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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

Ask HN: What are the best practises for using SSH keys? | Hacker News - 0 views

news.ycombinator.com/item

security ssh key server

shared by 張 旭 on 14 Oct 16 - No Cached
  • Make sure you use full disk encryption and never stand up from your machine without locking it, and make sure you keep your local machine patched.
  • I'm more focused on just stealing your keys from you regardless of length
  • attacks that aren't after your keys specifically, e.g. your home directory gets stolen.
  • ...19 more annotations...
  • ED25519 is more vulnerable to quantum computation than is RSA
  • best practice to be using a hardware token
  • to use a yubikey via gpg: with this method you use your gpg subkey as an ssh key
  • sit down and spend an hour thinking about your backup and recovery strategy first
  • never share a private keys between physical devices
  • allows you to revoke a single credential if you lose (control over) that device
  • If a private key ever turns up on the wrong machine, you *know* the key and both source and destination machines have been compromised.
  • centralized management of authentication/authorization
  • I have setup a VPS, disabled passwords, and setup a key with a passphrase to gain access. At this point my greatest worry is losing this private key, as that means I can't access the server.What is a reasonable way to backup my private key?
  • a mountable disk image that's encrypted
  • a system that can update/rotate your keys across all of your servers on the fly in case one is compromised or assumed to be compromised.
  • different keys for different purposes per client device
  • fall back to password plus OTP
  • relying completely on the security of your disk, against either physical or cyber.
  • It is better to use a different passphrase for each key but it is also less convenient unless you're using a password manager (personally, I'm using KeePass)
  • - RSA is pretty standard, and generally speaking is fairly secure for key lengths >=2048. RSA-2048 is the default for ssh-keygen, and is compatible with just about everything.
  • public-key authentication has somewhat unexpected side effect of preventing MITM per this security consulting firm
  • Disable passwords and only allow keys even for root with PermitRootLogin without-password
  • You should definitely use a different passphrase for keys stored on separate computers,
  • 張 旭 on 14 Oct 16
     
    "Make sure you use full disk encryption and never stand up from your machine without locking it, and make sure you keep your local machine patched"
張 旭

Backends: Configuration - Terraform by HashiCorp - 0 views

www.terraform.io/...config.html

terraform devops system

shared by 張 旭 on 07 Apr 19 - No Cached
  • merged configuration is stored on disk in the .terraform directory, which should be ignored from version control.
  • When using partial configuration, Terraform requires at a minimum that an empty backend configuration is specified in one of the root Terraform configuration files, to specify the backend type.
  • 張 旭 on 07 Apr 19
     
    "merged configuration is stored on disk in the .terraform directory, which should be ignored from version control."
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

What are Docker : images? - Project Atomic - 0 views

www.projectatomic.io/...at-are-docker-none-none-images

docker system

shared by 張 旭 on 18 Sep 18 - No Cached
  • Now we understand what these <none>:<none> images stand for. They stand for intermediate images and can be seen using docker images -a
  • They don’t result into a disk space problem but it is definitely a screen real estate problem
  • dangling images
  • ...7 more annotations...
  • Another style of <none>:<none> images are the dangling images which can cause disk space problems.
  • In programming languages like Java or Golang a dangling block of memory is a block that is not referenced by any piece of code.
  • a dangling file system layer in Docker is something that is unused and is not being referenced by any images.
  • intermediate images
  • do docker images and see <none>:<none> images in the list, these are dangling images and needs to be pruned.
  • These dangling images are produced as a result of docker build or pull command.
  • docker rmi $(docker images -f "dangling=true" -q)
張 旭

http - nginx upload client_max_body_size issue - Stack Overflow - 0 views

stackoverflow.com/...oad-client-max-body-size-issue

nginx upload file http server

shared by 張 旭 on 26 Sep 16 - No Cached
  • nginx "fails fast" when the client informs it that it's going to send a body larger than the client_max_body_size by sending a 413 response and closing the connection.
  • Because nginx closes the connection, the client sends data to the closed socket, causing a TCP RST.
  • Most clients don't read responses until the entire request body is sent.
  • ...2 more annotations...
  • Client body and buffers are key because nginx must buffer incoming data.
  • The clean setting frees up memory and consumption limits by instructing nginx to store incoming buffer in a file and then clean this file later from disk by deleting it.
張 旭

