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張 旭

Boosting your kubectl productivity ♦︎ Learnk8s - 0 views

learnk8s.io/...kubectl-productivity

devops kubernetes kubectl

shared by 張 旭 on 09 Apr 19 - No Cached
  • 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
      張 旭 on 09 Apr 19
       
      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

Securing NGINX-ingress - cert-manager Documentation - 1 views

cert-manager.io/...nginx-ingress

kubernetes ingress cert

shared by 張 旭 on 28 Jan 23 - No Cached
  • If using a ClusterIssuer, remember to update the Ingress annotation cert-manager.io/issuer to cert-manager.io/cluster-issuer
  • Certificates resources allow you to specify the details of the certificate you want to request.
  • An Issuer defines how cert-manager will request TLS certificates.
  • ...4 more annotations...
  • cert-manager mainly uses two different custom Kubernetes resources - known as CRDs - to configure and control how it operates, as well as to store state. These resources are Issuers and Certificates.
  • using annotations on the ingress with ingress-shim or directly creating a certificate resource.
  • The secret that is used in the ingress should match the secret defined in the certificate.
  • a typo will result in the ingress-nginx-controller falling back to its self-signed certificate.
  • 張 旭 on 28 Jan 23
     
    "If using a ClusterIssuer, remember to update the Ingress annotation cert-manager.io/issuer to cert-manager.io/cluster-issuer"
張 旭

Best practices for building Kubernetes Operators and stateful apps | Google Cloud Blog - 0 views

cloud.google.com/...es-operators-and-stateful-apps

kubernetes system operator

shared by 張 旭 on 17 May 21 - No Cached
  • use the StatefulSet workload controller to maintain identity for each of the pods, and to use Persistent Volumes to persist data so it can survive a service restart.
  • a way to extend Kubernetes functionality with application specific logic using custom resources and custom controllers.
  • An Operator can automate various features of an application, but it should be specific to a single application
  • ...12 more annotations...
  • Kubebuilder is a comprehensive development kit for building and publishing Kubernetes APIs and Controllers using CRDs
  • Design declarative APIs for operators, not imperative APIs. This aligns well with Kubernetes APIs that are declarative in nature.
  • With declarative APIs, users only need to express their desired cluster state, while letting the operator perform all necessary steps to achieve it.
  • scaling, backup, restore, and monitoring. An operator should be made up of multiple controllers that specifically handle each of the those features.
  • the operator can have a main controller to spawn and manage application instances, a backup controller to handle backup operations, and a restore controller to handle restore operations.
  • each controller should correspond to a specific CRD so that the domain of each controller's responsibility is clear.
  • If you keep a log for every container, you will likely end up with unmanageable amount of logs.
  • integrate application-specific details to the log messages such as adding a prefix for the application name.
  • you may have to use external logging tools such as Google Stackdriver, Elasticsearch, Fluentd, or Kibana to perform the aggregations.
  • adding labels to metrics to facilitate aggregation and analysis by monitoring systems.
  • a more viable option is for application pods to expose a metrics HTTP endpoint for monitoring tools to scrape.
  • A good way to achieve this is to use open-source application-specific exporters for exposing Prometheus-style metrics.
張 旭

