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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

DNS - FreeIPA - 0 views

www.freeipa.org/DNS

dns networking system bind freeipa

shared by 張 旭 on 30 Aug 19 - No Cached
  • FreeIPA DNS integration allows administrator to manage and serve DNS records in a domain using the same CLI or Web UI as when managing identities and policies.
  • Single-master DNS is error prone, especially for inexperienced admins.
  • a decent Kerberos experience.
  • ...14 more annotations...
  • Goal is NOT to provide general-purpose DNS server.
  • DNS component in FreeIPA is optional and user may choose to manage all DNS records manually in other third party DNS server.
  • Clients can be configured to automatically run DNS updates (nsupdate) when their IP address changes and thus keeping its DNS record up-to-date. DNS zones can be configured to synchronize client's reverse (PTR) record along with the forward (A, AAAA) DNS record.
  • It is extremely hard to change DNS domain in existing installations so it is better to think ahead.
  • You should only use names which are delegated to you by the parent domain.
  • Not respecting this rule will cause problems sooner or later!
  • DNSSEC validation.
  • For internal names you can use arbitrary sub-domain in a DNS sub-tree you own, e.g. int.example.com.. Always respect rules from the previous section.
  • General advice about DNS views is do not use them because views make DNS deployment harder to maintain and security benefits are questionable (when compared with ACL).
  • The DNS integration is based on the bind-dyndb-ldap project, which enhances BIND name server to be able to use FreeIPA server LDAP instance as a data backend (data are stored in cn=dns entry, using schema defined by bind-dyndb-ldap
  • FreeIPA LDAP directory information tree is by default accessible to any user in the network
  • As DNS data are often considered as sensitive and as having access to cn=dns tree would be basically equal to being able to run zone transfer to all FreeIPA managed DNS zones, contents of this tree in LDAP are hidden by default.
  • standard system log (/var/log/messages or system journal)
  • BIND configuration (/etc/named.conf) can be updated to produce a more detailed log.
  • 張 旭 on 30 Aug 19
     
    "FreeIPA DNS integration allows administrator to manage and serve DNS records in a domain using the same CLI or Web UI as when managing identities and policies."
張 旭

pre-commit - 0 views

pre-commit.com

programming code development

shared by 張 旭 on 21 Dec 18 - No Cached
  • a multi-language package manager for pre-commit hooks
  • pre-commit is specifically designed to not require root access
  • We copied and pasted unwieldy bash scripts from project to project and had to manually change the hooks to work for different project structures.
  • ...3 more annotations...
  • adding pre-commit plugins to your project is done with the .pre-commit-config.yaml configuration file.
  • The pre-commit config file describes what repositories and hooks are installed.
  • This configuration says to download the pre-commit-hooks project and run its trailing-whitespace hook
  • 張 旭 on 21 Dec 18
     
    "a multi-language package manager for pre-commit hooks"
crazylion lee

gerrit - Gerrit Code Review - Google Project Hosting - 0 views

code.google.com/gerrit

git codereview review code

shared by crazylion lee on 08 Apr 15 - No Cached
  • crazylion lee on 08 Apr 15
     
    "Web based code review and project management for Git based projects. "
crazylion lee

CocoaPods.org - 0 views

cocoapods.org

ios package manager

shared by crazylion lee on 02 Oct 15 - No Cached
  • crazylion lee on 02 Oct 15
     
    "CocoaPods is the dependency manager for Swift and Objective-C Cocoa projects. It has over ten thousand libraries and can help you scale your projects elegantly."
crazylion lee

Proxmox VE - 0 views

pve.proxmox.com/Main_Page

virtual vm management

shared by crazylion lee on 04 Dec 16 - No Cached
  • crazylion lee on 04 Dec 16
     
    " Proxmox Virtual Environment is an open source server virtualization management solution based on QEMU/KVM and LXC. You can manage virtual machines, containers, highly available clusters, storage and networks with an integrated, easy-to-use web interface or via CLI. Proxmox VE code is licensed under the GNU Affero General Public License, version 3. The project is developed and maintained by Proxmox Server Solutions GmbH."
crazylion lee

Duet Project Management - 0 views

duetapp.com

projectmanagement basecamp project-management project management

shared by crazylion lee on 04 Sep 16 - No Cached
  • crazylion lee on 04 Sep 16
     
    "Duet is self hosted so your data is always private, and it's completely brandable so that it matches your business. Best of all, its low one time fee means you will save hundreds over similar software "
crazylion lee