How to write excellent Dockerfiles - 0 views

rock-it.pl/to-write-excellent-dockerfiles

docker server system

shared by 張 旭 on 10 Apr 17 - No Cached
  • minimize image size, build time and number of layers.
  • maximize build cache usage
  • Container should do one thing
    • 張 旭
      張 旭 on 10 Apr 17
       
      這個有待商榷，在 baseimage 的 blog 介紹中有詳細的討論。
  • ...25 more annotations...
  • Use COPY and RUN commands in proper order
  • Merge multiple RUN commands into one
  • alpine versions should be enough
  • Use exec inside entrypoint script
  • Prefer COPY over ADD
  • Specify default environment variables, ports and volumes inside Dockerfile
  • problems with zombie processes
  • prepare separate Docker image for each component, and use Docker Compose to easily start multiple containers at the same time
  • Layers are cached and reused
  • Layers are immutable
  • They both makes you cry
  • rely on our base image updates
  • make a cleanup
  • alpine is a very tiny linux distribution, just about 4 MB in size.
  • Your disk will love you :)
  • WORKDIR command changes default directory, where we run our RUN / CMD / ENTRYPOINT commands.
  • CMD is a default command run after creating container without other command specified.
  • put your command inside array
  • entrypoint adds complexity
  • Entrypoint is a script, that will be run instead of command, and receive command as arguments
  • Without it, we would not be able to stop our application grecefully (SIGTERM is swallowed by bash script).
  • Use "exec" inside entrypoint script
  • ADD has some logic for downloading remote files and extracting archives.
  • stick with COPY.
  • ADD
    • 張 旭
      張 旭 on 10 Apr 17
       
      不是說要用 COPY 嗎？
張 旭

Home · sysown/proxysql Wiki - 0 views

github.com/wiki

mysql database cluster mariadb proxy

shared by 張 旭 on 19 Nov 18 - No Cached
  • bear in mind that the best way to configure ProxySQL is through its admin interface.
  • llow you to control the list of the backend servers, how traffic is routed to them, and other important settings (such as caching, access control, etc)
  • Once you've made modifications to the in-memory data structure, you must load the new configuration to the runtime, or persist the new settings to disk
  • ...4 more annotations...
  • mysql_variables: contains global variables that control the functionality for handling the incoming MySQL traffic.
  • mysql_users: contains rows for the mysql_users table from the admin interface. Basically, these define the users which can connect to the proxy, and the users with which the proxy can connect to the backend servers.
  • mysql_servers: contains rows for the mysql_servers table from the admin interface. Basically, these define the backend servers towards which the incoming MySQL traffic is routed.
  • mysql_query_rules: contains rows for the mysql_query_rules table from the admin interface. Basically, these define the rules used to classify and route the incoming MySQL traffic, according to various criteria (patterns matched, user used to run the query, etc.).
張 旭

Practical persistent cloud storage for Docker in AWS using RexRay - pt 4 - 0 views

blog.vizuri.com/ocker-in-aws-using-rexray-pt-4

docker volume disk aws storage

shared by 張 旭 on 14 Sep 18 - No Cached
  • Docker volumes can then be created and managed via the plugin, as requests are passed by Docker, and then orchestrated by the local server.
  • volumes are usually protected from deletion via a reference count.
  • Using the plugin means that the reference count is kept at the node level, so the plugin is only aware of the containers on a single node.
  • ...3 more annotations...
  • The S3FS plugin as of version 0.9.2 cannot delete an S3 bucket unless the bucket is empty, and has never been used (just created) as a Docker volume.
  • Starting with Docker 1.13 a new plugin system was introduced in which the plugin runs inside of a container.
  • Even though the plugin is a container image, you cannot start it using either docker image pull or docker container run; you need to use the docker plugin set of sub‑commands.
  • 張 旭 on 14 Sep 18
     
    "Docker volumes can then be created and managed via the plugin, as requests are passed by Docker, and then orchestrated by the local server."
張 旭

