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張 旭

Deploy a registry server | Docker Documentation - 0 views

docs.docker.com/...deploying

docker system

shared by 張 旭 on 06 Sep 18 - No Cached
  • By default, secrets are mounted into a service at /run/secrets/<secret-name>
  • docker secret create
  • If you use a distributed storage driver, such as Amazon S3, you can use a fully replicated service. Each worker can write to the storage back-end without causing write conflicts.
  • ...10 more annotations...
  • You can access the service on port 443 of any swarm node. Docker sends the requests to the node which is running the service.
  • --publish published=443,target=443
  • The most important aspect is that a load balanced cluster of registries must share the same resources
  • S3 or Azure, they should be accessing the same resource and share an identical configuration.
  • you must make sure you are properly sending the X-Forwarded-Proto, X-Forwarded-For, and Host headers to their “client-side” values. Failure to do so usually makes the registry issue redirects to internal hostnames or downgrading from https to http.
  • A properly secured registry should return 401 when the “/v2/” endpoint is hit without credentials
  • registries should always implement access restrictions.
  • REGISTRY_AUTH=htpasswd
  • REGISTRY_AUTH_HTPASSWD_PATH=/auth/htpasswd
  • The registry also supports delegated authentication which redirects users to a specific trusted token server. This approach is more complicated to set up, and only makes sense if you need to fully configure ACLs and need more control over the registry’s integration into your global authorization and authentication systems.
  • 張 旭 on 06 Sep 18
     
    "You can access the service on port 443 of any swarm node. Docker sends the requests to the node which is running the service. "
張 旭

Best practices for writing Dockerfiles | Docker Documentation - 0 views

docs.docker.com/...dockerfile_best-practices

docker system

shared by 張 旭 on 28 Sep 18 - No Cached
  • building efficient images
  • Docker builds images automatically by reading the instructions from a Dockerfile -- a text file that contains all commands, in order, needed to build a given image.
  • A Docker image consists of read-only layers each of which represents a Dockerfile instruction.
  • ...47 more annotations...
  • The layers are stacked and each one is a delta of the changes from the previous layer
  • When you run an image and generate a container, you add a new writable layer (the “container layer”) on top of the underlying layers.
  • By “ephemeral,” we mean that the container can be stopped and destroyed, then rebuilt and replaced with an absolute minimum set up and configuration.
  • Inadvertently including files that are not necessary for building an image results in a larger build context and larger image size.
  • To exclude files not relevant to the build (without restructuring your source repository) use a .dockerignore file. This file supports exclusion patterns similar to .gitignore files.
  • minimize image layers by leveraging build cache.
  • if your build contains several layers, you can order them from the less frequently changed (to ensure the build cache is reusable) to the more frequently changed
  • avoid installing extra or unnecessary packages just because they might be “nice to have.”
  • Each container should have only one concern.
  • Decoupling applications into multiple containers makes it easier to scale horizontally and reuse containers
  • Limiting each container to one process is a good rule of thumb, but it is not a hard and fast rule.
  • Use your best judgment to keep containers as clean and modular as possible.
  • do multi-stage builds and only copy the artifacts you need into the final image. This allows you to include tools and debug information in your intermediate build stages without increasing the size of the final image.
  • avoid duplication of packages and make the list much easier to update.
  • When building an image, Docker steps through the instructions in your Dockerfile, executing each in the order specified.
  • the next instruction is compared against all child images derived from that base image to see if one of them was built using the exact same instruction. If not, the cache is invalidated.
  • simply comparing the instruction in the Dockerfile with one of the child images is sufficient.
  • For the ADD and COPY instructions, the contents of the file(s) in the image are examined and a checksum is calculated for each file.
  • If anything has changed in the file(s), such as the contents and metadata, then the cache is invalidated.
  • cache checking does not look at the files in the container to determine a cache match.
  • In that case just the command string itself is used to find a match.
    • 張 旭
      張 旭 on 28 Sep 18
       