Task Management for Teams - MeisterTask - 0 views

www.meistertask.com

tasks management productivity collaboration projectmanagement

shared by crazylion lee on 24 Nov 16 - No Cached
  • crazylion lee on 24 Nov 16
     
    "The most intuitive project and task management tool on the web"
張 旭

Volumes - Kubernetes - 0 views

kubernetes.io/...volumes

kubernetes volume disk nfs

shared by 張 旭 on 28 May 19 - No Cached
  • On-disk files in a Container are ephemeral,
  • when a Container crashes, kubelet will restart it, but the files will be lost - the Container starts with a clean state
  • In Docker, a volume is simply a directory on disk or in another Container.
  • ...105 more annotations...
  • A Kubernetes volume, on the other hand, has an explicit lifetime - the same as the Pod that encloses it.
  • a volume outlives any Containers that run within the Pod, and data is preserved across Container restarts.
    • 張 旭
      張 旭 on 06 Jul 19
       
      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
      張 旭 on 06 Jul 19
       
      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

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.
張 旭

Serverless Architectures - 0 views

martinfowler.com/...serverless.html

development architecture system server backend

shared by 張 旭 on 12 Jul 16 - No Cached
  • Serverless was first used to describe applications that significantly or fully depend on 3rd party applications / services (‘in the cloud’) to manage server-side logic and state.
  • ‘rich client’ applications (think single page web apps, or mobile apps) that use the vast ecosystem of cloud accessible databases (like Parse, Firebase), authentication services (Auth0, AWS Cognito), etc.
  • ‘(Mobile) Backend as a Service’
  • ...33 more annotations...
  • Serverless can also mean applications where some amount of server-side logic is still written by the application developer but unlike traditional architectures is run in stateless compute containers that are event-triggered, ephemeral (may only last for one invocation), and fully managed by a 3rd party.
  • ‘Functions as a service
  • AWS Lambda is one of the most popular implementations of FaaS at present,
  • A good example is Auth0 - they started initially with BaaS ‘Authentication as a Service’, but with Auth0 Webtask they are entering the FaaS space.
  • a typical ecommerce app
  • a backend data-processing service
  • with zero administration.
  • FaaS offerings do not require coding to a specific framework or library.
  • Horizontal scaling is completely automatic, elastic, and managed by the provider
  • Functions in FaaS are triggered by event types defined by the provider.
  • a FaaS-supported message broker
  • from a deployment-unit point of view FaaS functions are stateless.
  • allowed the client direct access to a subset of our database
  • deleted the authentication logic in the original application and have replaced it with a third party BaaS service
  • The client is in fact well on its way to becoming a Single Page Application.
  • implement a FaaS function that responds to http requests via an API Gateway
  • port the search code from the Pet Store server to the Pet Store Search function
  • replaced a long lived consumer application with a FaaS function that runs within the event driven context
  • server applications - is a key difference when comparing with other modern architectural trends like containers and PaaS
  • the only code that needs to change when moving to FaaS is the ‘main method / startup’ code, in that it is deleted, and likely the specific code that is the top-level message handler (the ‘message listener interface’ implementation), but this might only be a change in method signature
  • With FaaS you need to write the function ahead of time to assume parallelism
  • Most providers also allow functions to be triggered as a response to inbound http requests, typically in some kind of API gateway
  • you should assume that for any given invocation of a function none of the in-process or host state that you create will be available to any subsequent invocation.
  • FaaS functions are either naturally stateless
  • store state across requests or for further input to handle a request.
  • certain classes of long lived task are not suited to FaaS functions without re-architecture
  • if you were writing a low-latency trading application you probably wouldn’t want to use FaaS systems at this time
  • An API Gateway is an HTTP server where routes / endpoints are defined in configuration and each route is associated with a FaaS function.
  • API Gateway will allow mapping from http request parameters to inputs arguments for the FaaS function
  • API Gateways may also perform authentication, input validation, response code mapping, etc.
  • the Serverless Framework makes working with API Gateway + Lambda significantly easier than using the first principles provided by AWS.
  • Apex - a project to ‘Build, deploy, and manage AWS Lambda functions with ease.'
  • 'Serverless' to mean the union of a couple of other ideas - 'Backend as a Service' and 'Functions as a Service'.
張 旭