The Asset Pipeline - Ruby on Rails Guides - 0 views

guides.rubyonrails.org/asset_pipeline.html

rails image javascript font CSS file

shared by 張 旭 on 29 Dec 14 - No Cached
  • provides a framework to concatenate and minify or compress JavaScript and CSS assets
  • adds the ability to write these assets in other languages and pre-processors such as CoffeeScript, Sass and ERB
  • invalidate the cache by altering this fingerprint
  • ...80 more annotations...
  • Rails 4 automatically adds the sass-rails, coffee-rails and uglifier gems to your Gemfile
  • reduce the number of requests that a browser makes to render a web page
  • Starting with version 3.1, Rails defaults to concatenating all JavaScript files into one master .js file and all CSS files into one master .css file
  • In production, Rails inserts an MD5 fingerprint into each filename so that the file is cached by the web browser
  • The technique sprockets uses for fingerprinting is to insert a hash of the content into the name, usually at the end.
  • asset minification or compression
  • The sass-rails gem is automatically used for CSS compression if included in Gemfile and no config.assets.css_compressor option is set.
  • Supported languages include Sass for CSS, CoffeeScript for JavaScript, and ERB for both by default.
  • When a filename is unique and based on its content, HTTP headers can be set to encourage caches everywhere (whether at CDNs, at ISPs, in networking equipment, or in web browsers) to keep their own copy of the content
  • asset pipeline is technically no longer a core feature of Rails 4
  • Rails uses for fingerprinting is to insert a hash of the content into the name, usually at the end
  • With the asset pipeline, the preferred location for these assets is now the app/assets directory.
  • Fingerprinting is enabled by default for production and disabled for all other environments
  • The files in app/assets are never served directly in production.
  • Paths are traversed in the order that they occur in the search path
  • You should use app/assets for files that must undergo some pre-processing before they are served.
  • By default .coffee and .scss files will not be precompiled on their own
  • app/assets is for assets that are owned by the application, such as custom images, JavaScript files or stylesheets.
  • lib/assets is for your own libraries' code that doesn't really fit into the scope of the application or those libraries which are shared across applications.
  • vendor/assets is for assets that are owned by outside entities, such as code for JavaScript plugins and CSS frameworks.
  • Any path under assets/* will be searched
  • By default these files will be ready to use by your application immediately using the require_tree directive.
  • By default, this means the files in app/assets take precedence, and will mask corresponding paths in lib and vendor
  • Sprockets uses files named index (with the relevant extensions) for a special purpose
  • Rails.application.config.assets.paths
  • causes turbolinks to check if an asset has been updated and if so loads it into the page
  • if you add an erb extension to a CSS asset (for example, application.css.erb), then helpers like asset_path are available in your CSS rules
  • If you add an erb extension to a JavaScript asset, making it something such as application.js.erb, then you can use the asset_path helper in your JavaScript code
  • The asset pipeline automatically evaluates ERB
  • data URI — a method of embedding the image data directly into the CSS file — you can use the asset_data_uri helper.
  • Sprockets will also look through the paths specified in config.assets.paths, which includes the standard application paths and any paths added by Rails engines.
  • image_tag
  • the closing tag cannot be of the style -%>
  • asset_data_uri
  • app/assets/javascripts/application.js
  • sass-rails provides -url and -path helpers (hyphenated in Sass, underscored in Ruby) for the following asset classes: image, font, video, audio, JavaScript and stylesheet.
  • Rails.application.config.assets.compress
  • In JavaScript files, the directives begin with //=
  • The require_tree directive tells Sprockets to recursively include all JavaScript files in the specified directory into the output.
  • manifest files contain directives — instructions that tell Sprockets which files to require in order to build a single CSS or JavaScript file.
  • You should not rely on any particular order among those
  • Sprockets uses manifest files to determine which assets to include and serve.
  • the family of require directives prevents files from being included twice in the output
  • which files to require in order to build a single CSS or JavaScript file
  • Directives are processed top to bottom, but the order in which files are included by require_tree is unspecified.
  • In JavaScript files, Sprockets directives begin with //=
  • If require_self is called more than once, only the last call is respected.
  • require directive is used to tell Sprockets the files you wish to require.
  • You need not supply the extensions explicitly. Sprockets assumes you are requiring a .js file when done from within a .js file
  • paths must be specified relative to the manifest file
  • require_directory
  • Rails 4 creates both app/assets/javascripts/application.js and app/assets/stylesheets/application.css regardless of whether the --skip-sprockets option is used when creating a new rails application.
  • The file extensions used on an asset determine what preprocessing is applied.
  • app/assets/stylesheets/application.css
  • Additional layers of preprocessing can be requested by adding other extensions, where each extension is processed in a right-to-left manner
  • require_self
  • use the Sass @import rule instead of these Sprockets directives.
  • Keep in mind that the order of these preprocessors is important
  • In development mode, assets are served as separate files in the order they are specified in the manifest file.
  • when these files are requested they are processed by the processors provided by the coffee-script and sass gems and then sent back to the browser as JavaScript and CSS respectively.
  • css.scss.erb
  • js.coffee.erb
  • Keep in mind the order of these preprocessors is important.
  • By default Rails assumes that assets have been precompiled and will be served as static assets by your web server
  • with the Asset Pipeline the :cache and :concat options aren't used anymore
  • Assets are compiled and cached on the first request after the server is started
  • RAILS_ENV=production bundle exec rake assets:precompile
  • Debug mode can also be enabled in Rails helper methods
  • If you set config.assets.initialize_on_precompile to false, be sure to test rake assets:precompile locally before deploying
  • By default Rails assumes assets have been precompiled and will be served as static assets by your web server.
  • a rake task to compile the asset manifests and other files in the pipeline
  • RAILS_ENV=production bin/rake assets:precompile
  • a recipe to handle this in deployment
  • links the folder specified in config.assets.prefix to shared/assets
  • config/initializers/assets.rb
  • The initialize_on_precompile change tells the precompile task to run without invoking Rails
  • The X-Sendfile header is a directive to the web server to ignore the response from the application, and instead serve a specified file from disk
  • the jquery-rails gem which comes with Rails as the standard JavaScript library gem.
  • Possible options for JavaScript compression are :closure, :uglifier and :yui
  • concatenate assets
張 旭