      RUN apt-get 這樣的指令，直接比對指令內容的意思。
  • Whenever possible, use current official repositories as the basis for your images.
  • Using RUN apt-get update && apt-get install -y ensures your Dockerfile installs the latest package versions with no further coding or manual intervention.
  • cache busting
  • Docker executes these commands using the /bin/sh -c interpreter, which only evaluates the exit code of the last operation in the pipe to determine success.
  • set -o pipefail && to ensure that an unexpected error prevents the build from inadvertently succeeding.
  • The CMD instruction should be used to run the software contained by your image, along with any arguments.
  • CMD should almost always be used in the form of CMD [“executable”, “param1”, “param2”…]
  • CMD should rarely be used in the manner of CMD [“param”, “param”] in conjunction with ENTRYPOINT
  • The ENV instruction is also useful for providing required environment variables specific to services you wish to containerize,
  • Each ENV line creates a new intermediate layer, just like RUN commands
  • COPY is preferred
  • COPY only supports the basic copying of local files into the container
  • the best use for ADD is local tar file auto-extraction into the image, as in ADD rootfs.tar.xz /
  • If you have multiple Dockerfile steps that use different files from your context, COPY them individually, rather than all at once.
  • using ADD to fetch packages from remote URLs is strongly discouraged; you should use curl or wget instead
  • The best use for ENTRYPOINT is to set the image’s main command, allowing that image to be run as though it was that command (and then use CMD as the default flags).
  • the image name can double as a reference to the binary as shown in the command
  • The VOLUME instruction should be used to expose any database storage area, configuration storage, or files/folders created by your docker container.
  • use VOLUME for any mutable and/or user-serviceable parts of your image
  • If you absolutely need functionality similar to sudo, such as initializing the daemon as root but running it as non-root), consider using “gosu”.
  • always use absolute paths for your WORKDIR
  • An ONBUILD command executes after the current Dockerfile build completes.
  • Think of the ONBUILD command as an instruction the parent Dockerfile gives to the child Dockerfile
  • A Docker build executes ONBUILD commands before any command in a child Dockerfile.
  • Be careful when putting ADD or COPY in ONBUILD. The “onbuild” image fails catastrophically if the new build’s context is missing the resource being added.
張 旭

Backends: State Storage and Locking - Terraform by HashiCorp - 0 views

www.terraform.io/...state.html

terraform devops system storage status

shared by 張 旭 on 07 Apr 19 - No Cached
  • Backends determine where state is stored.
  • backends happen to provide locking: local via system APIs and Consul via locking APIs.
  • manually retrieve the state from the remote state using the terraform state pull command
  • ...3 more annotations...
  • manually write state with terraform state push. This is extremely dangerous and should be avoided if possible. This will overwrite the remote state.
  • The "lineage" is a unique ID assigned to a state when it is created.
  • Every state has a monotonically increasing "serial" number.
  • 張 旭 on 07 Apr 19
     
    "Backends determine where state is stored."
張 旭

Docker for AWS persistent data volumes | Docker Documentation - 0 views

docs.docker.com/...persistent-data-volumes

aws docker system

shared by 張 旭 on 08 Oct 18 - No Cached
  • Cloudstor is a modern volume plugin built by Docker
  • Docker swarm mode tasks and regular Docker containers can use a volume created with Cloudstor to mount a persistent data volume.
  • Global shared Cloudstor volumes mounted by all tasks in a swarm service.
  • ...14 more annotations...
  • Workloads running in a Docker service that require access to low latency/high IOPs persistent storage, such as a database engine, can use a relocatable Cloudstor volume backed by EBS.
  • Each relocatable Cloudstor volume is backed by a single EBS volume.
  • If a swarm task using a relocatable Cloudstor volume gets rescheduled to another node within the same availability zone as the original node where the task was running, Cloudstor detaches the backing EBS volume from the original node and attaches it to the new target node automatically.
  • in a different availability zone,
  • Cloudstor transfers the contents of the backing EBS volume to the destination availability zone using a snapshot, and cleans up the EBS volume in the original availability zone.
  • Typically the snapshot-based transfer process across availability zones takes between 2 and 5 minutes unless the work load is write-heavy.
  • A swarm task is not started until the volume it mounts becomes available
  • Sharing/mounting the same Cloudstor volume backed by EBS among multiple tasks is not a supported scenario and leads to data loss.
  • a Cloudstor volume to share data between tasks, choose the appropriate EFS backed shared volume option.
  • When multiple swarm service tasks need to share data in a persistent storage volume, you can use a shared Cloudstor volume backed by EFS.
  • a volume and its contents can be mounted by multiple swarm service tasks without the risk of data loss
  • over NFS
  • the persistent data backed by EFS volumes is always available.
  • shared Cloudstor volumes only work in those AWS regions where EFS is supported.
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