Helm | - 0 views

helm.sh/developing_charts

helm kubernetes chart development devops package

shared by 張 旭 on 05 Aug 19 - No Cached
  • A chart is a collection of files that describe a related set of Kubernetes resources.
  • A single chart might be used to deploy something simple, like a memcached pod, or something complex, like a full web app stack with HTTP servers, databases, caches, and so on.
  • Charts are created as files laid out in a particular directory tree, then they can be packaged into versioned archives to be deployed.
  • ...170 more annotations...
  • A chart is organized as a collection of files inside of a directory.
  • values.yaml # The default configuration values for this chart
  • charts/ # A directory containing any charts upon which this chart depends.
  • templates/ # A directory of templates that, when combined with values, # will generate valid Kubernetes manifest files.
  • version: A SemVer 2 version (required)
  • apiVersion: The chart API version, always "v1" (required)
  • Every chart must have a version number. A version must follow the SemVer 2 standard.
  • non-SemVer names are explicitly disallowed by the system.
  • When generating a package, the helm package command will use the version that it finds in the Chart.yaml as a token in the package name.
  • the appVersion field is not related to the version field. It is a way of specifying the version of the application.
  • appVersion: The version of the app that this contains (optional). This needn't be SemVer.
  • If the latest version of a chart in the repository is marked as deprecated, then the chart as a whole is considered to be deprecated.
  • deprecated: Whether this chart is deprecated (optional, boolean)
  • one chart may depend on any number of other charts.
  • dependencies can be dynamically linked through the requirements.yaml file or brought in to the charts/ directory and managed manually.
  • the preferred method of declaring dependencies is by using a requirements.yaml file inside of your chart.
  • A requirements.yaml file is a simple file for listing your dependencies.
  • The repository field is the full URL to the chart repository.
  • you must also use helm repo add to add that repo locally.
  • helm dependency update and it will use your dependency file to download all the specified charts into your charts/ directory for you.
  • When helm dependency update retrieves charts, it will store them as chart archives in the charts/ directory.
  • Managing charts with requirements.yaml is a good way to easily keep charts updated, and also share requirements information throughout a team.
  • All charts are loaded by default.
  • The condition field holds one or more YAML paths (delimited by commas). If this path exists in the top parent’s values and resolves to a boolean value, the chart will be enabled or disabled based on that boolean value.
  • The tags field is a YAML list of labels to associate with this chart.
  • all charts with tags can be enabled or disabled by specifying the tag and a boolean value.
  • The --set parameter can be used as usual to alter tag and condition values.
  • Conditions (when set in values) always override tags.
  • The first condition path that exists wins and subsequent ones for that chart are ignored.
  • The keys containing the values to be imported can be specified in the parent chart’s requirements.yaml file using a YAML list. Each item in the list is a key which is imported from the child chart’s exports field.
  • specifying the key data in our import list, Helm looks in the exports field of the child chart for data key and imports its contents.
  • the parent key data is not contained in the parent’s final values. If you need to specify the parent key, use the ‘child-parent’ format.
  • To access values that are not contained in the exports key of the child chart’s values, you will need to specify the source key of the values to be imported (child) and the destination path in the parent chart’s values (parent).
  • To drop a dependency into your charts/ directory, use the helm fetch command
  • A dependency can be either a chart archive (foo-1.2.3.tgz) or an unpacked chart directory.
  • name cannot start with _ or .. Such files are ignored by the chart loader.
  • a single release is created with all the objects for the chart and its dependencies.
  • Helm Chart templates are written in the Go template language, with the addition of 50 or so add-on template functions from the Sprig library and a few other specialized functions
  • When Helm renders the charts, it will pass every file in that directory through the template engine.
  • Chart developers may supply a file called values.yaml inside of a chart. This file can contain default values.
  • Chart users may supply a YAML file that contains values. This can be provided on the command line with helm install.
  • When a user supplies custom values, these values will override the values in the chart’s values.yaml file.
  • Template files follow the standard conventions for writing Go templates
  • {{default "minio" .Values.storage}}
  • Values that are supplied via a values.yaml file (or via the --set flag) are accessible from the .Values object in a template.
  • pre-defined, are available to every template, and cannot be overridden
  • the names are case sensitive
  • Release.Name: The name of the release (not the chart)
  • Release.IsUpgrade: This is set to true if the current operation is an upgrade or rollback.