Kubernetes Deployments: The Ultimate Guide - Semaphore - 1 views

semaphoreci.com/...kubernetes-deployment

docker kubernetes devops system

shared by 張 旭 on 21 Oct 19 - No Cached
  • Continuous integration gives you confidence in your code. To extend that confidence to the release process, your deployment operations need to come with a safety belt.
  • these Kubernetes objects ensure that you can progressively deploy, roll back and scale your applications without downtime.
  • A pod is just a group of containers (it can be a group of one container) that run on the same machine, and share a few things together.
  • ...34 more annotations...
  • the containers within a pod can communicate with each other over localhost
  • From a network perspective, all the processes in these containers are local.
  • we can never create a standalone container: the closest we can do is create a pod, with a single container in it.
  • Kubernetes is a declarative system (by opposition to imperative systems).
  • All we can do, is describe what we want to have, and wait for Kubernetes to take action to reconcile what we have, with what we want to have.
  • In other words, we can say, “I would like a 40-feet long blue container with yellow doors“, and Kubernetes will find such a container for us. If it doesn’t exist, it will build it; if there is already one but it’s green with red doors, it will paint it for us; if there is already a container of the right size and color, Kubernetes will do nothing, since what we have already matches what we want.
  • The specification of a replica set looks very much like the specification of a pod, except that it carries a number, indicating how many replicas
  • What happens if we change that definition? Suddenly, there are zero pods matching the new specification.
  • the creation of new pods could happen in a more gradual manner.
  • the specification for a deployment looks very much like the one for a replica set: it features a pod specification, and a number of replicas.
  • Deployments, however, don’t create or delete pods directly.
  • When we update a deployment and adjust the number of replicas, it passes that update down to the replica set.
  • When we update the pod specification, the deployment creates a new replica set with the updated pod specification. That replica set has an initial size of zero. Then, the size of that replica set is progressively increased, while decreasing the size of the other replica set.
  • we are going to fade in (turn up the volume) on the new replica set, while we fade out (turn down the volume) on the old one.
  • During the whole process, requests are sent to pods of both the old and new replica sets, without any downtime for our users.
  • A readiness probe is a test that we add to a container specification.
  • Kubernetes supports three ways of implementing readiness probes:Running a command inside a container;Making an HTTP(S) request against a container; orOpening a TCP socket against a container.
  • When we roll out a new version, Kubernetes will wait for the new pod to mark itself as “ready” before moving on to the next one.
  • If there is no readiness probe, then the container is considered as ready, as long as it could be started.
  • MaxSurge indicates how many extra pods we are willing to run during a rolling update, while MaxUnavailable indicates how many pods we can lose during the rolling update.
  • Setting MaxUnavailable to 0 means, “do not shutdown any old pod before a new one is up and ready to serve traffic“.
  • Setting MaxSurge to 100% means, “immediately start all the new pods“, implying that we have enough spare capacity on our cluster, and that we want to go as fast as possible.
  • kubectl rollout undo deployment web
  • the replica set doesn’t look at the pods’ specifications, but only at their labels.
  • A replica set contains a selector, which is a logical expression that “selects” (just like a SELECT query in SQL) a number of pods.
  • it is absolutely possible to manually create pods with these labels, but running a different image (or with different settings), and fool our replica set.
  • Selectors are also used by services, which act as the load balancers for Kubernetes traffic, internal and external.
  • internal IP address (denoted by the name ClusterIP)
  • during a rollout, the deployment doesn’t reconfigure or inform the load balancer that pods are started and stopped. It happens automatically through the selector of the service associated to the load balancer.
  • a pod is added as a valid endpoint for a service only if all its containers pass their readiness check. In other words, a pod starts receiving traffic only once it’s actually ready for it.
  • In blue/green deployment, we want to instantly switch over all the traffic from the old version to the new, instead of doing it progressively
  • We can achieve blue/green deployment by creating multiple deployments (in the Kubernetes sense), and then switching from one to another by changing the selector of our service
  • kubectl label pods -l app=blue,version=v1.5 status=enabled
  • kubectl label pods -l app=blue,version=v1.4 status-
  • 張 旭 on 21 Oct 19
     
    "Continuous integration gives you confidence in your code. To extend that confidence to the release process, your deployment operations need to come with a safety belt."
張 旭