Secrets - Kubernetes - 0 views

kubernetes.io/...secret

kubernetes secret password security

shared by 張 旭 on 05 Jul 19 - No Cached
  • Putting this information in a secret is safer and more flexible than putting it verbatim in a PodThe smallest and simplest Kubernetes object. A Pod represents a set of running containers on your cluster. definition or in a container imageStored instance of a container that holds a set of software needed to run an application. .
  • A Secret is an object that contains a small amount of sensitive data such as a password, a token, or a key.
  • Users can create secrets, and the system also creates some secrets.
  • ...63 more annotations...
  • To use a secret, a pod needs to reference the secret.
  • A secret can be used with a pod in two ways: as files in a volumeA directory containing data, accessible to the containers in a pod. mounted on one or more of its containers, or used by kubelet when pulling images for the pod.
  • --from-file
  • You can also create a Secret in a file first, in json or yaml format, and then create that object.
  • The Secret contains two maps: data and stringData.
  • The data field is used to store arbitrary data, encoded using base64.
  • Kubernetes automatically creates secrets which contain credentials for accessing the API and it automatically modifies your pods to use this type of secret.
  • kubectl get and kubectl describe avoid showing the contents of a secret by default.
  • stringData field is provided for convenience, and allows you to provide secret data as unencoded strings.
  • where you are deploying an application that uses a Secret to store a configuration file, and you want to populate parts of that configuration file during your deployment process.
  • a field is specified in both data and stringData, the value from stringData is used.
  • The keys of data and stringData must consist of alphanumeric characters, ‘-’, ‘_’ or ‘.’.
  • Newlines are not valid within these strings and must be omitted.
  • When using the base64 utility on Darwin/macOS users should avoid using the -b option to split long lines.
  • create a Secret from generators and then apply it to create the object on the Apiserver.
  • The generated Secrets name has a suffix appended by hashing the contents.
  • base64 --decode
  • Secrets can be mounted as data volumes or be exposed as environment variablesContainer environment variables are name=value pairs that provide useful information into containers running in a Pod. to be used by a container in a pod.
  • Multiple pods can reference the same secret.
  • Each key in the secret data map becomes the filename under mountPath
  • each container needs its own volumeMounts block, but only one .spec.volumes is needed per secret
  • use .spec.volumes[].secret.items field to change target path of each key:
  • If .spec.volumes[].secret.items is used, only keys specified in items are projected. To consume all keys from the secret, all of them must be listed in the items field.
  • You can also specify the permission mode bits files part of a secret will have. If you don’t specify any, 0644 is used by default.
  • JSON spec doesn’t support octal notation, so use the value 256 for 0400 permissions.
  • Inside the container that mounts a secret volume, the secret keys appear as files and the secret values are base-64 decoded and stored inside these files.
  • Mounted Secrets are updated automatically
  • Kubelet is checking whether the mounted secret is fresh on every periodic sync.
  • cache propagation delay depends on the chosen cache type
  • A container using a Secret as a subPath volume mount will not receive Secret updates.
  • Multiple pods can reference the same secret.
  • env: - name: SECRET_USERNAME valueFrom: secretKeyRef: name: mysecret key: username
  • Inside a container that consumes a secret in an environment variables, the secret keys appear as normal environment variables containing the base-64 decoded values of the secret data.
  • An imagePullSecret is a way to pass a secret that contains a Docker (or other) image registry password to the Kubelet so it can pull a private image on behalf of your Pod.
  • a secret needs to be created before any pods that depend on it.
