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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

Docker can now run within Docker - Docker Blog - 0 views

www.docker.com/...cker-can-now-run-within-docker

devops docker

shared by 張 旭 on 11 Mar 22 - No Cached
  • Docker 0.6 is the new “privileged” mode for containers. It allows you to run some containers with (almost) all the capabilities of their host machine, regarding kernel features and device access.
  • Among the (many!) possibilities of the “privileged” mode, you can now run Docker within Docker itself.
  • in the new privileged mode.
  • ...8 more annotations...
  • that /var/lib/docker should be a volume. This is important, because the filesystem of a container is an AUFS mountpoint, composed of multiple branches; and those branches have to be “normal” filesystems (i.e. not AUFS mountpoints).
  • /var/lib/docker, the place where Docker stores its containers, cannot be an AUFS filesystem.
  • we use them as a pass-through to the “normal” filesystem of the host machine.
  • The /var/lib/docker directory of the nested Docker will live somewhere in /var/lib/docker/volumes on the host system.
  • since the private Docker instances run in privileged mode, they can easily escalate to the host, and you probably don’t want this! If you really want to run something like this and expose it to the public, you will have to fine-tune the LXC template file, to restrict the capabilities and devices available to the Docker instances.
  • When you are inside a privileged container, you can always nest one more level
  • the LXC tools cannot start nested containers if the devices control group is not in its own hierarchy.
  • if you use AppArmor, you need a special policy to support nested containers.
crazylion lee

TMSU - 0 views

tmsu.org

filesystem linux tag file tagging

shared by crazylion lee on 27 Jun 16 - No Cached
  • crazylion lee on 27 Jun 16
     
    "TMSU is a tool for tagging your files. It provides a simple command-line tool for applying tags and a virtual filesystem so that you can get a tag-based view of your files from within any other program. TMSU does not alter your files in any way: they remain unchanged on disk, or on the network, wherever you put them. TMSU maintains its own database and you simply gain an additional view, which you can mount, based upon the tags you set up. The only commitment required is your time and there's absolutely no lock-in."
張 旭

Share Process Namespace between Containers in a Pod | Kubernetes - 0 views

kubernetes.io/...share-process-namespace

kubernetes pod namespace

shared by 張 旭 on 19 Aug 22 - No Cached
  • When process namespace sharing is enabled, processes in a container are visible to all other containers in the same pod.
  • It's even possible to access the file system of another container using the /proc/$pid/root link.
  • Pods share many resources so it makes sense they would also share a process namespace.
  • ...2 more annotations...
  • Processes are visible to other containers in the pod. This includes all information visible in /proc, such as passwords that were passed as arguments or environment variables. These are protected only by regular Unix permissions.
  • Container filesystems are visible to other containers in the pod through the /proc/$pid/root link. This makes debugging easier, but it also means that filesystem secrets are protected only by filesystem permissions.
  • 張 旭 on 19 Aug 22
     
    "When process namespace sharing is enabled, processes in a container are visible to all other containers in the same pod. "
crazylion lee

The memory models that underlie programming languages - 0 views

canonical.org/...memory-models

ai memory

shared by crazylion lee on 30 Jan 17 - No Cached
  • crazylion lee on 30 Jan 17
     
    " There are about six major conceptualizations of memory, which I'm calling "memory models"², that dominate today's programming. Three of them derive from the three most historically important programming languages of the 1950s - COBOL, LISP, and FORTRAN - and the other three derive from the three historically important data storage systems: magnetic tape, Unix-style hierarchical filesystems, and relational databases."
crazylion lee

OS.js - JavaScript Cloud/Web Desktop Platform - 0 views

os.js.org

javascript os

shared by crazylion lee on 04 Apr 16 - No Cached
  • crazylion lee on 04 Apr 16
     
    " OS.js is a JavaScript web desktop implementation for your browser with a fully-fledged window manager, Application APIs, GUI toolkits and filesystem abstraction."
張 旭