  • Release.Revision: The revision number. It begins at 1, and increments with each helm upgrade
  • Chart: The contents of the Chart.yaml
  • Files: A map-like object containing all non-special files in the chart.
  • Files can be accessed using {{index .Files "file.name"}} or using the {{.Files.Get name}} or {{.Files.GetString name}} functions.
  • .helmignore
  • access the contents of the file as []byte using {{.Files.GetBytes}}
  • Any unknown Chart.yaml fields will be dropped
  • Chart.yaml cannot be used to pass arbitrarily structured data into the template.
  • A values file is formatted in YAML.
  • A chart may include a default values.yaml file
  • be merged into the default values file.
  • The default values file included inside of a chart must be named values.yaml
  • accessible inside of templates using the .Values object
  • Values files can declare values for the top-level chart, as well as for any of the charts that are included in that chart’s charts/ directory.
  • Charts at a higher level have access to all of the variables defined beneath.
  • lower level charts cannot access things in parent charts
  • Values are namespaced, but namespaces are pruned.
  • the scope of the values has been reduced and the namespace prefix removed
  • Helm supports special “global” value.
  • a way of sharing one top-level variable with all subcharts, which is useful for things like setting metadata properties like labels.
  • If a subchart declares a global variable, that global will be passed downward (to the subchart’s subcharts), but not upward to the parent chart.
  • global variables of parent charts take precedence over the global variables from subcharts.
  • helm lint
  • A chart repository is an HTTP server that houses one or more packaged charts
  • Any HTTP server that can serve YAML files and tar files and can answer GET requests can be used as a repository server.
  • Helm does not provide tools for uploading charts to remote repository servers.
  • the only way to add a chart to $HELM_HOME/starters is to manually copy it there.
  • Helm provides a hook mechanism to allow chart developers to intervene at certain points in a release’s life cycle.
  • Execute a Job to back up a database before installing a new chart, and then execute a second job after the upgrade in order to restore data.
  • Hooks are declared as an annotation in the metadata section of a manifest
  • Hooks work like regular templates, but they have special annotations
  • pre-install
  • post-install: Executes after all resources are loaded into Kubernetes
  • pre-delete
  • post-delete: Executes on a deletion request after all of the release’s resources have been deleted.
  • pre-upgrade
  • post-upgrade
  • pre-rollback
  • post-rollback: Executes on a rollback request after all resources have been modified.
  • crd-install
  • test-success: Executes when running helm test and expects the pod to return successfully (return code == 0).
  • test-failure: Executes when running helm test and expects the pod to fail (return code != 0).
  • Hooks allow you, the chart developer, an opportunity to perform operations at strategic points in a release lifecycle
  • Tiller then loads the hook with the lowest weight first (negative to positive)
  • Tiller returns the release name (and other data) to the client
  • If the resources is a Job kind, Tiller will wait until the job successfully runs to completion.
  • if the job fails, the release will fail. This is a blocking operation, so the Helm client will pause while the Job is run.
  • If they have hook weights (see below), they are executed in weighted order. Otherwise, ordering is not guaranteed.
  • good practice to add a hook weight, and set it to 0 if weight is not important.
  • The resources that a hook creates are not tracked or managed as part of the release.
  • leave the hook resource alone.
  • To destroy such resources, you need to either write code to perform this operation in a pre-delete or post-delete hook or add "helm.sh/hook-delete-policy" annotation to the hook template file.
  • Hooks are just Kubernetes manifest files with special annotations in the metadata section
  • One resource can implement multiple hooks
  • no limit to the number of different resources that may implement a given hook.
  • When subcharts declare hooks, those are also evaluated. There is no way for a top-level chart to disable the hooks declared by subcharts.
  • Hook weights can be positive or negative numbers but must be represented as strings.
  • sort those hooks in ascending order.
  • Hook deletion policies
  • "before-hook-creation" specifies Tiller should delete the previous hook before the new hook is launched.
  • By default Tiller will wait for 60 seconds for a deleted hook to no longer exist in the API server before timing out.
  • Custom Resource Definitions (CRDs) are a special kind in Kubernetes.
  • The crd-install hook is executed very early during an installation, before the rest of the manifests are verified.
  • A common reason why the hook resource might already exist is that it was not deleted following use on a previous install/upgrade.
  • Helm uses Go templates for templating your resource files.
  • two special template functions: include and required
  • include function allows you to bring in another template, and then pass the results to other template functions.