  • Secret API objects reside in a namespaceAn abstraction used by Kubernetes to support multiple virtual clusters on the same physical cluster. . They can only be referenced by pods in that same namespace.
  • Individual secrets are limited to 1MiB in size.
  • Kubelet only supports use of secrets for Pods it gets from the API server.
  • Secrets must be created before they are consumed in pods as environment variables unless they are marked as optional.
  • References to Secrets that do not exist will prevent the pod from starting.
  • References via secretKeyRef to keys that do not exist in a named Secret will prevent the pod from starting.
  • Once a pod is scheduled, the kubelet will try to fetch the secret value.
  • Think carefully before sending your own ssh keys: other users of the cluster may have access to the secret.
  • volumes: - name: secret-volume secret: secretName: ssh-key-secret
  • Special characters such as $, \*, and ! require escaping. If the password you are using has special characters, you need to escape them using the \\ character.
  • You do not need to escape special characters in passwords from files
  • make that key begin with a dot
  • Dotfiles in secret volume
  • .secret-file
  • a frontend container which handles user interaction and business logic, but which cannot see the private key;
  • a signer container that can see the private key, and responds to simple signing requests from the frontend
  • When deploying applications that interact with the secrets API, access should be limited using authorization policies such as RBAC
  • watch and list requests for secrets within a namespace are extremely powerful capabilities and should be avoided
  • watch and list all secrets in a cluster should be reserved for only the most privileged, system-level components.
  • additional precautions with secret objects, such as avoiding writing them to disk where possible.
  • A secret is only sent to a node if a pod on that node requires it
  • only the secrets that a pod requests are potentially visible within its containers
  • each container in a pod has to request the secret volume in its volumeMounts for it to be visible within the container.
  • In the API server secret data is stored in etcdConsistent and highly-available key value store used as Kubernetes’ backing store for all cluster data.
  • limit access to etcd to admin users
  • Base64 encoding is not an encryption method and is considered the same as plain text.
  • A user who can create a pod that uses a secret can also see the value of that secret.
  • anyone with root on any node can read any secret from the apiserver, by impersonating the kubelet.
張 旭

ProxySQL Experimental Feature: Native ProxySQL Clustering - Percona Database Performanc... - 0 views

www.percona.com/...ntal-feature-native-clustering

mysql proxysql cluster HA database

shared by 張 旭 on 07 Aug 19 - No Cached
  • several ProxySQL instances to communicate with and share configuration updates with each other.
  • 4 tables where you can make changes and propagate the configuration
  • When you make a change like INSERT/DELETE/UPDATE on any of these tables, after running the command LOAD … TO RUNTIME , ProxySQL creates a new checksum of the table’s data and increments the version number in the table runtime_checksums_values
  • ...2 more annotations...
  • all nodes are monitoring and communicating with all the other ProxySQL nodes. When another node detects a change in the checksum and version (both at the same time), each node will get a copy of the table that was modified, make the same changes locally, and apply the new config to RUNTIME to refresh the new config, make it visible to the applications connected and automatically save it to DISK for persistence.
  • a “synchronous cluster” so any changes to these 4 tables on any ProxySQL server will be replicated to all other ProxySQL nodes.
張 旭

thoughtbot/paperclip: Easy file attachment management for ActiveRecord - 0 views

github.com/paperclip

rails file upload

shared by 張 旭 on 04 Dec 17 - No Cached
  • Paperclip is intended as an easy file attachment library for ActiveRecord.
  • treat files as much like other attributes as possible
  • they aren't saved to their final locations on disk, nor are they deleted if set to nil, until ActiveRecord::Base#save is called.
張 旭