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

Secrets Management with Terraform - 0 views

www.linode.com/...rets-management-with-terraform

terraform config devops security

shared by 張 旭 on 12 Apr 19 - No Cached
  • Terraform is an Infrastructure as Code (IaC) tool that allows you to write declarative code to manage your infrastructure.
  • Keeping Secrets Out of .tf Files
  • .tf files contain the declarative code used to create, manage, and destroy infrastructure.
  • ...17 more annotations...
  • .tf files can accept values from input variables.
  • variable definitions can have default values assigned to them.
  • values are stored in separate files with the .tfvars extension.
  • looks through the working directory for a file named terraform.tfvars, or for files with the .auto.tfvars extension.
  • add the terraform.tfvars file to your .gitignore file and keep it out of version control.
  • include an example terraform.tfvars.example in your Git repository with all of the variable names recorded (but none of the values entered).
  • terraform apply -var-file=myvars.tfvars
  • Terraform allows you to keep input variable values in environment variables.
  • the prefix TF_VAR_
  • If Terraform does not find a default value for a defined variable; or a value from a .tfvars file, environment variable, or CLI flag; it will prompt you for a value before running an action
  • state file contains a JSON object that holds your managed infrastructure’s current state
  • state is a snapshot of the various attributes of your infrastructure at the time it was last modified
  • sensitive information used to generate your Terraform state can be stored as plain text in the terraform.tfstate file.
  • Avoid checking your terraform.tfstate file into your version control repository.
  • Some backends, like Consul, also allow for state locking. If one user is applying a state, another user will be unable to make any changes.
  • Terraform backends allow the user to securely store their state in a remote location, such as a key/value store like Consul, or an S3 compatible bucket storage like Minio.
  • at minimum the repository should be private.
crazylion lee

fastlane - iOS and Android Automation for Continuous Delivery - 1 views

fastlane.tools

automation ios android build

shared by crazylion lee on 08 Oct 16 - No Cached
  • crazylion lee on 08 Oct 16
     
    "stlane is the tool to release your iOS and Android app "
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.
張 旭

Syntax - Configuration Language | Terraform | HashiCorp Developer - 0 views

developer.hashicorp.com/...configuration

devops terraform

shared by 張 旭 on 22 Jan 23 - No Cached
  • the native syntax of the Terraform language, which is a rich language designed to be relatively easy for humans to read and write.
  • Terraform's configuration language is based on a more general language called HCL, and HCL's documentation usually uses the word "attribute" instead of "argument."
  • A particular block type may have any number of required labels, or it may require none
  • ...34 more annotations...
  • After the block type keyword and any labels, the block body is delimited by the { and } characters
  • Identifiers can contain letters, digits, underscores (_), and hyphens (-). The first character of an identifier must not be a digit, to avoid ambiguity with literal numbers.
  • The # single-line comment style is the default comment style and should be used in most cases.
  • he idiomatic style is to use the Unix convention
  • Indent two spaces for each nesting level.
  • align their equals signs
  • Use empty lines to separate logical groups of arguments within a block.
  • Use one blank line to separate the arguments from the blocks.
  • "meta-arguments" (as defined by the Terraform language semantics)
  • Avoid separating multiple blocks of the same type with other blocks of a different type, unless the block types are defined by semantics to form a family.
  • Resource names must start with a letter or underscore, and may contain only letters, digits, underscores, and dashes.
  • Each resource is associated with a single resource type, which determines the kind of infrastructure object it manages and what arguments and other attributes the resource supports.
  • Each resource type is implemented by a provider, which is a plugin for Terraform that offers a collection of resource types.
  • By convention, resource type names start with their provider's preferred local name.
  • Most publicly available providers are distributed on the Terraform Registry, which also hosts their documentation.
  • The Terraform language defines several meta-arguments, which can be used with any resource type to change the behavior of resources.
  • use precondition and postcondition blocks to specify assumptions and guarantees about how the resource operates.
  • Some resource types provide a special timeouts nested block argument that allows you to customize how long certain operations are allowed to take before being considered to have failed.
  • Timeouts are handled entirely by the resource type implementation in the provider
  • Most resource types do not support the timeouts block at all.
  • A resource block declares that you want a particular infrastructure object to exist with the given settings.
  • Destroy resources that exist in the state but no longer exist in the configuration.
  • Destroy and re-create resources whose arguments have changed but which cannot be updated in-place due to remote API limitations.
  • Expressions within a Terraform module can access information about resources in the same module, and you can use that information to help configure other resources. Use the <RESOURCE TYPE>.<NAME>.<ATTRIBUTE> syntax to reference a resource attribute in an expression.
  • resources often provide read-only attributes with information obtained from the remote API; this often includes things that can't be known until the resource is created, like the resource's unique random ID.
  • data sources, which are a special type of resource used only for looking up information.
  • some dependencies cannot be recognized implicitly in configuration.
  • local-only resource types exist for generating private keys, issuing self-signed TLS certificates, and even generating random ids.
  • The behavior of local-only resources is the same as all other resources, but their result data exists only within the Terraform state.
  • The count meta-argument accepts a whole number, and creates that many instances of the resource or module.
  • count.index — The distinct index number (starting with 0) corresponding to this instance.
  • the count value must be known before Terraform performs any remote resource actions. This means count can't refer to any resource attributes that aren't known until after a configuration is applied
  • Within nested provisioner or connection blocks, the special self object refers to the current resource instance, not the resource block as a whole.
  • This was fragile, because the resource instances were still identified by their index instead of the string values in the list.
  • 張 旭 on 22 Jan 23
     