  • The required function allows you to declare a particular values entry as required for template rendering.
  • If the value is empty, the template rendering will fail with a user submitted error message.
  • When you are working with string data, you are always safer quoting the strings than leaving them as bare words
  • Quote Strings, Don’t Quote Integers
  • when working with integers do not quote the values
  • env variables values which are expected to be string
  • to include a template, and then perform an operation on that template’s output, Helm has a special include function
  • The above includes a template called toYaml, passes it $value, and then passes the output of that template to the nindent function.
  • Go provides a way for setting template options to control behavior when a map is indexed with a key that’s not present in the map
  • The required function gives developers the ability to declare a value entry as required for template rendering.
  • The tpl function allows developers to evaluate strings as templates inside a template.
  • Rendering a external configuration file
  • (.Files.Get "conf/app.conf")
  • Image pull secrets are essentially a combination of registry, username, and password.
  • Automatically Roll Deployments When ConfigMaps or Secrets change
  • configmaps or secrets are injected as configuration files in containers
  • a restart may be required should those be updated with a subsequent helm upgrade
  • The sha256sum function can be used to ensure a deployment’s annotation section is updated if another file changes
  • checksum/config: {{ include (print $.Template.BasePath "/configmap.yaml") . | sha256sum }}
  • helm upgrade --recreate-pods
  • "helm.sh/resource-policy": keep
  • resources that should not be deleted when Helm runs a helm delete
  • this resource becomes orphaned. Helm will no longer manage it in any way.
  • create some reusable parts in your chart
  • In the templates/ directory, any file that begins with an underscore(_) is not expected to output a Kubernetes manifest file.
  • by convention, helper templates and partials are placed in a _helpers.tpl file.
  • The current best practice for composing a complex application from discrete parts is to create a top-level umbrella chart that exposes the global configurations, and then use the charts/ subdirectory to embed each of the components.
  • SAP’s Converged charts: These charts install SAP Converged Cloud a full OpenStack IaaS on Kubernetes. All of the charts are collected together in one GitHub repository, except for a few submodules.
  • Deis’s Workflow: This chart exposes the entire Deis PaaS system with one chart. But it’s different from the SAP chart in that this umbrella chart is built from each component, and each component is tracked in a different Git repository.
  • YAML is a superset of JSON
  • any valid JSON structure ought to be valid in YAML.
  • As a best practice, templates should follow a YAML-like syntax unless the JSON syntax substantially reduces the risk of a formatting issue.
  • There are functions in Helm that allow you to generate random data, cryptographic keys, and so on.
  • a chart repository is a location where packaged charts can be stored and shared.
  • A chart repository is an HTTP server that houses an index.yaml file and optionally some packaged charts.
  • Because a chart repository can be any HTTP server that can serve YAML and tar files and can answer GET requests, you have a plethora of options when it comes down to hosting your own chart repository.
  • It is not required that a chart package be located on the same server as the index.yaml file.
  • A valid chart repository must have an index file. The index file contains information about each chart in the chart repository.
  • The Helm project provides an open-source Helm repository server called ChartMuseum that you can host yourself.
  • $ helm repo index fantastic-charts --url https://fantastic-charts.storage.googleapis.com
  • A repository will not be added if it does not contain a valid index.yaml
  • add the repository to their helm client via the helm repo add [NAME] [URL] command with any name they would like to use to reference the repository.
  • Helm has provenance tools which help chart users verify the integrity and origin of a package.
  • Integrity is established by comparing a chart to a provenance record
  • The provenance file contains a chart’s YAML file plus several pieces of verification information
  • Chart repositories serve as a centralized collection of Helm charts.
  • Chart repositories must make it possible to serve provenance files over HTTP via a specific request, and must make them available at the same URI path as the chart.
  • We don’t want to be “the certificate authority” for all chart signers. Instead, we strongly favor a decentralized model, which is part of the reason we chose OpenPGP as our foundational technology.
  • The Keybase platform provides a public centralized repository for trust information.
  • A chart contains a number of Kubernetes resources and components that work together.
  • A test in a helm chart lives under the templates/ directory and is a pod definition that specifies a container with a given command to run.
  • The pod definition must contain one of the helm test hook annotations: helm.sh/hook: test-success or helm.sh/hook: test-failure
  • helm test
  • nest your test suite under a tests/ directory like <chart-name>/templates/tests/
張 旭

