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張 旭

Dynamic Provisioning | vSphere Storage for Kubernetes - 0 views

  • Storage Policy based Management (SPBM). SPBM provides a single unified control plane across a broad range of data services and storage solutions
  • Kubernetes StorageClasses allow the creation of PersistentVolumes on-demand without having to create storage and mount it into K8s nodes upfront
  • When a PVC is created, the PersistentVolume will be provisioned on a compatible datastore with the most free space that satisfies the gold storage policy requirements.
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  • When a PVC is created, the vSphere Cloud Provider checks if the user specified datastore satisfies the gold storage policy requirements. If it does, the vSphere Cloud Provider will provision the PersistentVolume on the user specified datastore. If not, it will create an error telling the user that the specified datastore is not compatible with gold storage policy requirements.
  • The Kubernetes user will have the ability to specify custom vSAN Storage Capabilities during dynamic volume provisioning.
  •  
    "Storage Policy based Management (SPBM). SPBM provides a single unified control plane across a broad range of data services and storage solutions"
張 旭

Using Infrastructure as Code to Automate VMware Deployments - 1 views

  • Infrastructure as code is at the heart of provisioning for cloud infrastructure marking a significant shift away from monolithic point-and-click management tools.
  • infrastructure as code enables operators to take a programmatic approach to provisioning.
  • provides a single workflow to provision and maintain infrastructure and services from all of your vendors, making it not only easier to switch providers
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  • A Terraform Provider is responsible for understanding API interactions between and exposing the resources from a given Infrastructure, Platform, or SaaS offering to Terraform.
  • write a Terraform file that describes the Virtual Machine that you want, apply that file with Terraform and create that VM as you described without ever needing to log into the vSphere dashboard.
  • HashiCorp Configuration Language (HCL)
  • the provider credentials are passed in at the top of the script to connect to the vSphere account.
  • modules— a way to encapsulate infrastructure resources into a reusable format.
  •  
    "revolutionizing"
張 旭

What is DevOps? | Atlassian - 0 views

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

Developing with Docker - 1 views

  • Before moving our production infrastructure over however, we decided that we wanted to start developing with them locally first. We could shake out any issues with our applications before risking the production environment.
  • using Chef and Vagrant to provision local VMs
  • Engineers at IFTTT currently all use Apple computers
  • ...7 more annotations...
  • /bin/true
    • 張 旭
       
      如果使用 docker create 就不用跑這個, 不過目前 docker-compose 沒有支援 volume-only 的 container
  • it will install gems onto the data volume from the bundler-cache container.
  • dev rm bundler-cache
    • 張 旭
       
      要完全刪除干淨,後面的指令可能是: docker rm -v bundler-cache
  • if you accidentally delete bundler-cache, you then have to install all your gems over again.
  • Containerization and Docker are powerful tools in your infrastructure toolbox.
  • highly recommend starting off in your developer environment first
  • the onboarding time for new developers go from a couple days or more to a matter of hours.
張 旭

The Twelve-Factor App - 0 views

  • Keep development, staging, and production as similar as possible
  • Developers write code, ops engineers deploy it.
  • The twelve-factor app is designed for continuous deployment by keeping the gap between development and production small
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  • Backing services, such as the app’s database, queueing system, or cache, is one area where dev/prod parity is important
  • The twelve-factor developer resists the urge to use different backing services between development and production, even when adapters theoretically abstract away any differences in backing services.
  • declarative provisioning tools such as Chef and Puppet combined with light-weight virtual environments such as Docker and Vagrant allow developers to run local environments which closely approximate production environments.
  • all deploys of the app (developer environments, staging, production) should be using the same type and version of each of the backing services.
  •  
    "as similar as possible "
張 旭