    "the native syntax of the Terraform language, which is a rich language designed to be relatively easy for humans to read and write. "
張 旭

Cluster Networking - Kubernetes - 0 views

kubernetes.io/...networking

kubernetes networking network system

shared by 張 旭 on 08 Jul 19 - No Cached
  • Networking is a central part of Kubernetes, but it can be challenging to understand exactly how it is expected to work
  • Highly-coupled container-to-container communications
  • Pod-to-Pod communications
  • ...57 more annotations...
  • this is the primary focus of this document
    • 張 旭
      張 旭 on 27 Aug 21
       
      Cluster Networking 所關注處理的是： Pod 到 Pod 之間的連線
  • Pod-to-Service communications
  • External-to-Service communications
  • Kubernetes is all about sharing machines between applications.
  • sharing machines requires ensuring that two applications do not try to use the same ports.
  • Dynamic port allocation brings a lot of complications to the system
  • Every Pod gets its own IP address
  • do not need to explicitly create links between Pods
  • almost never need to deal with mapping container ports to host ports.
  • Pods can be treated much like VMs or physical hosts from the perspectives of port allocation, naming, service discovery, load balancing, application configuration, and migration.
  • pods on a node can communicate with all pods on all nodes without NAT
  • agents on a node (e.g. system daemons, kubelet) can communicate with all pods on that node
  • pods in the host network of a node can communicate with all pods on all nodes without NAT
  • If your job previously ran in a VM, your VM had an IP and could talk to other VMs in your project. This is the same basic model.
  • containers within a Pod share their network namespaces - including their IP address
  • containers within a Pod can all reach each other’s ports on localhost
  • containers within a Pod must coordinate port usage
  • “IP-per-pod” model.
  • request ports on the Node itself which forward to your Pod (called host ports), but this is a very niche operation
  • The Pod itself is blind to the existence or non-existence of host ports.
  • AOS is an Intent-Based Networking system that creates and manages complex datacenter environments from a simple integrated platform.
  • Cisco Application Centric Infrastructure offers an integrated overlay and underlay SDN solution that supports containers, virtual machines, and bare metal servers.
  • AOS Reference Design currently supports Layer-3 connected hosts that eliminate legacy Layer-2 switching problems.
  • The AWS VPC CNI offers integrated AWS Virtual Private Cloud (VPC) networking for Kubernetes clusters.
  • users can apply existing AWS VPC networking and security best practices for building Kubernetes clusters.
  • Using this CNI plugin allows Kubernetes pods to have the same IP address inside the pod as they do on the VPC network.
  • The CNI allocates AWS Elastic Networking Interfaces (ENIs) to each Kubernetes node and using the secondary IP range from each ENI for pods on the node.
  • Big Cloud Fabric is a cloud native networking architecture, designed to run Kubernetes in private cloud/on-premises environments.
  • Cilium is L7/HTTP aware and can enforce network policies on L3-L7 using an identity based security model that is decoupled from network addressing.
  • CNI-Genie is a CNI plugin that enables Kubernetes to simultaneously have access to different implementations of the Kubernetes network model in runtime.
  • CNI-Genie also supports assigning multiple IP addresses to a pod, each from a different CNI plugin.