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

4sysops.com/...-vs-ansible-awx-for-automation

ansible devops system config provision

shared by 張 旭 on 15 Aug 19 - No Cached
  • 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
crazylion lee

Keepalived for Linux - 0 views

www.keepalived.org

clustering HA failover keepalived

shared by crazylion lee on 15 Aug 14 - Cached
  • crazylion lee on 15 Aug 14
     
    Keepalived is a routing software written in C. The main goal of this project is to provide simple and robust facilities for loadbalancing and high-availability to Linux system and Linux based infrastructures. Loadbalancing framework relies on well-known and widely used Linux Virtual Server (IPVS) kernel module providing Layer4 loadbalancing. Keepalived implements a set of checkers to dynamically and adaptively maintain and manage loadbalanced server pool according their health. On the other hand high-availability is achieved by VRRP protocol. VRRP is a fundamental brick for router failover. In addition, Keepalived implements a set of hooks to the VRRP finite state machine providing low-level and high-speed protocol interactions. Keepalived frameworks can be used independently or all together to provide resilient infrastructures.
張 旭

LXC vs Docker: Why Docker is Better | UpGuard - 0 views

www.upguard.com/...docker-vs-lxc

docker container devops

shared by 張 旭 on 28 Jun 21 - No Cached
  • LXC (LinuX Containers) is a OS-level virtualization technology that allows creation and running of multiple isolated Linux virtual environments (VE) on a single control host.
  • Docker, previously called dotCloud, was started as a side project and only open-sourced in 2013. It is really an extension of LXC’s capabilities.
  • run processes in isolation.
  • ...35 more annotations...
  • Docker is developed in the Go language and utilizes LXC, cgroups, and the Linux kernel itself. Since it’s based on LXC, a Docker container does not include a separate operating system; instead it relies on the operating system’s own functionality as provided by the underlying infrastructure.
  • Docker acts as a portable container engine, packaging the application and all its dependencies in a virtual container that can run on any Linux server.
  • a VE there is no preloaded emulation manager software as in a VM.
  • In a VE, the application (or OS) is spawned in a container and runs with no added overhead, except for a usually minuscule VE initialization process.
  • LXC will boast bare metal performance characteristics because it only packages the needed applications.
  • the OS is also just another application that can be packaged too.
  • a VM, which packages the entire OS and machine setup, including hard drive, virtual processors and network interfaces. The resulting bloated mass usually takes a long time to boot and consumes a lot of CPU and RAM.
  • don’t offer some other neat features of VM’s such as IaaS setups and live migration.
  • LXC as supercharged chroot on Linux. It allows you to not only isolate applications, but even the entire OS.
  • Libvirt, which allows the use of containers through the LXC driver by connecting to 'lxc:///'.
  • 'LXC', is not compatible with libvirt, but is more flexible with more userspace tools.
  • Portable deployment across machines
  • Versioning: Docker includes git-like capabilities for tracking successive versions of a container
  • Component reuse: Docker allows building or stacking of already created packages.
  • Shared libraries: There is already a public registry (http://index.docker.io/ ) where thousands have already uploaded the useful containers they have created.
  • Docker taking the devops world by storm since its launch back in 2013.
  • LXC, while older, has not been as popular with developers as Docker has proven to be
  • LXC having a focus on sys admins that’s similar to what solutions like the Solaris operating system, with its Solaris Zones, Linux OpenVZ, and FreeBSD, with its BSD Jails virtualization system
  • it started out being built on top of LXC, Docker later moved beyond LXC containers to its own execution environment called libcontainer.
  • Unlike LXC, which launches an operating system init for each container, Docker provides one OS environment, supplied by the Docker Engine
  • LXC tooling sticks close to what system administrators running bare metal servers are used to
  • The LXC command line provides essential commands that cover routine management tasks, including the creation, launch, and deletion of LXC containers.
  • Docker containers aim to be even lighter weight in order to support the fast, highly scalable, deployment of applications with microservice architecture.
  • With backing from Canonical, LXC and LXD have an ecosystem tightly bound to the rest of the open source Linux community.
  • Docker Swarm
  • Docker Trusted Registry
  • Docker Compose
  • Docker Machine
  • Kubernetes facilitates the deployment of containers in your data center by representing a cluster of servers as a single system.
  • Swarm is Docker’s clustering, scheduling and orchestration tool for managing a cluster of Docker hosts. 
  • rkt is a security minded container engine that uses KVM for VM-based isolation and packs other enhanced security features. 
  • Apache Mesos can run different kinds of distributed jobs, including containers. 
  • Elastic Container Service is Amazon’s service for running and orchestrating containerized applications on AWS
  • LXC offers the advantages of a VE on Linux, mainly the ability to isolate your own private workloads from one another. It is a cheaper and faster solution to implement than a VM, but doing so requires a bit of extra learning and expertise.
  • Docker is a significant improvement of LXC’s capabilities.
張 旭