The Twelve-Factor App - 0 views

12factor.net/processes

development application programming

shared by 張 旭 on 20 Feb 19 - No Cached
  • stateless processes
  • a production deploy of a sophisticated app may use many process types, instantiated into zero or more running processes.
  • Twelve-factor processes are stateless and share-nothing.
  • ...6 more annotations...
  • Any data that needs to persist must be stored in a stateful backing service, typically a database.
  • The memory space or filesystem of the process can be used as a brief, single-transaction cache.
  • wipe out all local (e.g., memory and filesystem) state
  • compiling during the build stage
  • “sticky sessions” – that is, caching user session data in memory of the app’s process and expecting future requests from the same visitor to be routed to the same process.
  • Sticky sessions are a violation of twelve-factor and should never be used or relied upon
張 旭

Pods - Kubernetes - 0 views

kubernetes.io/...pod

kubernetes pod system

shared by 張 旭 on 05 Jul 19 - No Cached
  • Pods are the smallest deployable units of computing
  • A Pod (as in a pod of whales or pea pod) is a group of one or more containersA lightweight and portable executable image that contains software and all of its dependencies. (such as Docker containers), with shared storage/network, and a specification for how to run the containers.
  • A Pod’s contents are always co-located and co-scheduled, and run in a shared context.
  • ...32 more annotations...
  • A Pod models an application-specific “logical host”
  • application containers which are relatively tightly coupled
  • being executed on the same physical or virtual machine would mean being executed on the same logical host.
  • The shared context of a Pod is a set of Linux namespaces, cgroups, and potentially other facets of isolation
  • Containers within a Pod share an IP address and port space, and can find each other via localhost
  • Containers in different Pods have distinct IP addresses and can not communicate by IPC without special configuration. These containers usually communicate with each other via Pod IP addresses.
  • Applications within a Pod also have access to shared volumesA directory containing data, accessible to the containers in a pod. , which are defined as part of a Pod and are made available to be mounted into each application’s filesystem.
  • a Pod is modelled as a group of Docker containers with shared namespaces and shared filesystem volumes
    • 張 旭
      張 旭 on 05 Jul 19
       
      類似 docker-compose 裡面宣告的同一坨？
  • Pods are considered to be relatively ephemeral (rather than durable) entities.
  • Pods are created, assigned a unique ID (UID), and scheduled to nodes where they remain until termination (according to restart policy) or deletion.
  • it can be replaced by an identical Pod
  • When something is said to have the same lifetime as a Pod, such as a volume, that means that it exists as long as that Pod (with that UID) exists.
  • uses a persistent volume for shared storage between the containers
  • Pods serve as unit of deployment, horizontal scaling, and replication
  • The applications in a Pod all use the same network namespace (same IP and port space), and can thus “find” each other and communicate using localhost
  • flat shared networking space
  • Containers within the Pod see the system hostname as being the same as the configured name for the Pod.
  • Volumes enable data to survive container restarts and to be shared among the applications within the Pod.
  • Individual Pods are not intended to run multiple instances of the same application
  • The individual containers may be versioned, rebuilt and redeployed independently.
  • Pods aren’t intended to be treated as durable entities.
  • Controllers like StatefulSet can also provide support to stateful Pods.
  • When a user requests deletion of a Pod, the system records the intended grace period before the Pod is allowed to be forcefully killed, and a TERM signal is sent to the main process in each container.
  • Once the grace period has expired, the KILL signal is sent to those processes, and the Pod is then deleted from the API server.
  • grace period
  • Pod is removed from endpoints list for service, and are no longer considered part of the set of running Pods for replication controllers.
  • When the grace period expires, any processes still running in the Pod are killed with SIGKILL.
  • By default, all deletes are graceful within 30 seconds.
  • You must specify an additional flag --force along with --grace-period=0 in order to perform force deletions.
  • Force deletion of a Pod is defined as deletion of a Pod from the cluster state and etcd immediately.
  • StatefulSet Pods
  • Processes within the container get almost the same privileges that are available to processes outside a container.
張 旭