  • cni-ipvlan-vpc-k8s contains a set of CNI and IPAM plugins to provide a simple, host-local, low latency, high throughput, and compliant networking stack for Kubernetes within Amazon Virtual Private Cloud (VPC) environments by making use of Amazon Elastic Network Interfaces (ENI) and binding AWS-managed IPs into Pods using the Linux kernel’s IPvlan driver in L2 mode.
  • to be straightforward to configure and deploy within a VPC
  • Contiv provides configurable networking
  • Contrail, based on Tungsten Fabric, is a truly open, multi-cloud network virtualization and policy management platform.
  • DANM is a networking solution for telco workloads running in a Kubernetes cluster.
  • Flannel is a very simple overlay network that satisfies the Kubernetes requirements.
  • Any traffic bound for that subnet will be routed directly to the VM by the GCE network fabric.
  • sysctl net.ipv4.ip_forward=1
  • Jaguar provides overlay network using vxlan and Jaguar CNIPlugin provides one IP address per pod.
  • Knitter is a network solution which supports multiple networking in Kubernetes.
  • Kube-OVN is an OVN-based kubernetes network fabric for enterprises.
  • Kube-router provides a Linux LVS/IPVS-based service proxy, a Linux kernel forwarding-based pod-to-pod networking solution with no overlays, and iptables/ipset-based network policy enforcer.
  • If you have a “dumb” L2 network, such as a simple switch in a “bare-metal” environment, you should be able to do something similar to the above GCE setup.
  • Multus is a Multi CNI plugin to support the Multi Networking feature in Kubernetes using CRD based network objects in Kubernetes.
  • NSX-T can provide network virtualization for a multi-cloud and multi-hypervisor environment and is focused on emerging application frameworks and architectures that have heterogeneous endpoints and technology stacks.
  • NSX-T Container Plug-in (NCP) provides integration between NSX-T and container orchestrators such as Kubernetes
  • Nuage uses the open source Open vSwitch for the data plane along with a feature rich SDN Controller built on open standards.
  • OpenVSwitch is a somewhat more mature but also complicated way to build an overlay network
  • OVN is an opensource network virtualization solution developed by the Open vSwitch community.
  • Project Calico is an open source container networking provider and network policy engine.
  • Calico provides a highly scalable networking and network policy solution for connecting Kubernetes pods based on the same IP networking principles as the internet
  • Calico can be deployed without encapsulation or overlays to provide high-performance, high-scale data center networking.
  • Calico can also be run in policy enforcement mode in conjunction with other networking solutions such as Flannel, aka canal, or native GCE, AWS or Azure networking.
  • Romana is an open source network and security automation solution that lets you deploy Kubernetes without an overlay network
  • Weave Net runs as a CNI plug-in or stand-alone. In either version, it doesn’t require any configuration or extra code to run, and in both cases, the network provides one IP address per pod - as is standard for Kubernetes.
  • The network model is implemented by the container runtime on each node.
crazylion lee

therecipe/qt: Qt binding for Go (Golang) which supports Windows / macOS / Linux / Andro... - 0 views

github.com/qt

qt go

shared by crazylion lee on 12 Nov 16 - No Cached
  • crazylion lee on 12 Nov 16
     
    "Qt binding for Go (Golang) which supports Windows / macOS / Linux / Android / iOS / Sailfish OS / Raspberry Pi"
crazylion lee

