jul 19 - No Cached
  • Keycloak is an “Open source identity and access management” solution.
  • setup a central Identity Provider (IdP) that applications acting as Service Providers (SP) use to authenticate or authorize user access.
  • FreeIPA does a LOT more than just provide user info though.  It can manage user groups, service lists, hosts, DNS, certificates, and much, much, more.
  • ...5 more annotations...
  • IPA – refers to the FreeIPA Master Server.
  • IdP – as mentioned earlier, IdP stands for Identity Provider.
  • SP – stands for Service Provider.   This can be a java application, jboss, etc.  It can also be a simple Apache web server
  • SAML – stands for Security Assertion Markup Language and refers to mod_auth_mellon here.  This provides the SSO functionality.
  • Openidc – stands for OpenID Connect.
張 旭

Auto DevOps | GitLab - 0 views

docs.gitlab.com/...index.html

gitlab auto devops CI deploy

shared by 張 旭 on 02 Aug 19 - No Cached
  • 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
      張 旭 on 02 Aug 19
       
      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
      張 旭 on 02 Aug 19
       
      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
      張 旭 on 02 Aug 19
       
      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

What's the story behind the names of CloudFlare's name servers? - 0 views

blog.cloudflare.com/es-of-cloudflares-name-servers

dns system networking

shared by 張 旭 on 28 Aug 19 - No Cached
  • what would happen if two people signed up the same domain at the same time?
  • we commissioned an artist to draw representations of the 100 name servers as if they were ninjas. While we've never done much with the drawings, we liked the metaphor of two ninja name servers protecting your website.
  • The servers in CloudFlare's infrastructure are configured to be able to respond to any request for any one of our customers.
  • ...1 more annotation...
  • While you may get Bob and Lola, and someone else may get Stan and Amy, in fact they are both sending requests to the same elastic pool of resources.
  • 張 旭 on 28 Aug 19
     
    "what would happen if two people signed up the same domain at the same time?"
張 旭

What is a CAA record? - DNSimple Help - 0 views

support.dnsimple.com/...caa-record

networking network dns

shared by 張 旭 on 10 Mar 20 - No Cached
  • The purpose of the CAA record is to allow domain owners to declare which certificate authorities are allowed to issue a certificate for a domain.
  • If a CAA record is present, only the CAs listed in the record(s) are allowed to issue certificates for that hostname.
  • CAA records can set policy for the entire domain, or for specific hostnames.
  • ...4 more annotations...
  • The CAA record consists of a flags byte and a tag-value pair referred to as a ‘property’.
  • example.com. CAA 0 issue "letsencrypt.org"
  • each CAA record contains only one tag-value pair
  • dig google.com type257
張 旭

Guide to Service Discovery with Docker - 0 views

docs.datadoghq.com/...servicediscovery

docker service system server dns

shared by 張 旭 on 23 Apr 17 - No Cached
  • The Service Discovery feature watches for Docker events like when a container is created, destroyed, started or stopped. When one of these happens, the Agent identifies which service is impacted, loads the configuration template for this image, and automatically sets up its checks.
  • Configuration templates can be defined by simple template files or as single key-value stores using etcd or Consul.
張 旭