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

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

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

MongoDB Performance - MongoDB Manual - 0 views

docs.mongodb.com/...analyzing-mongodb-performance

database mongodb performance

shared by 張 旭 on 20 Apr 21 - No Cached
  • MongoDB uses a locking system to ensure data set consistency. If certain operations are long-running or a queue forms, performance will degrade as requests and operations wait for the lock.
  • performance limitations as a result of inadequate or inappropriate indexing strategies, or as a consequence of poor schema design patterns.
  • performance issues may be temporary and related to abnormal traffic load.
  • ...9 more annotations...
  • Lock-related slowdowns can be intermittent.
  • If globalLock.currentQueue.total is consistently high, then there is a chance that a large number of requests are waiting for a lock.
  • If globalLock.totalTime is high relative to uptime, the database has existed in a lock state for a significant amount of time.
  • For write-heavy applications, deploy sharding and add one or more shards to a sharded cluster to distribute load among mongod instances.
  • Unless constrained by system-wide limits, the maximum number of incoming connections supported by MongoDB is configured with the maxIncomingConnections setting.
  • When logLevel is set to 0, MongoDB records slow operations to the diagnostic log at a rate determined by slowOpSampleRate.
  • At higher logLevel settings, all operations appear in the diagnostic log regardless of their latency with the following exception
  • Full Time Diagnostic Data Collection (FTDC) mechanism. FTDC data files are compressed, are not human-readable, and inherit the same file access permissions as the MongoDB data files.
  • mongod processes store FTDC data files in a diagnostic.data directory under the instances storage.dbPath.
  • 張 旭 on 20 Apr 21
     
    "MongoDB uses a locking system to ensure data set consistency. If certain operations are long-running or a queue forms, performance will degrade as requests and operations wait for the lock."
張 旭

Options for Highly Available Topology | Kubernetes - 0 views

kubernetes.io/...ha-topology

kubernetes etcd

shared by 張 旭 on 26 Jan 23 - No Cached
  • With stacked control plane nodes, where etcd nodes are colocated with control plane nodes
  • A stacked HA cluster is a topology where the distributed data storage cluster provided by etcd is stacked on top of the cluster formed by the nodes managed by kubeadm that run control plane components.
  • Each control plane node runs an instance of the kube-apiserver, kube-scheduler, and kube-controller-manager
  • ...6 more annotations...
  • Each control plane node creates a local etcd member and this etcd member communicates only with the kube-apiserver of this node.
  • This topology couples the control planes and etcd members on the same nodes.
  • a stacked cluster runs the risk of failed coupling. If one node goes down, both an etcd member and a control plane instance are lost
  • An HA cluster with external etcd is a topology where the distributed data storage cluster provided by etcd is external to the cluster formed by the nodes that run control plane components.
  • etcd members run on separate hosts, and each etcd host communicates with the kube-apiserver of each control plane node.
  • This topology decouples the control plane and etcd member. It therefore provides an HA setup where losing a control plane instance or an etcd member has less impact and does not affect the cluster redundancy as much as the stacked HA topology.
crazylion lee

Minio - 0 views

minio.io

s3 storage cloud

shared by crazylion lee on 14 Sep 16 - No Cached
  • crazylion lee on 14 Sep 16
     
    "Store photos, videos, VMs, containers, log files, or any blob of data as objects."
張 旭