I don't understand Python's Asyncio | Armin Ronacher's Thoughts and Writings - 0 views

lucumr.pocoo.org/...i-dont-understand-asyncio

python io async

shared by crazylion lee on 27 Nov 16 - No Cached
  • crazylion lee on 27 Nov 16
     
    "Recently I started looking into Python's new asyncio module a bit more. The reason for this is that I needed to do something that works better with evented IO and I figured I might give the new hot thing in the Python world a try. Primarily what I learned from this exercise is that I it's a much more complex system than I expected and I am now at the point where I am very confident that I do not know how to use it properly. It's not conceptionally hard to understand and borrows a lot from Twisted, but it has so many elements that play into it that I'm not sure any more how the individual bits and pieces are supposed to go together. Since I'm not clever enough to actually propose anything better I just figured I share my thoughts about what confuses me instead so that others might be able to use that in some capacity to understand it."
crazylion lee

dularion/streama: It's like Netflix, but self-hosted! http://dularion.github.io/streama/ - 0 views

github.com/streama

open source streaming video netflix

shared by crazylion lee on 13 Jan 17 - No Cached
  • crazylion lee on 13 Jan 17
     
    "It's like Netflix, but self-hosted! http://dularion.github.io/streama/"
crazylion lee

Gobot - 0 views

gobot.io

go robot automator

shared by crazylion lee on 17 Jan 14 - No Cached
  • crazylion lee on 17 Jan 14
     
    Gobot is set of libraries in the Go programming language for robotics and physical computing. It provides a simple, yet powerful way to create solutions that incorporate multiple, different hardware devices at the same time. Want to use Ruby on robots? Check out our sister project Artoo (http://artoo.io). Want to use Node.js? Check out our sister project Cylon (http://cylonjs.com).
張 旭

Kubernetes - Traefik - 0 views

docs.traefik.io/...kubernetes

kubernetes networking network ingress traefik

shared by 張 旭 on 04 Jul 19 - No Cached
  • allow fine-grained control of Kubernetes resources and API.
  • authorize Traefik to use the Kubernetes API.
  • namespace-specific RoleBindings
  • ...29 more annotations...
  • a single, global ClusterRoleBinding.
  • RoleBindings per namespace enable to restrict granted permissions to the very namespaces only that Traefik is watching over, thereby following the least-privileges principle.
  • The scalability can be much better when using a Deployment
  • you will have a Single-Pod-per-Node model when using a DaemonSet,
  • DaemonSets automatically scale to new nodes, when the nodes join the cluster
  • DaemonSets ensure that only one replica of pods run on any single node.
  • DaemonSets can be run with the NET_BIND_SERVICE capability, which will allow it to bind to port 80/443/etc on each host. This will allow bypassing the kube-proxy, and reduce traffic hops.
  • start with the Daemonset
  • The Deployment has easier up and down scaling possibilities.
  • The DaemonSet automatically scales to all nodes that meets a specific selector and guarantees to fill nodes one at a time.
  • Rolling updates are fully supported from Kubernetes 1.7 for DaemonSets as well.
  • provide the TLS certificate via a Kubernetes secret in the same namespace as the ingress.
  • If there are any errors while loading the TLS section of an ingress, the whole ingress will be skipped.
  • create secret generic
  • Name-based Routing
  • Path-based Routing
  • Traefik will merge multiple Ingress definitions for the same host/path pair into one definition.
  • specify priority for ingress routes
  • traefik.frontend.priority
  • When specifying an ExternalName, Traefik will forward requests to the given host accordingly and use HTTPS when the Service port matches 443.
  • By default Traefik will pass the incoming Host header to the upstream resource.
  • traefik.frontend.passHostHeader: "false"
  • type: ExternalName
  • By default, Traefik processes every Ingress objects it observes.
  • It is also possible to set the ingressClass option in Traefik to a particular value. Traefik will only process matching Ingress objects.
  • It is possible to split Ingress traffic in a fine-grained manner between multiple deployments using service weights.
  • use case is canary releases where a deployment representing a newer release is to receive an initially small but ever-increasing fraction of the requests over time.
  • annotations: traefik.ingress.kubernetes.io/service-weights: | my-app: 99% my-app-canary: 1%
  • Over time, the ratio may slowly shift towards the canary deployment until it is deemed to replace the previous main application, in steps such as 5%/95%, 10%/90%, 50%/50%, and finally 100%/0%.
張 旭