MongoDB Performance Tuning: Everything You Need to Know - Stackify - 0 views

stackify.com/mongodb-performance-tuning

database mongodb

shared by 張 旭 on 15 Apr 21 - No Cached
  • db.serverStatus().globalLock
  • db.serverStatus().locks
  • globalLock.currentQueue.total: This number can indicate a possible concurrency issue if it’s consistently high. This can happen if a lot of requests are waiting for a lock to be released.
  • ...35 more annotations...
  • globalLock.totalTime: If this is higher than the total database uptime, the database has been in a lock state for too long.
  • Unlike relational databases such as MySQL or PostgreSQL, MongoDB uses JSON-like documents for storing data.
  • Databases operate in an environment that consists of numerous reads, writes, and updates.
  • When a lock occurs, no other operation can read or modify the data until the operation that initiated the lock is finished.
  • locks.deadlockCount: Number of times the lock acquisitions have encountered deadlocks
  • Is the database frequently locking from queries? This might indicate issues with the schema design, query structure, or system architecture.
  • For version 3.2 on, WiredTiger is the default.
  • MMAPv1 locks whole collections, not individual documents.
  • WiredTiger performs locking at the document level.
  • When the MMAPv1 storage engine is in use, MongoDB will use memory-mapped files to store data.
  • All available memory will be allocated for this usage if the data set is large enough.
  • db.serverStatus().mem
  • mem.resident: Roughly equivalent to the amount of RAM in megabytes that the database process uses
  • If mem.resident exceeds the value of system memory and there’s a large amount of unmapped data on disk, we’ve most likely exceeded system capacity.
  • If the value of mem.mapped is greater than the amount of system memory, some operations will experience page faults.
  • The WiredTiger storage engine is a significant improvement over MMAPv1 in performance and concurrency.
  • By default, MongoDB will reserve 50 percent of the available memory for the WiredTiger data cache.
  • wiredTiger.cache.bytes currently in the cache – This is the size of the data currently in the cache.
  • wiredTiger.cache.tracked dirty bytes in the cache – This is the size of the dirty data in the cache.
  • we can look at the wiredTiger.cache.bytes read into cache value for read-heavy applications. If this value is consistently high, increasing the cache size may improve overall read performance.
  • check whether the application is read-heavy. If it is, increase the size of the replica set and distribute the read operations to secondary members of the set.
  • write-heavy, use sharding within a sharded cluster to distribute the load.
  • Replication is the propagation of data from one node to another
  • Replication sets handle this replication.
  • Sometimes, data isn’t replicated as quickly as we’d like.
  • a particularly thorny problem if the lag between a primary and secondary node is high and the secondary becomes the primary
  • use the db.printSlaveReplicationInfo() or the rs.printSlaveReplicationInfo() command to see the status of a replica set from the perspective of the secondary member of the set.
  • shows how far behind the secondary members are from the primary. This number should be as low as possible.
  • monitor this metric closely.
  • watch for any spikes in replication delay.
  • Always investigate these issues to understand the reasons for the lag.
  • One replica set is primary. All others are secondary.
  • it’s not normal for nodes to change back and forth between primary and secondary.
  • use the profiler to gain a deeper understanding of the database’s behavior.
  • Enabling the profiler can affect system performance, due to the additional activity.
  • 張 旭 on 15 Apr 21
     
    "globalLock.currentQueue.total: This number can indicate a possible concurrency issue if it's consistently high. This can happen if a lot of requests are waiting for a lock to be released."
張 旭