Getting Started with Rails - Ruby on Rails Guides - 0 views

guides.rubyonrails.org/getting_started.html

shared by 張 旭 on 22 Jan 14 - Cached
  • A controller's purpose is to receive specific requests for the application.
  • Routing decides which controller receives which requests
  • The view should just display that information
  • ...55 more annotations...
  • view templates are written in a language called ERB (Embedded Ruby) which is converted by the request cycle in Rails before being sent to the user.
  • Each action's purpose is to collect information to provide it to a view.
  • A view's purpose is to display this information in a human readable format.
  • routing file which holds entries in a special DSL (domain-specific language) that tells Rails how to connect incoming requests to controllers and actions.
  • You can create, read, update and destroy items for a resource and these operations are referred to as CRUD operations
  • A controller is simply a class that is defined to inherit from ApplicationController.
  • If not found, then it will attempt to load a template called application/new. It looks for one here because the PostsController inherits from ApplicationController
  • :formats specifies the format of template to be served in response. The default format is :html, and so Rails is looking for an HTML template.
  • :handlers, is telling us what template handlers could be used to render our template.
  • When you call form_for, you pass it an identifying object for this form. In this case, it's the symbol :post. This tells the form_for helper what this form is for.
  • that the action attribute for the form is pointing at /posts/new
  • When a form is submitted, the fields of the form are sent to Rails as parameters.
  • parameters can then be referenced inside the controller actions, typically to perform a particular task
  • params method is the object which represents the parameters (or fields) coming in from the form.
  • Active Record is smart enough to automatically map column names to model attributes,
  • Rails uses rake commands to run migrations, and it's possible to undo a migration after it's been applied to your database
  • every Rails model can be initialized with its respective attributes, which are automatically mapped to the respective database columns.
  • migration creates a method named change which will be called when you run this migration.
  • The action defined in this method is also reversible, which means Rails knows how to reverse the change made by this migration, in case you want to reverse it later
  • Migration filenames include a timestamp to ensure that they're processed in the order that they were created.
  • @post.save returns a boolean indicating whether the model was saved or not.
  • prevents an attacker from setting the model's attributes by manipulating the hash passed to the model.
  • If you want to link to an action in the same controller, you don't need to specify the :controller option, as Rails will use the current controller by default.
  • inherits from ActiveRecord::Base
  • Active Record supplies a great deal of functionality to your Rails models for free, including basic database CRUD (Create, Read, Update, Destroy) operations, data validation, as well as sophisticated search support and the ability to relate multiple models to one another.
  • Rails includes methods to help you validate the data that you send to models
  • Rails can validate a variety of conditions in a model, including the presence or uniqueness of columns, their format, and the existence of associated objects.
  • redirect_to will tell the browser to issue another request.
  • rendering is done within the same request as the form submission
  • Each request for a comment has to keep track of the post to which the comment is attached, thus the initial call to the find method of the Post model to get the post in question.
  • pluralize is a rails helper that takes a number and a string as its arguments. If the number is greater than one, the string will be automatically pluralized.
  • The render method is used so that the @post object is passed back to the new template when it is rendered.
  • The method: :patch option tells Rails that we want this form to be submitted via the PATCH HTTP method which is the HTTP method you're expected to use to update resources according to the REST protocol.
  • it accepts a hash containing the attributes that you want to update.
  • field_with_errors. You can define a css rule to make them standout
  • belongs_to :post, which sets up an Active Record association
  • creates comments as a nested resource within posts
  • call destroy on Active Record objects when you want to delete them from the database.
  • Rails allows you to use the dependent option of an association to achieve this.
  • store all external data as UTF-8
  • you're better off ensuring that all external data is UTF-8
  • use UTF-8 as the internal storage of your database
  • Rails defaults to converting data from your database into UTF-8 at the boundary.
  • :patch
  • By default forms built with the form_for helper are sent via POST
  • The :method and :'data-confirm' options are used as HTML5 attributes so that when the link is clicked, Rails will first show a confirm dialog to the user, and then submit the link with method delete. This is done via the JavaScript file jquery_ujs which is automatically included into your application's layout (app/views/layouts/application.html.erb) when you generated the application.
  • Without this file, the confirmation dialog box wouldn't appear.
  • just defines the partial template we want to render
  • As the render method iterates over the @post.comments collection, it assigns each comment to
  • a local variable named the same as the partial
  • use the authentication system
  • require and permit
  • the method is often made private to make sure it can't be called outside its intended context.
  • standard CRUD actions in each controller in the following order: index, show, new, edit, create, update and destroy.
  • must be placed before any private or protected method in the controller in order to work
張 旭