Volumes - Kubernetes - 0 views

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

Auto DevOps | GitLab - 0 views

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

Ansible Tower vs Ansible AWX for Automation - 4sysops - 0 views

  • you can run Ansible freely by downloading the module and running configurations and playbooks from the command line.
  • AWX Project from Red Hat. It provides an open-source version of Ansible Tower that may suit the needs of Tower functionality in many environments.
  • Ansible Tower may be the more familiar option for Ansible users as it is the commercial GUI Ansible tool that provides the officially supported GUI interface, API access, role-based access, scheduling, notifications, and other nice features that allow businesses to manage environments easily with Ansible.
  • ...5 more annotations...
  • Ansible AWX is the open-sourced project that was the foundation on which Ansible Tower was created. With this being said, Ansible AWX is a development branch of code that only undergoes minimal testing and quality engineering testing.
  • Ansible AWX is a powerful open-source, freely available project for testing or using Ansible AWX in a lab, development, or other POC environment.
  • to use an external PostgreSQL database, please note that the minimum version is 9.6+
  • Full enterprise features and functionality of Tower
  • Not limited to 10 nodes
張 旭

vSphere Cloud Provider | vSphere Storage for Kubernetes - 0 views

  • Containers are stateless and ephemeral but applications are stateful and need persistent storage.
  • Cloud Provider
  • Kubernetes cloud providers are an interface to integrate various node (i.e. hosts), load balancers and networking routes
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  • VMware offers a Cloud Provider known as the vSphere Cloud Provider (VCP) for Kubernetes which allows Pods to use enterprise grade persistent storage.
  • A vSphere datastore is an abstraction which hides storage details (such as LUNs) and provides a uniform interface for storing persistent data.
  • the datastores can be of the type vSAN, VMFS, NFS & VVol.
  • VMFS (Virtual Machine File System) is a cluster file system that allows virtualization to scale beyond a single node for multiple VMware ESX servers.
  • NFS (Network File System) is a distributed file protocol to access storage over network like local storage.
  • vSphere Cloud Provider supports every storage primitive exposed by Kubernetes
  • Kubernetes PVs are defined in Pod specifications.
  • PVCs when using Dynamic Provisioning (preferred).
張 旭

MySQL :: MySQL 5.7 Reference Manual :: 20.2 Introducing InnoDB Cluster - 0 views

  • A group of MySQL servers can be configured to create a cluster using MySQL Shell
  • The cluster of servers has a single master, called the primary, which acts as the read-write master.
  • Multiple secondary servers are replicas of the master
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  • A client application is connected to the primary via MySQL Router
  • MySQL Shell also requires Python 2.7 and above to run cluster provisioning scripts
  • AdminAPI, which enables you to create and administer an InnoDB cluster, using either JavaScript or Python scripting
  • Caches the metadata of the InnoDB cluster and performs high availability routing to the MySQL Server instances which make up the cluster
  • Group Replication mechanism to allow data to be replicated from the primary to the secondaries in the cluster
  • AdminAPI is available as of MySQL Shell 1.0.8.
張 旭

Introducing Infrastructure as Code | Linode - 0 views

  • Infrastructure as Code (IaC) is a technique for deploying and managing infrastructure using software, configuration files, and automated tools.
  • With the older methods, technicians must configure a device manually, perhaps with the aid of an interactive tool. Information is added to configuration files by hand or through the use of ad-hoc scripts. Configuration wizards and similar utilities are helpful, but they still require hands-on management. A small group of experts owns the expertise, the process is typically poorly defined, and errors are common.
  • The development of the continuous integration and continuous delivery (CI/CD) pipeline made the idea of treating infrastructure as software much more attractive.
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  • Infrastructure as Code takes advantage of the software development process, making use of quality assurance and test automation techniques.
  • Consistency/Standardization
  • Each node in the network becomes what is known as a snowflake, with its own unique settings. This leads to a system state that cannot easily be reproduced and is difficult to debug.
  • With standard configuration files and software-based configuration, there is greater consistency between all equipment of the same type. A key IaC concept is idempotence.
  • Idempotence makes it easy to troubleshoot, test, stabilize, and upgrade all the equipment.
  • Infrastructure as Code is central to the culture of DevOps, which is a mix of development and operations
  • edits are always made to the source configuration files, never on the target.
  • A declarative approach describes the final state of a device, but does not mandate how it should get there. The specific IaC tool makes all the procedural decisions. The end state is typically defined through a configuration file, a JSON specification, or a similar encoding.
  • An imperative approach defines specific functions or procedures that must be used to configure the device. It focuses on what must happen, but does not necessarily describe the final state. Imperative techniques typically use scripts for the implementation.
  • With a push configuration, the central server pushes the configuration to the destination device.
  • If a device is mutable, its configuration can be changed while it is active
  • Immutable devices cannot be changed. They must be decommissioned or rebooted and then completely rebuilt.
  • an immutable approach ensures consistency and avoids drift. However, it usually takes more time to remove or rebuild a configuration than it does to change it.
  • System administrators should consider security issues as part of the development process.
  • Ansible is a very popular open source IaC application from Red Hat
  • Ansible is often used in conjunction with Kubernetes and Docker.
  • Linode offers a collection of several Ansible guides for a more comprehensive overview.
  • Pulumi permits the use of a variety of programming languages to deploy and manage infrastructure within a cloud environment.
  • Terraform allows users to provision data center infrastructure using either JSON or Terraform’s own declarative language.
  • Terraform manages resources through the use of providers, which are similar to APIs.
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Storage Classes | Kubernetes - 0 views