Kubernetes Components | Kubernetes - 0 views

kubernetes.io/...components

kubernetes system

shared by 張 旭 on 17 May 21 - No Cached
  • 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.
  • ...29 more annotations...
  • 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

Ingress - Kubernetes - 0 views

kubernetes.io/...ingress

kubernetes networking network ingress

shared by 張 旭 on 04 Jul 19 - No Cached
  • An API object that manages external access to the services in a cluster, typically HTTP.
  • load balancing
  • SSL termination
  • ...62 more annotations...
  • name-based virtual hosting
  • Edge routerA router that enforces the firewall policy for your cluster.
  • Cluster networkA set of links, logical or physical, that facilitate communication within a cluster according to the Kubernetes networking model.
  • A Kubernetes ServiceA way to expose an application running on a set of Pods as a network service. that identifies a set of Pods using labelTags objects with identifying attributes that are meaningful and relevant to users. selectors.
  • Services are assumed to have virtual IPs only routable within the cluster network.
  • Ingress exposes HTTP and HTTPS routes from outside the cluster to services within the cluster.
  • Traffic routing is controlled by rules defined on the Ingress resource.
  • An Ingress can be configured to give Services externally-reachable URLs, load balance traffic, terminate SSL / TLS, and offer name based virtual hosting.
  • Exposing services other than HTTP and HTTPS to the internet typically uses a service of type Service.Type=NodePort or Service.Type=LoadBalancer.
  • You must have an ingress controller to satisfy an Ingress. Only creating an Ingress resource has no effect.
  • As with all other Kubernetes resources, an Ingress needs apiVersion, kind, and metadata fields
  • Ingress frequently uses annotations to configure some options depending on the Ingress controller,
  • Ingress resource only supports rules for directing HTTP traffic.
  • An optional host.
  • A list of paths
  • A backend is a combination of Service and port names
  • has an associated backend
  • Both the host and path must match the content of an incoming request before the load balancer directs traffic to the referenced Service.
  • HTTP (and HTTPS) requests to the Ingress that matches the host and path of the rule are sent to the listed backend.
  • A default backend is often configured in an Ingress controller to service any requests that do not match a path in the spec.
  • An Ingress with no rules sends all traffic to a single default backend.
  • Ingress controllers and load balancers may take a minute or two to allocate an IP address.
  • A fanout configuration routes traffic from a single IP address to more than one Service, based on the HTTP URI being requested.
  • nginx.ingress.kubernetes.io/rewrite-target: /
  • describe ingress
  • get ingress
  • Name-based virtual hosts support routing HTTP traffic to multiple host names at the same IP address.
  • route requests based on the Host header.
  • an Ingress resource without any hosts defined in the rules, then any web traffic to the IP address of your Ingress controller can be matched without a name based virtual host being required.
  • secure an Ingress by specifying a SecretStores sensitive information, such as passwords, OAuth tokens, and ssh keys. that contains a TLS private key and certificate.
  • Currently the Ingress only supports a single TLS port, 443, and assumes TLS termination.
  • An Ingress controller is bootstrapped with some load balancing policy settings that it applies to all Ingress, such as the load balancing algorithm, backend weight scheme, and others.
  • persistent sessions, dynamic weights) are not yet exposed through the Ingress. You can instead get these features through the load balancer used for a Service.
  • review the controller specific documentation to see how they handle health checks
  • edit ingress
  • After you save your changes, kubectl updates the resource in the API server, which tells the Ingress controller to reconfigure the load balancer.
  • kubectl replace -f on a modified Ingress YAML file.
  • Node: A worker machine in Kubernetes, part of a cluster.
  • in most common Kubernetes deployments, nodes in the cluster are not part of the public internet.
  • Edge router: A router that enforces the firewall policy for your cluster.
  • a gateway managed by a cloud provider or a physical piece of hardware.
  • Cluster network: A set of links, logical or physical, that facilitate communication within a cluster according to the Kubernetes networking model.
  • Service: A Kubernetes Service that identifies a set of Pods using label selectors.
  • An Ingress may be configured to give Services externally-reachable URLs, load balance traffic, terminate SSL / TLS, and offer name-based virtual hosting.
  • An Ingress does not expose arbitrary ports or protocols.
  • You must have an Ingress controller to satisfy an Ingress. Only creating an Ingress resource has no effect.
  • The name of an Ingress object must be a valid DNS subdomain name
  • The Ingress spec has all the information needed to configure a load balancer or proxy server.
  • Ingress resource only supports rules for directing HTTP(S) traffic.
  • An Ingress with no rules sends all traffic to a single default backend and .spec.defaultBackend is the backend that should handle requests in that case.
  • If defaultBackend is not set, the handling of requests that do not match any of the rules will be up to the ingress controller
  • A common usage for a Resource backend is to ingress data to an object storage backend with static assets.
  • Exact: Matches the URL path exactly and with case sensitivity.
  • Prefix: Matches based on a URL path prefix split by /. Matching is case sensitive and done on a path element by element basis.
  • multiple paths within an Ingress will match a request. In those cases precedence will be given first to the longest matching path.
  • Hosts can be precise matches (for example “foo.bar.com”) or a wildcard (for example “*.foo.com”).
  • No match, wildcard only covers a single DNS label
  • Each Ingress should specify a class, a reference to an IngressClass resource that contains additional configuration including the name of the controller that should implement the class.
  • secure an Ingress by specifying a Secret that contains a TLS private key and certificate.
  • The Ingress resource only supports a single TLS port, 443, and assumes TLS termination at the ingress point (traffic to the Service and its Pods is in plaintext).
  • TLS will not work on the default rule because the certificates would have to be issued for all the possible sub-domains.
  • hosts in the tls section need to explicitly match the host in the rules section.
張 旭