Active Record Basics - Ruby on Rails Guides - 0 views

guides.rubyonrails.org/active_record_basics.html

ruby rails programming development framework model database object

shared by 張 旭 on 22 Jan 14 - No Cached
  • the model - which is the layer of the system responsible for representing business data and logic.
  • Active Record facilitates the creation and use of business objects whose data requires persistent storage to a database
  • Database Table - Plural with underscores separating words
  • ...33 more annotations...
  • objects carry both persistent data and behavior which operates on that data
  • Object-Relational Mapping, commonly referred to as its abbreviation ORM, is a technique that connects the rich objects of an application to tables in a relational database management system
  • Represent associations between these models
  • Validate models before they get persisted to the database
  • The idea is that if you configure your applications in the very same way most of the times then this should be the default way.
  • Rails will pluralize your class names to find the respective database table.
  • use the ActiveRecord::Base.table_name= method to specify the table name
  • Model Class - Singular with the first letter of each word capitalized
  • Foreign keys - These fields should be named following the pattern singularized_table_name_id
  • Primary keys - By default, Active Record will use an integer column named id as the table's primary key
  • created_at
  • updated_at
  • (table_name)_count - Used to cache the number of belonging objects on associations.
  • Object Relational Mapping
  • Single Table Inheritance (STI)
  • rake db:rollback
  • ActiveRecord::Base.primary_key=
  • CRUD is an acronym for the four verbs we use to operate on data: Create, Read, Update and Delete.
  • new method will return a new object
  • create will return the object and save it to the database.
  • Using the new method, an object can be instantiated without being saved
  • user.save will commit the record to the database
  • update_all class method
  • an Active Record object can be destroyed which removes it from the database
  • Validation is a very important issue to consider when persisting to database, so the methods create, save and update take it into account when running: they return false when validation fails and they didn't actually perform any operation on database.
  • a bang counterpart
  • Active Record callbacks allow you to attach code to certain events in the life-cycle of your models
  • Rails keeps track of which files have been committed to the database and provides rollback features
  • rake db:migrate
  • class_name.yml
  • Convention over Configuration
    • 張 旭
      張 旭 on 12 Apr 16
       
      Model 是單數，Table 是複數。想象一下，處理 Object 的時候是逐一處理，但是存放的地方是放了一堆 Objects。
    • 張 旭
      張 旭 on 12 Apr 16
       
      外鍵是單數的形式，這也很好理解：因為關聯到的是一個外部的 Object
張 旭

Managing files | Django documentation | Django - 0 views

docs.djangoproject.com/...files

python django web framework

shared by 張 旭 on 14 Oct 18 - No Cached
  • By default, Django stores files locally, using the MEDIA_ROOT and MEDIA_URL settings.
  • use a FileField or ImageField, Django provides a set of APIs you can use to deal with that file.
  • Behind the scenes, Django delegates decisions about how and where to store files to a file storage system.
  • ...1 more annotation...
  • Django uses a django.core.files.File instance any time it needs to represent a file.
張 旭

Virtual Private Cloud (VPC)  |  Virtual Private Cloud  |  Google Cloud - 0 views

cloud.google.com/vpc

google gcp cloud system

shared by 張 旭 on 09 Nov 18 - No Cached
  • A single Google Cloud VPC can span multiple regions without communicating across the public Internet.
  • Google Cloud VPCs let you increase the IP space of any subnets without any workload shutdown or downtime.
  • Get private access to Google services, such as storage, big data, analytics, or machine learning, without having to give your service a public IP address.
  • ...3 more annotations...
  • Enable dynamic Border Gateway Protocol (BGP) route updates between your VPC network and your non-Google network with our virtual router.
  • Configure a VPC Network to be shared across several projects in your organization.
  • Hosting globally distributed multi-tier applications, by creating a VPC with subnets.
張 旭