  • A StorageClass provides a way for administrators to describe the "classes" of storage they offer.
  • Kubernetes itself is unopinionated about what classes represent.
  • Each StorageClass contains the fields provisioner, parameters, and reclaimPolicy, which are used when a PersistentVolume belonging to the class needs to be dynamically provisioned.
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  • The name of a StorageClass object is significant, and is how users can request a particular class.
  • Administrators can specify a default StorageClass only for PVCs that don't request any particular class to bind to
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MySQL cluster vs Galera - How to make the right choice - 0 views

  • there is no “one size fits all” solution when coming to database clustering.
  • MySQL cluster contains the data nodes that store the cluster data and management node that store the cluster’s configuration.
  • MySQL clients first communicate with the management node and then connect directly to these data nodes.
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  • For synchronization of data in the data nodes, MySQL cluster uses a special data engine called NDB (Network Database).
  • it uses automatic shrading aka splitting of a large database into small units.
  • MySQL cluster avoids single point failure and ensures 99.99% availability.
  • MySQL cluster can provide a response time as low as less than 3 ms.
  • Galera Cluster consists of a database server and uses the Galera Replication Plugin to manage replication.
  • a multi-master database cluster that supports synchronous replication.
  • it provides multiple, up-to-date copies of the data.
  • there is a need for instant fail-over.
  • Galera cluster allows the read and write of data in any node.
  • Galera cluster include guaranteed write consistency, automatic node provisioning, etc.
  • Upon restoring the connection, the separated nodes will sync back and rejoin the cluster automatically.
  • there is no need to have management node like MySQL cluster.
  • it gives best results with the InnoDB storage engine.
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Introducing the MinIO Operator and Operator Console - 0 views

  • Object-storage-as-a-service is a game changer for IT.
  • provision multi-tenant object storage as a service.
  • have the skill set to create, deploy, tune, scale and manage modern, application oriented object storage using Kubernetes
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  • MinIO is purpose-built to take full advantage of the Kubernetes architecture.
  • MinIO and Kubernetes work together to simplify infrastructure management, providing a way to manage object storage infrastructure within the Kubernetes toolset.  
  • The operator pattern extends Kubernetes's familiar declarative API model with custom resource definitions (CRDs) to perform common operations like resource orchestration, non-disruptive upgrades, cluster expansion and to maintain high-availability
  • The Operator uses the command set kubectl that the Kubernetes community was already familiar with and adds the kubectl minio plugin . The MinIO Operator and the MinIO kubectl plugin facilitate the deployment and management of MinIO Object Storage on Kubernetes - which is how multi-tenant object storage as a service is delivered.
  • choosing a leader for a distributed application without an internal member election process
  • The Operator Console makes Kubernetes object storage easier still. In this graphical user interface, MinIO created something so simple that anyone in the organization can create, deploy and manage object storage as a service.
  • The primary unit of managing MinIO on Kubernetes is the tenant.
  • The MinIO Operator can allocate multiple tenants within the same Kubernetes cluster.
  • Each tenant, in turn, can have different capacity (i.e: a small 500GB tenant vs a 100TB tenant), resources (1000m CPU and 4Gi RAM vs 4000m CPU and 16Gi RAM) and servers (4 pods vs 16 pods), as well a separate configurations regarding Identity Providers, Encryption and versions.
  • each tenant is a cluster of server pools (independent sets of nodes with their own compute, network, and storage resources), that, while sharing the same physical infrastructure, are fully isolated from each other in their own namespaces.
  • Each tenant runs their own MinIO cluster, fully isolated from other tenants
  • Each tenant scales independently by federating clusters across geographies.
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Language Server Protocol - Wikipedia - 0 views

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