Quick start - 0 views

terragrunt.gruntwork.io/...quick-start

devops terraform

shared by 張 旭 on 15 Jun 21 - No Cached
  • Terragrunt will forward almost all commands, arguments, and options directly to Terraform, but based on the settings in your terragrunt.hcl file
  • the backend configuration does not support variables or expressions of any sort
  • the path_relative_to_include() built-in function,
  • ...9 more annotations...
  • The generate attribute is used to inform Terragrunt to generate the Terraform code for configuring the backend.
  • The find_in_parent_folders() helper will automatically search up the directory tree to find the root terragrunt.hcl and inherit the remote_state configuration from it.
  • Unlike the backend configurations, provider configurations support variables,
  • if you needed to modify the configuration to expose another parameter (e.g session_name), you would have to then go through each of your modules to make this change.
  • instructs Terragrunt to create the file provider.tf in the working directory (where Terragrunt calls terraform) before it calls any of the Terraform commands
  • large modules should be considered harmful.
  • it is a Bad Idea to define all of your environments (dev, stage, prod, etc), or even a large amount of infrastructure (servers, databases, load balancers, DNS, etc), in a single Terraform module.
  • Large modules are slow, insecure, hard to update, hard to code review, hard to test, and brittle (i.e., you have all your eggs in one basket).
  • Terragrunt allows you to define your Terraform code once and to promote a versioned, immutable “artifact” of that exact same code from environment to environment.
張 旭

Helm | - 0 views

helm.sh/...chart_template_guide

helm kubernetes chart devops development

shared by 張 旭 on 06 Aug 19 - No Cached
  • Templates generate manifest files, which are YAML-formatted resource descriptions that Kubernetes can understand.
  • service.yaml: A basic manifest for creating a service endpoint for your deployment
  • In Kubernetes, a ConfigMap is simply a container for storing configuration data.
  • ...88 more annotations...
  • deployment.yaml: A basic manifest for creating a Kubernetes deployment
  • using the suffix .yaml for YAML files and .tpl for helpers.
  • It is just fine to put a plain YAML file like this in the templates/ directory.
  • helm get manifest
  • The helm get manifest command takes a release name (full-coral) and prints out all of the Kubernetes resources that were uploaded to the server. Each file begins with --- to indicate the start of a YAML document
  • Names should be unique to a release
  • The name: field is limited to 63 characters because of limitations to the DNS system.
  • release names are limited to 53 characters
  • {{ .Release.Name }}
  • A template directive is enclosed in {{ and }} blocks.
  • The values that are passed into a template can be thought of as namespaced objects, where a dot (.) separates each namespaced element.
  • The leading dot before Release indicates that we start with the top-most namespace for this scope
  • The Release object is one of the built-in objects for Helm
  • When you want to test the template rendering, but not actually install anything, you can use helm install ./mychart --debug --dry-run
  • Using --dry-run will make it easier to test your code, but it won’t ensure that Kubernetes itself will accept the templates you generate.
  • Objects are passed into a template from the template engine.
  • create new objects within your templates
  • Objects can be simple, and have just one value. Or they can contain other objects or functions.
  • Release is one of the top-level objects that you can access in your templates.
  • Release.Namespace: The namespace to be released into (if the manifest doesn’t override)
  • Values: Values passed into the template from the values.yaml file and from user-supplied files. By default, Values is empty.
  • Chart: The contents of the Chart.yaml file.
  • Files: This provides access to all non-special files in a chart.
  • Files.Get is a function for getting a file by name
  • Files.GetBytes is a function for getting the contents of a file as an array of bytes instead of as a string. This is useful for things like images.
  • Template: Contains information about the current template that is being executed
  • BasePath: The namespaced path to the templates directory of the current chart
  • The built-in values always begin with a capital letter.
  • Go’s naming convention
  • use only initial lower case letters in order to distinguish local names from those built-in.
  • If this is a subchart, the values.yaml file of a parent chart
  • Individual parameters passed with --set