Secrets Management with Terraform - 0 views

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

terraform config devops security

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

Glossary - CircleCI - 0 views

circleci.com/glossary

circleci CI system deploy

shared by 張 旭 on 25 Nov 18 - No Cached
  • User authentication may use LDAP for an instance of the CircleCI application that is installed on your private server or cloud
  • The first user to log into a private installation of CircleCI
  • Contexts provide a mechanism for securing and sharing environment variables across projects.
  • ...22 more annotations...
  • The environment variables are defined as name/value pairs and are injected at runtime.
  • The CircleCI Docker Layer Caching feature allows builds to reuse Docker image layers
  • from previous builds.
  • Image layers are stored in separate volumes in the cloud and are not shared between projects.
  • Layers may only be used by builds from the same project.
  • Environment variables store customer data that is used by a project.
  • Defines the underlying technology to run a job.
  • machine to run your job inside a full virtual machine.
  • docker to run your job inside a Docker container with a specified image
  • A job is a collection of steps.
  • The first image listed in config.yml
  • A CircleCI project shares the name of the code repository for which it automates workflows, tests, and deployment.
  • must be added with the Add Project button
  • Following a project enables a user to subscribe to email notifications for the project build status and adds the project to their CircleCI dashboard.
  • A step is a collection of executable commands
  • Users must be added to a GitHub or Bitbucket org to view or follow associated CircleCI projects.
  • Users may not view project data that is stored in environment variables.  
  • A Workflow is a set of rules for defining a collection of jobs and their run order.
  • Workflows are implemented as a directed acyclic graph (DAG) of jobs for greatest flexibility.
  • referred to as Pipelines
  • A workspace is a workflows-aware storage mechanism.
  • A workspace stores data unique to the job, which may be needed in downstream jobs.
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

JSON Web Token Introduction - jwt.io - 0 views

jwt.io/introduction

javascript jwt authorization authentication oauth security

shared by 張 旭 on 24 Apr 18 - No Cached
  • a stateless authentication mechanism as the user state is never saved in server memory
  • In authentication, when the user successfully logs in using their credentials, a JSON Web Token will be returned and must be saved locally (typically in local storage, but cookies can be also used), instead of the traditional approach of creating a session in the server and returning a cookie.
  • ser agent should send the JWT, typically in the Authorization header using the Bearer schema.
  • ...2 more annotations...
  • It doesn't matter which domains are serving your APIs, so Cross-Origin Resource Sharing (CORS) won't be an issue as it doesn't use cookies.
  • WT and SAML tokens can use a public/private key pair in the form of a X.509 certificate for signing.
張 旭