Using Workflows to Schedule Jobs - CircleCI - 1 views

circleci.com/workflows

circleci CI deploy system

shared by 張 旭 on 25 Nov 18 - No Cached
  • A workflow is a set of rules for defining a collection of jobs and their run order.
  • Schedule workflows for jobs that should only run periodically.
  • run multiple jobs in parallel
  • ...37 more annotations...
  • rerun just the failed job
  • Builds without workflows require a build job.
  • Refer the YAML Anchors/Aliases documentation for information about how to alias and reuse syntax to keep your .circleci/config.yml file small.
  • workflow orchestration with two parallel jobs
  • jobs run according to configured requirements, each job waiting to start until the required job finishes successfully
  • requires: key
  • fans-out to run a set of acceptance test jobs in parallel, and finally fans-in to run a common deploy job.
  • Holding a Workflow for a Manual Approval
  • Workflows can be configured to wait for manual approval of a job before continuing to the next job
  • add a job to the jobs list with the key type: approval
  • approval is a special job type that is only available to jobs under the workflow key
  • The name of the job to hold is arbitrary - it could be wait or pause, for example, as long as the job has a type: approval key in it.
  • schedule a workflow to run at a certain time for specific branches.
  • The triggers key is only added under your workflows key
  • using cron syntax to represent Coordinated Universal Time (UTC) for specified branches.
  • By default, a workflow is triggered on every git push
  • the commit workflow has no triggers key and will run on every git push
  • The nightly workflow has a triggers key and will run on the specified schedule
  • Cron step syntax (for example, */1, */20) is not supported.
  • use a context to share environment variables
  • use the same shared environment variables when initiated by a user who is part of the organization.
  • CircleCI does not run workflows for tags unless you explicitly specify tag filters.
  • CircleCI branch and tag filters support the Java variant of regex pattern matching.
  • Each workflow has an associated workspace which can be used to transfer files to downstream jobs as the workflow progresses.
  • The workspace is an additive-only store of data.
  • Jobs can persist data to the workspace
  • Downstream jobs can attach the workspace to their container filesystem.
  • Attaching the workspace downloads and unpacks each layer based on the ordering of the upstream jobs in the workflow graph.
  • Workflows that include jobs running on multiple branches may require data to be shared using workspaces
  • To persist data from a job and make it available to other jobs, configure the job to use the persist_to_workspace key.
  • Files and directories named in the paths: property of persist_to_workspace will be uploaded to the workflow’s temporary workspace relative to the directory specified with the root key.
  • Configure a job to get saved data by configuring the attach_workspace key.
  • persist_to_workspace
  • attach_workspace
  • To rerun only a workflow’s failed jobs, click the Workflows icon in the app and select a workflow to see the status of each job, then click the Rerun button and select Rerun from failed.
  • if you do not see your workflows triggering, a configuration error is preventing the workflow from starting.
  • check your Workflows page of the CircleCI app (not the Job page)
  • 張 旭 on 25 Nov 18
     
    "A workflow is a set of rules for defining a collection of jobs and their run order."
張 旭