Logging Architecture | Kubernetes - 0 views

kubernetes.io/...logging

kubernetes log

shared by 張 旭 on 27 May 21 - No Cached
  • Application logs can help you understand what is happening inside your application
  • container engines are designed to support logging.
  • The easiest and most adopted logging method for containerized applications is writing to standard output and standard error streams.
  • ...26 more annotations...
  • In a cluster, logs should have a separate storage and lifecycle independent of nodes, pods, or containers. This concept is called cluster-level logging.
  • Cluster-level logging architectures require a separate backend to store, analyze, and query logs
  • Kubernetes does not provide a native storage solution for log data.
  • use kubectl logs --previous to retrieve logs from a previous instantiation of a container.
  • A container engine handles and redirects any output generated to a containerized application's stdout and stderr streams
  • The Docker JSON logging driver treats each line as a separate message.
  • By default, if a container restarts, the kubelet keeps one terminated container with its logs.
  • An important consideration in node-level logging is implementing log rotation, so that logs don't consume all available storage on the node
  • You can also set up a container runtime to rotate an application's logs automatically.
  • The two kubelet flags container-log-max-size and container-log-max-files can be used to configure the maximum size for each log file and the maximum number of files allowed for each container respectively.
  • The kubelet and container runtime do not run in containers.
  • On machines with systemd, the kubelet and container runtime write to journald. If systemd is not present, the kubelet and container runtime write to .log files in the /var/log directory.
  • System components inside containers always write to the /var/log directory, bypassing the default logging mechanism.
  • Kubernetes does not provide a native solution for cluster-level logging
  • Use a node-level logging agent that runs on every node.
  • implement cluster-level logging by including a node-level logging agent on each node.
  • the logging agent is a container that has access to a directory with log files from all of the application containers on that node.
  • the logging agent must run on every node, it is recommended to run the agent as a DaemonSet
  • Node-level logging creates only one agent per node and doesn't require any changes to the applications running on the node.
  • Containers write stdout and stderr, but with no agreed format. A node-level agent collects these logs and forwards them for aggregation.
  • Each sidecar container prints a log to its own stdout or stderr stream.
  • It is not recommended to write log entries with different formats to the same log stream
  • writing logs to a file and then streaming them to stdout can double disk usage.
  • If you have an application that writes to a single file, it's recommended to set /dev/stdout as the destination
  • it's recommended to use stdout and stderr directly and leave rotation and retention policies to the kubelet.
  • Using a logging agent in a sidecar container can lead to significant resource consumption. Moreover, you won't be able to access those logs using kubectl logs because they are not controlled by the kubelet.
張 旭

Logstash Alternatives: Pros & Cons of 5 Log Shippers [2019] - Sematext - 0 views

sematext.com/...logstash-alternatives

log monitor system logstash fluentd

shared by 張 旭 on 05 Nov 19 - No Cached
  • In this case, Elasticsearch. And because Elasticsearch can be down or struggling, or the network can be down, the shipper would ideally be able to buffer and retry
  • Logstash is typically used for collecting, parsing, and storing logs for future use as part of log management.
  • Logstash’s biggest con or “Achille’s heel” has always been performance and resource consumption (the default heap size is 1GB).
  • ...37 more annotations...
  • This can be a problem for high traffic deployments, when Logstash servers would need to be comparable with the Elasticsearch ones.
  • Filebeat was made to be that lightweight log shipper that pushes to Logstash or Elasticsearch.
  • differences between Logstash and Filebeat are that Logstash has more functionality, while Filebeat takes less resources.
  • Filebeat is just a tiny binary with no dependencies.
  • For example, how aggressive it should be in searching for new files to tail and when to close file handles when a file didn’t get changes for a while.
  • For example, the apache module will point Filebeat to default access.log and error.log paths
  • Filebeat’s scope is very limited,
  • Initially it could only send logs to Logstash and Elasticsearch, but now it can send to Kafka and Redis, and in 5.x it also gains filtering capabilities.
  • Filebeat can parse JSON
  • you can push directly from Filebeat to Elasticsearch, and have Elasticsearch do both parsing and storing.
  • You shouldn’t need a buffer when tailing files because, just as Logstash, Filebeat remembers where it left off
  • For larger deployments, you’d typically use Kafka as a queue instead, because Filebeat can talk to Kafka as well
  • The default syslog daemon on most Linux distros, rsyslog can do so much more than just picking logs from the syslog socket and writing to /var/log/messages.
  • It can tail files, parse them, buffer (on disk and in memory) and ship to a number of destinations, including Elasticsearch.
  • rsyslog is the fastest shipper
  • Its grammar-based parsing module (mmnormalize) works at constant speed no matter the number of rules (we tested this claim).
  • use it as a simple router/shipper, any decent machine will be limited by network bandwidth
  • It’s also one of the lightest parsers you can find, depending on the configured memory buffers.
  • rsyslog requires more work to get the configuration right
  • the main difference between Logstash and rsyslog is that Logstash is easier to use while rsyslog lighter.
  • rsyslog fits well in scenarios where you either need something very light yet capable (an appliance, a small VM, collecting syslog from within a Docker container).
  • rsyslog also works well when you need that ultimate performance.
  • syslog-ng as an alternative to rsyslog (though historically it was actually the other way around).
  • a modular syslog daemon, that can do much more than just syslog
  • Unlike rsyslog, it features a clear, consistent configuration format and has nice documentation.
  • Similarly to rsyslog, you’d probably want to deploy syslog-ng on boxes where resources are tight, yet you do want to perform potentially complex processing.
  • syslog-ng has an easier, more polished feel than rsyslog, but likely not that ultimate performance
  • Fluentd was built on the idea of logging in JSON wherever possible (which is a practice we totally agree with) so that log shippers down the line don’t have to guess which substring is which field of which type.
  • Fluentd plugins are in Ruby and very easy to write.
  • structured data through Fluentd, it’s not made to have the flexibility of other shippers on this list (Filebeat excluded).
  • Fluent Bit, which is to Fluentd similar to how Filebeat is for Logstash.
  • Fluentd is a good fit when you have diverse or exotic sources and destinations for your logs, because of the number of plugins.
  • Splunk isn’t a log shipper, it’s a commercial logging solution
  • Graylog is another complete logging solution, an open-source alternative to Splunk.
  • everything goes through graylog-server, from authentication to queries.
  • Graylog is nice because you have a complete logging solution, but it’s going to be harder to customize than an ELK stack.
  • it depends
張 旭