  • values.yaml is the default, which can be overridden by a parent chart’s values.yaml, which can in turn be overridden by a user-supplied values file, which can in turn be overridden by --set parameters.
  • While structuring data this way is possible, the recommendation is that you keep your values trees shallow, favoring flatness.
  • If you need to delete a key from the default values, you may override the value of the key to be null, in which case Helm will remove the key from the overridden values merge.
  • Kubernetes would then fail because you can not declare more than one livenessProbe handler.
  • When injecting strings from the .Values object into the template, we ought to quote these strings.
  • quote
  • Template functions follow the syntax functionName arg1 arg2...
  • While we talk about the “Helm template language” as if it is Helm-specific, it is actually a combination of the Go template language, some extra functions, and a variety of wrappers to expose certain objects to the templates.
  • Drawing on a concept from UNIX, pipelines are a tool for chaining together a series of template commands to compactly express a series of transformations.
  • pipelines are an efficient way of getting several things done in sequence
  • The repeat function will echo the given string the given number of times
  • default DEFAULT_VALUE GIVEN_VALUE. This function allows you to specify a default value inside of the template, in case the value is omitted.
  • all static default values should live in the values.yaml, and should not be repeated using the default command
  • Operators are implemented as functions that return a boolean value.
  • To use eq, ne, lt, gt, and, or, not etcetera place the operator at the front of the statement followed by its parameters just as you would a function.
  • if and
  • if or
  • with to specify a scope
  • range, which provides a “for each”-style loop
  • block declares a special kind of fillable template area
  • A pipeline is evaluated as false if the value is: a boolean false a numeric zero an empty string a nil (empty or null) an empty collection (map, slice, tuple, dict, array)
  • incorrect YAML because of the whitespacing
  • When the template engine runs, it removes the contents inside of {{ and }}, but it leaves the remaining whitespace exactly as is.
  • {{- (with the dash and space added) indicates that whitespace should be chomped left, while -}} means whitespace to the right should be consumed.
  • Newlines are whitespace!
  • an * at the end of the line indicates a newline character that would be removed
  • Be careful with the chomping modifiers.
  • the indent function
  • Scopes can be changed. with can allow you to set the current scope (.) to a particular object.
  • Inside of the restricted scope, you will not be able to access the other objects from the parent scope.
  • range
  • The range function will “range over” (iterate through) the pizzaToppings list.
  • Just like with sets the scope of ., so does a range operator.
  • The toppings: |- line is declaring a multi-line string.
  • not a YAML list. It’s a big string.
  • the data in ConfigMaps data is composed of key/value pairs, where both the key and the value are simple strings.
  • The |- marker in YAML takes a multi-line string.
  • range can be used to iterate over collections that have a key and a value (like a map or dict).
  • In Helm templates, a variable is a named reference to another object. It follows the form $name
  • Variables are assigned with a special assignment operator: :=
  • {{- $relname := .Release.Name -}}
  • capture both the index and the value
  • the integer index (starting from zero) to $index and the value to $topping
  • For data structures that have both a key and a value, we can use range to get both
  • Variables are normally not “global”. They are scoped to the block in which they are declared.
  • one variable that is always global - $ - this variable will always point to the root context.
  • $.
  • $.
  • Helm template language is its ability to declare multiple templates and use them together.
  • A named template (sometimes called a partial or a subtemplate) is simply a template defined inside of a file, and given a name.
  • when naming templates: template names are global.
  • If you declare two templates with the same name, whichever one is loaded last will be the one used.
  • you should be careful to name your templates with chart-specific names.
  • templates in subcharts are compiled together with top-level templates
  • naming convention is to prefix each defined template with the name of the chart: {{ define "mychart.labels" }}
  • Helm has over 60 available functions.
張 旭