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

stackoverflow.com/...-if-i-have-a-jquery-background

jquery javascript angular programming architecture development google angularjs web

shared by 張 旭 on 02 Oct 13 - No Cached
  • in AngularJS, we have a separate model layer that we can manage in any way we want, completely independently from the view.
  • keep your concerns separate
  • do DOM manipulation and augment your view with directives
  • ...34 more annotations...
  • DI means that you can declare components very freely and then from any other component, just ask for an instance of it and it will be granted
  • do test-driven development iteratively in AngularJS!
  • only do DOM manipulation in a directive
  • with ngClass we can dynamically update the class;
  • ngBind allows two-way data binding;
  • ngShow and ngHide programmatically show or hide an element;
  • The less DOM manipulation, the easier directives are to test, the easier they are to style, the easier they are to change in the future, and the more re-usable and distributable they are.
  • still wrong.
  • Before doing DOM manipulation anywhere in your application, ask yourself if you really need to.
  • a few things wrong with this
  • jQuery was never necessary
  • use angular.element and our component will still work when dropped into a project that doesn't have jQuery.
  • just use angular.element
  • the element that is passed to the link function would already be a jQuery element!
  • directives aren't just collections of jQuery-like functions
  • Directives are actually extensions of HTML
  • If HTML doesn't do something you need it to do, you write a directive to do it for you, and then use it just as if it was part of HTML.
  • think how the team would accomplish it to fit right in with ngClick, ngClass, et al.
  • Don't even use jQuery. Don't even include it.
  • ry to think about how to do it within the confines the AngularJS.
  • In jQuery, selectors are used to find DOM elements and then bind/register event handlers to them.
  • Views are (declarative) HTML that contain AngularJS directives
  • Directives set up the event handlers behind the scenes for us and give us dynamic databinding.
  • Views are tied to models (via scopes). Views are a projection of the model
  • In AngularJS, think about models, rather than jQuery-selected DOM elements that hold your data.
  • AngularJS uses controllers and directives (each of which can have their own controller, and/or compile and linking functions) to remove behavior from the view/structure (HTML). Angular also has services and filters to help separate/organize your application.
  • Think about your models
  • Think about how you want to present your models -- your views.
  • using the necessary directives to get dynamic databinding.
  • Attach a controller to each view (using ng-view and routing, or ng-controller)
  • Make controllers as thin as possible.
  • You can do a lot with jQuery without knowing about how JavaScript prototypal inheritance works.
  • jQuery is a library
  • AngularJS is a beautiful client-side framework
張 旭

Persisting Data in Workflows: When to Use Caching, Artifacts, and Workspaces - CircleCI - 0 views