How to Benchmark Performance of MySQL & MariaDB Using SysBench | Severalnines - 1 views

severalnines.com/...e-mysql-mariadb-using-sysbench

database mysql performance

shared by 張 旭 on 22 Oct 20 - No Cached
  • SysBench is a C binary which uses LUA scripts to execute benchmarks
  • support for parallelization in the LUA scripts, multiple queries can be executed in parallel
  • by default, benchmarks which cover most of the cases - OLTP workloads, read-only or read-write, primary key lookups and primary key updates.
  • ...21 more annotations...
  • SysBench is not a tool which you can use to tune configurations of your MySQL servers (unless you prepared LUA scripts with custom workload or your workload happen to be very similar to the benchmark workloads that SysBench comes with)
  • it is great for is to compare performance of different hardware.
  • Every new server acquired should go through a warm-up period during which you will stress it to pinpoint potential hardware defects
  • by executing OLTP workload which overloads the server, or you can also use dedicated benchmarks for CPU, disk and memory.
  • bulk_insert.lua. This test can be used to benchmark the ability of MySQL to perform multi-row inserts.
  • All oltp_* scripts share a common table structure. First two of them (oltp_delete.lua and oltp_insert.lua) execute single DELETE and INSERT statements.
  • oltp_point_select, oltp_update_index and oltp_update_non_index. These will execute a subset of queries - primary key-based selects, index-based updates and non-index-based updates.
  • you can run different workload patterns using the same benchmark.
  • Warmup helps to identify “regular” throughput by executing benchmark for a predefined time, allowing to warm up the cache, buffer pools etc.
  • By default SysBench will attempt to execute queries as fast as possible. To simulate slower traffic this option may be used. You can define here how many transactions should be executed per second.
  • SysBench gives you ability to generate different types of data distribution.
  • decide if SysBench should use prepared statements (as long as they are available in the given datastore - for MySQL it means PS will be enabled by default) or not.
  • sysbench ./sysbench/src/lua/oltp_read_write.lua  help
  • By default, SysBench will attempt to execute queries in explicit transaction. This way the dataset will stay consistent and not affected: SysBench will, for example, execute INSERT and DELETE on the same row, making sure the data set will not grow (impacting your ability to reproduce results).
  • specify error codes from MySQL which SysBench should ignore (and not kill the connection).
  • the two most popular benchmarks - OLTP read only and OLTP read/write.
  • 1 million rows will result in ~240 MB of data. Ten tables, 1000 000 rows each equals to 2.4GB
  • by default, SysBench looks for ‘sbtest’ schema which has to exist before you prepare the data set. You may have to create it manually.
  • pass ‘--histogram’ argument to SysBench
  • ~48GB of data (20 tables, 10 000 000 rows each).
  • if you don’t understand why the performance was like it was, you may draw incorrect conclusions out of the benchmarks.
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