你到底知不知道什麼是 Kubernetes? | Hwchiu Learning Note - 0 views

www.hwchiu.com/kubernetes-concept.html

kubernetes storage networking programming system

shared by 張 旭 on 03 Feb 19 - No Cached
  • Storage(儲存) 實際上一直都不是一個簡單處理的問題，從軟體面來看實際上牽扯到非常多的層級，譬如 Linux Kernel, FileSystem, Block/File-Level, Cache, Snapshot, Object Storage 等各式各樣的議題可以討論。
  • DRBD
  • 異地備援，容錯機制，快照，重複資料刪除等超多相關的議題基本上從來沒有一個完美的解法能夠滿足所有使用情境。
  • ...20 more annotations...
  • 管理者可能會直接在 NFS Server 上進行 MDADM 來設定相關的 Block Device 並且基於上面提供 Export 供 NFS 使用，甚至底層套用不同的檔案系統 (EXT4/BTF4) 來獲取不同的功能與效能。
  • Kubernetes 就只是 NFS Client 的角色
  • CSI(Container Storage Interface)。CSI 本身作為 Kubernetes 與 Storage Solution 的中介層。
  • 基本上 Pod 裡面每個 Container 會使用 Volume 這個物件來代表容器內的掛載點，而在外部實際上會透過 PVC 以及 PV 的方式來描述這個 Volume 背後的儲存方案伺服器的資訊。
  • 整體會透過 CSI 的元件們與最外面實際上的儲存設備連接，所有儲存相關的功能是否有實現，有支援全部都要仰賴最後面的實際提供者， kubernetes 只透過 CSI 的標準去執行。
  • 在網路部分也有與之對應的 CNI(Container Network Interface). kubernetes 透過 CNI 這個介面來與後方的 網路解決方案 溝通
  • CNI 最基本的要求就是在在對應的階段為對應的容器提供網路能力
  • 目前最常見也是 IPv4 + TCP/UDP 的傳輸方式，因此才會看到大部分的 CNI 都在講這些。
  • 希望所有容器彼此之間可以透過 IPv4 來互相存取彼此，不論是同節點或是跨節點的容器們都要可以滿足這個需求。
  • 容器間到底怎麼傳輸的，需不需要封裝，透過什麼網卡，要不要透過 NAT 處理? 這一切都是 CNI 介面背後的實現
  • 外部網路存取容器服務 (Service/Ingress)
  • kubernetes 在 Service/Ingress 中間自行實現了一個模組，大抵上稱為 kube-proxy, 其底層可以使用 iptables, IPVS, user-space software 等不同的實現方法，這部分是跟 CNI 完全無關。
  • CNI 跟 Service/Ingress 是會衝突的，也有可能彼此沒有配合，這中間沒有絕對的穩定整合。
  • CNI 一般會處理的部份，包含了容器內的 網卡數量,網卡名稱,網卡IP, 以及容器與外部節點的連接能力等
  • CRI (Container Runtime Interface) 或是 Device Plugin
  • 對於 kubernetes 來說，其實本身並不在意到底底下的容器化技術實際上是怎麼實現的，你要用 Docker, rkt, CRI-O 都無所謂，甚至背後是一個偽裝成 Container 的 Virtaul Machine virtlet 都可以。
  • 去思考到底為什麼自己本身的服務需要容器化，容器化可以帶來什麼優點
  • 太多太多的人都認為只要寫一個 Dockerfile 將原先的應用程式們全部包裝起來放在一起就是一個很好的容器 來使用了。
  • 最後就會發現根本把 Container 當作 Virtual Machine 來使用，然後再補一句 Contaienr 根本不好用啊
  • 容器化 不是把直接 Virtual Machine 的使用習慣換個環境使用就叫做 容器化，而是要從概念上去暸解與使用
張 旭

Storing Sessions in a Database, by Chris Shiflett - 0 views

shiflett.org/...storing-sessions-in-a-database

php session database

shared by 張 旭 on 14 Jan 19 - Cached
  • to store sessions in a database rather than the filesystem
  • server affinity (methods that direct requests from the same client to the same server)
  • store sessions in a central database that is common to all servers
  • ...6 more annotations...
  • security concerns
  • PHP provides a function that lets you override the default session mechanism by specifying the names of your own functions for taking care of the distinct tasks
  • The handler PHP uses to handle data serialization is defined by the session.serialize_handler configuration directive. It is set to php by default.
  • REPLACE
  • REPLACE, which behaves exactly like INSERT, except that it handles cases where a record already exists with the same session identifier by first deleting that record.
  • the _write() function keeps the timestamp of the last access in the access column for each record, this can be used to determine which records to delete.
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

Kubernetes Volumes Guide - Examples for NFS and Persistent Volume - 0 views

matthewpalmer.net/...ple-nfs-persistent-volume.html

kubernetes volume storage

shared by 張 旭 on 07 Jul 19 - No Cached
  • Persistent volumes exist beyond containers, pods, and nodes.
  • Volumes also let you share data between containers in the same pod.
  • data in that volume will be destroyed when the pod is restarted.
  • ...9 more annotations...
  • Persistent volumes are long-term storage in your Kubernetes cluster.
  • A pod uses a persistent volume claim to to get read and write access to the persistent volume.
  • NFS stands for Network File System – it's a shared filesystem that can be accessed over the network.
  • The NFS must already exist – Kubernetes doesn't run the NFS, pods in just access it.
  • what's already stored in the NFS is not deleted when a pod is destroyed. Data is persistent.
  • an NFS can be accessed from multiple pods at the same time. An NFS can be used to share data between pods!
  • volumes: - name: nfs-volume nfs: # URL for the NFS server server: 10.108.211.244 # Change this! path: /
  • volumeMounts: - name: nfs-volume mountPath: /var/nfs
  • Just add the volume to each pod, and add a volume mount to use the NFS volume from each container.
  • 張 旭 on 07 Jul 19
     