Data Sources - Configuration Language | Terraform | HashiCorp Developer - 0 views

developer.hashicorp.com/...data-sources

devops terraform

shared by 張 旭 on 23 Jan 23 - No Cached
  • Each provider may offer data sources alongside its set of resource types.
  • When distinguishing from data resources, the primary kind of resource (as declared by a resource block) is known as a managed resource.
  • Each data resource is associated with a single data source, which determines the kind of object (or objects) it reads and what query constraint arguments are available.
  • ...4 more annotations...
  • Terraform reads data resources during the planning phase when possible, but announces in the plan when it must defer reading resources until the apply phase to preserve the order of operations.
  • local-only data sources exist for rendering templates, reading local files, and rendering AWS IAM policies.
  • As with managed resources, when count or for_each is present it is important to distinguish the resource itself from the multiple resource instances it creates. Each instance will separately read from its data source with its own variant of the constraint arguments, producing an indexed result.
  • Data instance arguments may refer to computed values, in which case the attributes of the instance itself cannot be resolved until all of its arguments are defined. I
張 旭

What ChatOps Solutions Should You Use Today? | PäksTech - 0 views

pakstech.com/chatops

devops chat

shared by 張 旭 on 16 Feb 22 - No Cached
  • The big elephant in the room is of course Hubot, which now hasn’t seen new commits in over three years.
  • Botkit bots are written in JavaScript and they run on Node.js
  • Errbot is a chatbot written in Python, it comes with a ton of features, and it is extendable with custom plugins.
  • ...8 more annotations...
  • by default they react to !commands in your chatroom. Commands can also trigger on regular expression matches, with or without a bot prefix.
  • Errbot also supports Markdown responses with Jinja2 templating.
  • Errbot supports webhooks; It has a small web server that can translate endpoints to your custom plugins.
  • It’s recommended that you configure this behind a web server such as nginx or Apache.
  • It works with the If This Then That (IFTTT) principle, meaning that you define a set of rules that the system then uses to take action.
  • Lita is a chat bot written in Ruby. Like the other bots I’ve mentioned, it is also open source and supports different chat platforms via plugins.
  • Gort is a newer entrant to the ChatOps space. As the name suggests it has been written in Go, and it is still under active development.
  • can persist information in databases, supports advanced parsers, and is extendable with custom skills.
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