Helm | - 0 views

helm.sh/using_helm

kubernetes helm system

shared by 張 旭 on 17 Jul 19 - No Cached
  • Helm will figure out where to install Tiller by reading your Kubernetes configuration file (usually $HOME/.kube/config). This is the same file that kubectl uses.
  • kubectl cluster-info
  • Role-Based Access Control (RBAC) enabled
  • ...133 more annotations...
  • initialize the local CLI
  • install Tiller into your Kubernetes cluster
  • helm install
  • helm init --upgrade
  • By default, when Tiller is installed, it does not have authentication enabled.
  • helm repo update
  • Without a max history set the history is kept indefinitely, leaving a large number of records for helm and tiller to maintain.
  • helm init --upgrade
  • Whenever you install a chart, a new release is created.
  • one chart can be installed multiple times into the same cluster. And each can be independently managed and upgraded.
  • helm list function will show you a list of all deployed releases.
  • helm delete
  • helm status
  • you can audit a cluster’s history, and even undelete a release (with helm rollback).
  • the Helm server (Tiller).
  • The Helm client (helm)
  • brew install kubernetes-helm
  • Tiller, the server portion of Helm, typically runs inside of your Kubernetes cluster.
  • it can also be run locally, and configured to talk to a remote Kubernetes cluster.
  • Role-Based Access Control - RBAC for short
  • create a service account for Tiller with the right roles and permissions to access resources.
  • run Tiller in an RBAC-enabled Kubernetes cluster.
  • run kubectl get pods --namespace kube-system and see Tiller running.
  • helm inspect
  • Helm will look for Tiller in the kube-system namespace unless --tiller-namespace or TILLER_NAMESPACE is set.
  • For development, it is sometimes easier to work on Tiller locally, and configure it to connect to a remote Kubernetes cluster.
  • even when running locally, Tiller will store release configuration in ConfigMaps inside of Kubernetes.
  • helm version should show you both the client and server version.
  • Tiller stores its data in Kubernetes ConfigMaps, you can safely delete and re-install Tiller without worrying about losing any data.
  • helm reset
  • The --node-selectors flag allows us to specify the node labels required for scheduling the Tiller pod.
  • --override allows you to specify properties of Tiller’s deployment manifest.
  • helm init --override manipulates the specified properties of the final manifest (there is no “values” file).
  • The --output flag allows us skip the installation of Tiller’s deployment manifest and simply output the deployment manifest to stdout in either JSON or YAML format.
  • By default, tiller stores release information in ConfigMaps in the namespace where it is running.
  • switch from the default backend to the secrets backend, you’ll have to do the migration for this on your own.
  • a beta SQL storage backend that stores release information in an SQL database (only postgres has been tested so far).
  • Once you have the Helm Client and Tiller successfully installed, you can move on to using Helm to manage charts.
  • Helm requires that kubelet have access to a copy of the socat program to proxy connections to the Tiller API.
  • A Release is an instance of a chart running in a Kubernetes cluster. One chart can often be installed many times into the same cluster.
  • helm init --client-only
  • helm init --dry-run --debug
  • A panic in Tiller is almost always the result of a failure to negotiate with the Kubernetes API server
  • Tiller and Helm have to negotiate a common version to make sure that they can safely communicate without breaking API assumptions
  • helm delete --purge
  • Helm stores some files in $HELM_HOME, which is located by default in ~/.helm
  • A Chart is a Helm package. It contains all of the resource definitions necessary to run an application, tool, or service inside of a Kubernetes cluster.
  • it like the Kubernetes equivalent of a Homebrew formula, an Apt dpkg, or a Yum RPM file.
  • A Repository is the place where charts can be collected and shared.
  • Set the $HELM_HOME environment variable
  • each time it is installed, a new release is created.
  • Helm installs charts into Kubernetes, creating a new release for each installation. And to find new charts, you can search Helm chart repositories.
  • chart repository is named stable by default
  • helm search shows you all of the available charts
  • helm inspect
  • To install a new package, use the helm install command. At its simplest, it takes only one argument: The name of the chart.
  • If you want to use your own release name, simply use the --name flag on helm install
  • additional configuration steps you can or should take.
  • Helm does not wait until all of the resources are running before it exits. Many charts require Docker images that are over 600M in size, and may take a long time to install into the cluster.
  • helm status
  • helm inspect values
  • helm inspect values stable/mariadb
  • override any of these settings in a YAML formatted file, and then pass that file during installation.
  • helm install -f config.yaml stable/mariadb
  • --values (or -f): Specify a YAML file with overrides.
  • --set (and its variants --set-string and --set-file): Specify overrides on the command line.
  • Values that have been --set can be cleared by running helm upgrade with --reset-values specified.