    "Persistent volumes exist beyond containers, pods, and nodes. "
張 旭

鳥哥的 Linux 私房菜 -- 第零章、計算機概論 - 0 views

linux.vbird.org/...0105computers.php

system

shared by 張 旭 on 22 Jun 21 - No Cached
  • 但因為 CPU 的運算速度比其他的設備都要來的快，又為了要滿足 FSB 的頻率，因此廠商就在 CPU 內部再進行加速， 於是就有所謂的外頻與倍頻了。
  • 中央處理器 (Central Processing Unit, CPU)，CPU 為一個具有特定功能的晶片， 裡頭含有微指令集，如果你想要讓主機進行什麼特異的功能，就得要參考這顆 CPU 是否有相關內建的微指令集才可以。
  • CPU 內又可分為兩個主要的單元，分別是： 算數邏輯單元與控制單元。
  • ...63 more annotations...
  • CPU 讀取的資料都是從主記憶體來的！ 主記憶體內的資料則是從輸入單元所傳輸進來！而 CPU 處理完畢的資料也必須要先寫回主記憶體中，最後資料才從主記憶體傳輸到輸出單元。
  • 重點在於 CPU 與主記憶體。 特別要看的是實線部分的傳輸方向，基本上資料都是流經過主記憶體再轉出去的！
  • CPU 實際要處理的資料則完全來自於主記憶體 (不管是程式還是一般文件資料)！這是個很重要的概念喔！ 這也是為什麼當你的記憶體不足時，系統的效能就很糟糕！
  • 常見到的兩種主要 CPU 架構， 分別是：精簡指令集 (RISC) 與複雜指令集 (CISC) 系統。
  • 微指令集較為精簡，每個指令的執行時間都很短，完成的動作也很單純，指令的執行效能較佳； 但是若要做複雜的事情，就要由多個指令來完成。
  • CISC在微指令集的每個小指令可以執行一些較低階的硬體操作，指令數目多而且複雜， 每條指令的長度並不相同。因為指令執行較為複雜所以每條指令花費的時間較長， 但每條個別指令可以處理的工作較為豐富。
  • 多媒體微指令集：MMX, SSE, SSE2, SSE3, SSE4, AMD-3DNow! 虛擬化微指令集：Intel-VT, AMD-SVM 省電功能：Intel-SpeedStep, AMD-PowerNow! 64/32位元相容技術：AMD-AMD64, Intel-EM64T
  • 若光以效能來說，目前的個人電腦效能已經夠快了，甚至已經比工作站等級以上的電腦運算速度還要快！ 但是工作站電腦強調的是穩定不當機，並且運算過程要完全正確，因此工作站以上等級的電腦在設計時的考量與個人電腦並不相同啦
  • 1 Byte = 8 bits
  • 檔案容量使用的是二進位的方式，所以 1 GBytes 的檔案大小實際上為：1024x1024x1024 Bytes 這麼大！ 速度單位則常使用十進位，例如 1GHz 就是 1000x1000x1000 Hz 的意思。
  • CPU的運算速度常使用 MHz 或者是 GHz 之類的單位，這個 Hz 其實就是秒分之一
  • 在網路傳輸方面，由於網路使用的是 bit 為單位，因此網路常使用的單位為 Mbps 是 Mbits per second，亦即是每秒多少 Mbit
  • (1)北橋：負責連結速度較快的CPU、主記憶體與顯示卡界面等元件
  • (2)南橋：負責連接速度較慢的裝置介面， 包括硬碟、USB、網路卡等等
  • CPU內部含有微指令集，不同的微指令集會導致CPU工作效率的優劣
  • 時脈就是CPU每秒鐘可以進行的工作次數。 所以時脈越高表示這顆CPU單位時間內可以作更多的事情。
  • 早期的 CPU 架構主要透過北橋來連結系統最重要的 CPU、主記憶體與顯示卡裝置。因為所有的設備都得掉透過北橋來連結，因此每個設備的工作頻率應該要相同。