Kubernetes 基本概念 · Kubernetes指南 - 0 views

feisky.gitbooks.io/...concepts.html

kubernetes volume namespace system devops

shared by 張 旭 on 30 May 19 - No Cached
  • Container（容器）是一种便携式、轻量级的操作系统级虚拟化技术。它使用 namespace 隔离不同的软件运行环境，并通过镜像自包含软件的运行环境，从而使得容器可以很方便的在任何地方运行。
  • 每个应用程序用容器封装，管理容器部署就等同于管理应用程序部署。+
  • Pod 是一组紧密关联的容器集合，它们共享 PID、IPC、Network 和 UTS namespace，是 Kubernetes 调度的基本单位。
  • ...9 more annotations...
  • 进程间通信和文件共享
  • 在 Kubernetes 中，所有对象都使用 manifest（yaml 或 json）来定义
  • Node 是 Pod 真正运行的主机，可以是物理机，也可以是虚拟机。
  • 每个 Node 节点上至少要运行 container runtime（比如 docker 或者 rkt）、kubelet 和 kube-proxy 服务。
  • 常见的 pods, services, replication controllers 和 deployments 等都是属于某一个 namespace 的（默认是 default）
  • node, persistentVolumes 等则不属于任何 namespace
  • Service 是应用服务的抽象，通过 labels 为应用提供负载均衡和服务发现。
  • 匹配 labels 的 Pod IP 和端口列表组成 endpoints，由 kube-proxy 负责将服务 IP 负载均衡到这些 endpoints 上。
  • 每个 Service 都会自动分配一个 cluster IP（仅在集群内部可访问的虚拟地址）和 DNS 名
  • 張 旭 on 30 May 19
     
    "常见的 pods, services, replication controllers 和 deployments 等都是属于某一个 namespace 的（默认是 default），而 node, persistentVolumes 等则不属于任何 namespace。"
張 旭

Helm | Getting Started - 0 views

helm.sh/...getting_started

helm

shared by 張 旭 on 02 Oct 21 - No Cached
  • The templates/ directory is for template files. When Helm evaluates a chart, it will send all of the files in the templates/ directory through the template rendering engine. It then collects the results of those templates and sends them on to Kubernetes.
  • The charts/ directory may contain other charts (which we call subcharts).
  • we recommend using the suffix .yaml for YAML files and .tpl for helpers.
  • ...8 more annotations...
  • 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, and then is followed by an automatically generated comment line that tells us what template file generated this YAML document.
  • name: field is limited to 63 characters because of limitations to the DNS system.
  • The template directive {{ .Release.Name }} injects the release name into the template. 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
  • helm install --debug --dry-run goodly-guppy ./mychart. This will render the templates. But instead of installing the chart, it will return the rendered template to you
  • 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.
  • It's best not to assume that your chart will install just because --dry-run works.
張 旭

Creating a cluster with kubeadm | Kubernetes - 0 views

kubernetes.io/...create-cluster-kubeadm

kubernetes networking

shared by 張 旭 on 25 Jan 23 - No Cached
  • (Recommended) If you have plans to upgrade this single control-plane kubeadm cluster to high availability you should specify the --control-plane-endpoint to set the shared endpoint for all control-plane nodes
  • set the --pod-network-cidr to a provider-specific value.
  • kubeadm tries to detect the container runtime by using a list of well known endpoints.
  • ...12 more annotations...
  • kubeadm uses the network interface associated with the default gateway to set the advertise address for this particular control-plane node's API server. To use a different network interface, specify the --apiserver-advertise-address=<ip-address> argument to kubeadm init
  • Do not share the admin.conf file with anyone and instead grant users custom permissions by generating them a kubeconfig file using the kubeadm kubeconfig user command.
  • The token is used for mutual authentication between the control-plane node and the joining nodes. The token included here is secret. Keep it safe, because anyone with this token can add authenticated nodes to your cluster.
  • You must deploy a Container Network Interface (CNI) based Pod network add-on so that your Pods can communicate with each other. Cluster DNS (CoreDNS) will not start up before a network is installed.
  • Take care that your Pod network must not overlap with any of the host networks
  • Make sure that your Pod network plugin supports RBAC, and so do any manifests that you use to deploy it.
  • You can install only one Pod network per cluster.
  • The cluster created here has a single control-plane node, with a single etcd database running on it.
  • The node-role.kubernetes.io/control-plane label is such a restricted label and kubeadm manually applies it using a privileged client after a node has been created.
  • By default, your cluster will not schedule Pods on the control plane nodes for security reasons.
  • kubectl taint nodes --all node-role.kubernetes.io/control-plane-
  • remove the node-role.kubernetes.io/control-plane:NoSchedule taint from any nodes that have it, including the control plane nodes, meaning that the scheduler will then be able to schedule Pods everywhere.
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