circleci.com/...ching-artifacts-and-workspaces

circleci deploy system CI volume share

shared by 張 旭 on 25 Nov 18 - No Cached
  • Repeatability is also important
  • When a CI process isn’t repeatable you’ll find yourself wasting time re-running jobs to get them to go green.
  • Workspaces persist data between jobs in a single Workflow.
  • ...9 more annotations...
  • Caching persists data between the same job in different Workflow builds.
  • Artifacts persist data after a Workflow has finished
  • When a Workspace is declared in a job, one or more files or directories can be added. Each addition creates a new layer in the Workspace filesystem. Downstreams jobs can then use this Workspace for its own needs or add more layers on top.
  • Unlike caching, Workspaces are not shared between runs as they no longer exists once a Workflow is complete.
  • Caching lets you reuse the data from expensive fetch operations from previous jobs.
  • A prime example is package dependency managers such as Yarn, Bundler, or Pip.
  • Caches are global within a project, a cache saved on one branch will be used by others so they should only be used for data that is OK to share across Branches
  • Artifacts are used for longer-term storage of the outputs of your build process.
  • If your project needs to be packaged in some form or fashion, say an Android app where the .apk file is uploaded to Google Play, that’s a great example of an artifact.
  • 張 旭 on 25 Nov 18
     
    "CircleCI 2.0 provides a number of different ways to move data into and out of jobs, persist data, and with the introduction of Workspaces, move data between jobs"
張 旭

Tagging AWS resources - AWS General Reference - 0 views

docs.aws.amazon.com/...aws_tagging.html

aws cloud

shared by 張 旭 on 20 Jan 22 - No Cached
  • assign metadata to your AWS resources in the form of tags.
  • a user-defined key and value
  • Tag keys are case sensitive.
  • ...17 more annotations...
  • tag values are case sensitive.
  • Tags are accessible to many AWS services, including billing.
  • personally identifiable information (PII)
  • apply it consistently across all resource types.
  • Use automated tools to help manage resource tags.
  • Use too many tags rather than too few tags.
  • Tag policies let you specify tagging rules that define valid key names and the values that are valid for each key.
  • Name – Identify individual resources
  • Environment – Distinguish between development, test, and production resources
  • Project – Identify projects that the resource supports
  • Owner – Identify who is responsible for the resource
  • Each resource can have a maximum of 50 user created tags.
  • For each resource, each tag key must be unique, and each tag key can have only one value.
  • Tag keys and values are case sensitive.
  • decide on a strategy for capitalizing tags, and consistently implement that strategy across all resource types.
  • AWS Cost Explorer and detailed billing reports let you break down AWS costs by tag.
  • An effective tagging strategy uses standardized tags and applies them consistently and programmatically across AWS resources.
  • 張 旭 on 20 Jan 22
     
    "assign metadata to your AWS resources in the form of tags."
張 旭

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

www.digitalocean.com/...and-use-docker-getting-started

docker system deploy

shared by 張 旭 on 26 Oct 14 - No Cached
  • docker as a project offers you the complete set of higher-level tools to carry everything that forms an application across systems and machines - virtual or physical - and brings along loads more of great benefits with it
  • docker daemon: used to manage docker (LXC) containers on the host it runs
  • docker CLI: used to command and communicate with the docker daemon
  • ...20 more annotations...
  • containers: directories containing everything-your-application
  • images: snapshots of containers or base OS (e.g. Ubuntu) images
  • Dockerfiles: scripts automating the building process of images
  • Docker containers are basically directories which can be packed (e.g. tar-archived) like any other, then shared and run across various different machines and platforms (hosts).
  • Linux Containers can be defined as a combination various kernel-level features (i.e. things that Linux-kernel can do) which allow management of applications (and resources they use) contained within their own environment
  • Each container is layered like an onion and each action taken within a container consists of putting another block (which actually translates to a simple change within the file system) on top of the previous one.
  • Each docker container starts from a docker image which forms the base for other applications and layers to come.
  • Docker images constitute the base of docker containers from which everything starts to form
  • a solid, consistent and dependable base with everything that is needed to run the applications
  • As more layers (tools, applications etc.) are added on top of the base, new images can be formed by committing these changes.
  • a Dockerfile for automated image building
  • Dockerfiles are scripts containing a successive series of instructions, directions, and commands which are to be executed to form a new docker image.
  • As you work with a container and continue to perform actions on it (e.g. download and install software, configure files etc.), to have it keep its state, you need to “commit”.
  • Please remember to “commit” all your changes.
  • When you "run" any process using an image, in return, you will have a container.
  • When the process is not actively running, this container will be a non-running container. Nonetheless, all of them will reside on your system until you remove them via rm command.
  • To create a new container, you need to use a base image and specify a command to run.
  • you can not change the command you run after having created a container (hence specifying one during "creation")
  • If you would like to save the progress and changes you made with a container, you can use “commit”
  • turns your container to an image
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