  • 前端匯流排 (FSB)
  • 外頻指的是CPU與外部元件進行資料傳輸時的速度
  • 倍頻則是 CPU 內部用來加速工作效能的一個倍數
  • 新的 CPU 設計中， 已經將記憶體控制器整合到 CPU 內部，而連結 CPU 與記憶體、顯示卡的控制器的設計，在Intel部份使用 QPI (Quick Path Interconnect) 與 DMI 技術，而 AMD 部份則使用 Hyper Transport 了，這些技術都可以讓 CPU 直接與主記憶體、顯示卡等設備分別進行溝通，而不需要透過外部的連結晶片了。
  • 如何知道主記憶體能提供的資料量呢？此時還是得要藉由 CPU 內的記憶體控制晶片與主記憶體間的傳輸速度『前端匯流排速度(Front Side Bus, FSB)
  • 主記憶體也是有其工作的時脈，這個時脈限制還是來自於 CPU 內的記憶體控制器所決定的。
  • CPU每次能夠處理的資料量稱為字組大小(word size)， 字組大小依據CPU的設計而有32位元與64位元。我們現在所稱的電腦是32或64位元主要是依據這個 CPU解析的字組大小而來的
  • 早期的32位元CPU中，因為CPU每次能夠解析的資料量有限， 因此由主記憶體傳來的資料量就有所限制了。這也導致32位元的CPU最多只能支援最大到4GBytes的記憶體。
  • 在每一個 CPU 內部將重要的暫存器 (register) 分成兩群， 而讓程序分別使用這兩群暫存器。
  • 可以有兩個程序『同時競爭 CPU 的運算單元』，而非透過作業系統的多工切換！
  • 大多發現 HT 雖然可以提昇效能，不過，有些情況下卻可能導致效能降低喔！因為，實際上明明就僅有一個運算單元
  • 個人電腦的主記憶體主要元件為動態隨機存取記憶體(Dynamic Random Access Memory, DRAM)， 隨機存取記憶體只有在通電時才能記錄與使用，斷電後資料就消失了。因此我們也稱這種RAM為揮發性記憶體。
  • 要啟用雙通道的功能你必須要安插兩支(或四支)主記憶體，這兩支記憶體最好連型號都一模一樣比較好， 這是因為啟動雙通道記憶體功能時，資料是同步寫入/讀出這一對主記憶體中，如此才能夠提升整體的頻寬啊！
  • 第二層快取(L2 cache)整合到CPU內部，因此這個L2記憶體的速度必須要CPU時脈相同。 使用DRAM是無法達到這個時脈速度的，此時就需要靜態隨機存取記憶體(Static Random Access Memory, SRAM)的幫忙了。
  • BIOS(Basic Input Output System)是一套程式，這套程式是寫死到主機板上面的一個記憶體晶片中， 這個記憶體晶片在沒有通電時也能夠將資料記錄下來，那就是唯讀記憶體(Read Only Memory, ROM)。
  • BIOS對於個人電腦來說是非常重要的， 因為他是系統在開機的時候首先會去讀取的一個小程式
  • 由於磁碟盤是圓的，並且透過機器手臂去讀寫資料，磁碟盤要轉動才能夠讓機器手臂讀寫。因此，通常資料寫入當然就是以圓圈轉圈的方式讀寫囉！ 所以，當初設計就是在類似磁碟盤同心圓上面切出一個一個的小區塊，這些小區塊整合成一個圓形，讓機器手臂上的讀寫頭去存取。 這個小區塊就是磁碟的最小物理儲存單位，稱之為磁區 (sector)，那同一個同心圓的磁區組合成的圓就是所謂的磁軌(track)。 由於磁碟裡面可能會有多個磁碟盤，因此在所有磁碟盤上面的同一個磁軌可以組合成所謂的磁柱 (cylinder)。
  • 原本硬碟的磁區都是設計成 512byte 的容量，但因為近期以來硬碟的容量越來越大，為了減少資料量的拆解，所以新的高容量硬碟已經有 4Kbyte 的磁區設計
  • 拿快閃記憶體去製作成高容量的設備，這些設備的連接界面也是透過 SATA 或 SAS，而且外型還做的跟傳統磁碟一樣