  • Chart designers are encouraged to consider the --set usage when designing the format of a values.yaml file.
  • --set-file key=filepath is another variant of --set. It reads the file and use its content as a value.
  • inject a multi-line text into values without dealing with indentation in YAML.
  • An unpacked chart directory
  • When a new version of a chart is released, or when you want to change the configuration of your release, you can use the helm upgrade command.
  • Kubernetes charts can be large and complex, Helm tries to perform the least invasive upgrade.
  • It will only update things that have changed since the last release
  • $ helm upgrade -f panda.yaml happy-panda stable/mariadb
  • deployment
  • If both are used, --set values are merged into --values with higher precedence.
  • The helm get command is a useful tool for looking at a release in the cluster.
  • helm rollback
  • A release version is an incremental revision. Every time an install, upgrade, or rollback happens, the revision number is incremented by 1.
  • helm history
  • a release name cannot be re-used.
  • you can rollback a deleted resource, and have it re-activate.
  • helm repo list
  • helm repo add
  • helm repo update
  • The Chart Development Guide explains how to develop your own charts.
  • helm create
  • helm lint
  • helm package
  • Charts that are archived can be loaded into chart repositories.
  • chart repository server
  • Tiller can be installed into any namespace.
  • Limiting Tiller to only be able to install into specific namespaces and/or resource types is controlled by Kubernetes RBAC roles and rolebindings
  • Release names are unique PER TILLER INSTANCE
  • Charts should only contain resources that exist in a single namespace.
  • not recommended to have multiple Tillers configured to manage resources in the same namespace.
  • a client-side Helm plugin. A plugin is a tool that can be accessed through the helm CLI, but which is not part of the built-in Helm codebase.
  • Helm plugins are add-on tools that integrate seamlessly with Helm. They provide a way to extend the core feature set of Helm, but without requiring every new feature to be written in Go and added to the core tool.
  • Helm plugins live in $(helm home)/plugins
  • The Helm plugin model is partially modeled on Git’s plugin model
  • helm referred to as the porcelain layer, with plugins being the plumbing.
  • helm plugin install https://github.com/technosophos/helm-template
  • command is the command that this plugin will execute when it is called.
  • Environment variables are interpolated before the plugin is executed.
  • The command itself is not executed in a shell. So you can’t oneline a shell script.
  • Helm is able to fetch Charts using HTTP/S
  • Variables like KUBECONFIG are set for the plugin if they are set in the outer environment.
  • In Kubernetes, granting a role to an application-specific service account is a best practice to ensure that your application is operating in the scope that you have specified.
  • restrict Tiller’s capabilities to install resources to certain namespaces, or to grant a Helm client running access to a Tiller instance.
  • Service account with cluster-admin role
  • The cluster-admin role is created by default in a Kubernetes cluster
  • Deploy Tiller in a namespace, restricted to deploying resources only in that namespace
  • Deploy Tiller in a namespace, restricted to deploying resources in another namespace
  • When running a Helm client in a pod, in order for the Helm client to talk to a Tiller instance, it will need certain privileges to be granted.
  • SSL Between Helm and Tiller
  • The Tiller authentication model uses client-side SSL certificates.
  • creating an internal CA, and using both the cryptographic and identity functions of SSL.
  • Helm is a powerful and flexible package-management and operations tool for Kubernetes.
  • default installation applies no security configurations
  • with a cluster that is well-secured in a private network with no data-sharing or no other users or teams.
  • With great power comes great responsibility.
  • Choose the Best Practices you should apply to your helm installation
  • Role-based access control, or RBAC
  • Tiller’s gRPC endpoint and its usage by Helm
  • Kubernetes employ a role-based access control (or RBAC) system (as do modern operating systems) to help mitigate the damage that can be done if credentials are misused or bugs exist.
  • In the default installation the gRPC endpoint that Tiller offers is available inside the cluster (not external to the cluster) without authentication configuration applied.
  • Tiller stores its release information in ConfigMaps. We suggest changing the default to Secrets.
  • release information
  • charts
  • charts are a kind of package that not only installs containers you may or may not have validated yourself, but it may also install into more than one namespace.
  • As with all shared software, in a controlled or shared environment you must validate all software you install yourself before you install it.
  • Helm’s provenance tools to ensure the provenance and integrity of charts
  • 張 旭 on 17 Jul 19
     
    "Helm will figure out where to install Tiller by reading your Kubernetes configuration file (usually $HOME/.kube/config). This is the same file that kubectl uses."
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