  • 固態硬碟最大的好處是，它沒有馬達不需要轉動，而是透過記憶體直接讀寫的特性，因此除了沒資料延遲且快速之外，還很省電
  • 硬碟主要是利用主軸馬達轉動磁碟盤來存取，因此轉速的快慢會影響到效能
  • 使用作業系統的正常關機方式，才能夠有比較好的硬碟保養啊！因為他會讓硬碟的機械手臂歸回原位啊！
  • I/O位址有點類似每個裝置的門牌號碼，每個裝置都有他自己的位址，一般來說，不能有兩個裝置使用同一個I/O位址， 否則系統就會不曉得該如何運作這兩個裝置了。
  • IRQ就可以想成是各個門牌連接到郵件中心(CPU)的專門路徑囉！ 各裝置可以透過IRQ中斷通道來告知CPU該裝置的工作情況，以方便CPU進行工作分配的任務。
  • BIOS為寫入到主機板上某一塊 flash 或 EEPROM 的程式，他可以在開機的時候執行，以載入CMOS當中的參數， 並嘗試呼叫儲存裝置中的開機程式，進一步進入作業系統當中。
  • 電腦都只有記錄0/1而已，甚至記錄的資料都是使用byte/bit等單位來記錄的
  • 常用的英文編碼表為ASCII系統，這個編碼系統中， 每個符號(英文、數字或符號等)都會佔用1bytes的記錄， 因此總共會有28=256種變化
  • 中文字當中的編碼系統早期最常用的就是big5這個編碼表了。 每個中文字會佔用2bytes，理論上最多可以有216=65536，亦即最多可達6萬多個中文字。
  • 國際組織ISO/IEC跳出來制訂了所謂的Unicode編碼系統， 我們常常稱呼的UTF8或萬國碼的編碼
  • CPU其實是具有微指令集的。因此，我們需要CPU幫忙工作時，就得要參考微指令集的內容， 然後撰寫讓CPU讀的懂的指令碼給CPU執行，這樣就能夠讓CPU運作了。
  • 編譯器』來將這些人類能夠寫的程式語言轉譯成為機器能看懂得機器碼
  • 當你需要將運作的資料寫入記憶體中，你就得要自行分配一個記憶體區塊出來讓自己的資料能夠填上去， 所以你還得要瞭解到記憶體的位址是如何定位的，啊！眼淚還是不知不覺的流了下來... 怎麼寫程式這麼麻煩啊！
  • 作業系統(Operating System, OS)其實也是一組程式， 這組程式的重點在於管理電腦的所有活動以及驅動系統中的所有硬體。
  • 作業系統的功能就是讓CPU可以開始判斷邏輯與運算數值、 讓主記憶體可以開始載入/讀出資料與程式碼、讓硬碟可以開始被存取、讓網路卡可以開始傳輸資料、 讓所有周邊可以開始運轉等等。
  • 只有核心有提供的功能，你的電腦系統才能幫你完成！舉例來說，你的核心並不支援TCP/IP的網路協定， 那麼無論你購買了什麼樣的網卡，這個核心都無法提供網路能力的！
  • 核心程式所放置到記憶體當中的區塊是受保護的！ 並且開機後就一直常駐在記憶體當中。
  • 作業系統通常會提供一整組的開發介面給工程師來開發軟體！ 工程師只要遵守該開發介面那就很容易開發軟體了！
  • 系統呼叫介面(System call interface)
  • 程序管理(Process control)
  • 記憶體管理(Memory management)
  • 檔案系統管理(Filesystem management)
  • 通常核心會提供虛擬記憶體的功能，當記憶體不足時可以提供記憶體置換(swap)的功能
  • 裝置的驅動(Device drivers)
  • 『可載入模組』功能，可以將驅動程式編輯成模組，就不需要重新的編譯核心
  • 驅動程式可以說是作業系統裡面相當重要的一環
  • 作業系統通常會提供一個開發介面給硬體開發商， 讓他們可以根據這個介面設計可以驅動他們硬體的『驅動程式』，如此一來，只要使用者安裝驅動程式後， 自然就可以在他們的作業系統上面驅動這塊顯示卡了。
  • 張 旭 on 22 Jun 21
     
    "但因為 CPU 的運算速度比其他的設備都要來的快，又為了要滿足 FSB 的頻率，因此廠商就在 CPU 內部再進行加速， 於是就有所謂的外頻與倍頻了。"
張 旭

Connection and Privileges Needed - 0 views

www.percona.com/...privileges.html

mysql database backup percona xtradb

shared by 張 旭 on 02 Dec 19 - No Cached
  • Percona XtraBackup needs to be able to connect to the database server and perform operations on the server and the datadir when creating a backup, when preparing in some scenarios and when restoring it.
  • When xtrabackup is used, there are two actors involved: the user invoking the program - a system user - and the user performing action in the database server - a database user.
  • these are different users in different places, even though they may have the same username.
  • ...1 more annotation...
  • Once connected to the server, in order to perform a backup you will need READ and EXECUTE permissions at a filesystem level in the server’s datadir.
  • 張 旭 on 02 Dec 19
     
    "Percona XtraBackup needs to be able to connect to the database server and perform operations on the server and the datadir when creating a backup, when preparing in some scenarios and when restoring it. "
張 旭

Memory inside Linux containers | Fabio Kung - 0 views

fabiokung.com/...memory-inside-linux-containers

linux docker system process

shared by 張 旭 on 05 Dec 19 - No Cached
  • /sys/fs/cgroup/ is the recommended location for cgroup hierarchies, but it is not a standard.
  • most container specific metrics are available at the cgroup filesystem via /path/to/cgroup/memory.stat, /path/to/cgroup/memory.usage_in_bytes, /path/to/cgroup/memory.limit_in_bytes and others.
  • cat /sys/fs/cgroup/memory/memory.stat
  • ...3 more annotations...
  • /sys/fs/cgroup is just an umbrella for all cgroup hierarchies, there is no recommendation or standard for my own cgroup location.
  • an userspace library that processes can use to query their memory usage and available memory.
  • we might need to encourage people to stop using those tools inside containers.
張 旭

Container Runtimes | Kubernetes - 0 views

kubernetes.io/...container-runtimes

kubernetes container docker devops

shared by 張 旭 on 25 Jan 23 - No Cached
  • Kubernetes releases before v1.24 included a direct integration with Docker Engine, using a component named dockershim. That special direct integration is no longer part of Kubernetes
  • You need to install a container runtime into each node in the cluster so that Pods can run there.
  • Kubernetes 1.26 requires that you use a runtime that conforms with the Container Runtime Interface (CRI).
  • ...9 more annotations...
  • On Linux, control groups are used to constrain resources that are allocated to processes.
  • Both kubelet and the underlying container runtime need to interface with control groups to enforce resource management for pods and containers and set resources such as cpu/memory requests and limits.
  • When the cgroupfs driver is used, the kubelet and the container runtime directly interface with the cgroup filesystem to configure cgroups.
  • The cgroupfs driver is not recommended when systemd is the init system
  • When systemd is chosen as the init system for a Linux distribution, the init process generates and consumes a root control group (cgroup) and acts as a cgroup manager.
  • Two cgroup managers result in two views of the available and in-use resources in the system.
  • Changing the cgroup driver of a Node that has joined a cluster is a sensitive operation. If the kubelet has created Pods using the semantics of one cgroup driver, changing the container runtime to another cgroup driver can cause errors when trying to re-create the Pod sandbox for such existing Pods. Restarting the kubelet may not solve such errors.
  • The approach to mitigate this instability is to use systemd as the cgroup driver for the kubelet and the container runtime when systemd is the selected init system.
  • Kubernetes 1.26 defaults to using v1 of the CRI API. If a container runtime does not support the v1 API, the kubelet falls back to using the (deprecated) v1alpha2 API instead.
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