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張 旭

Boosting your kubectl productivity ♦︎ Learnk8s - 0 views

  • kubectl is your cockpit to control Kubernetes.
  • kubectl is a client for the Kubernetes API
  • Kubernetes API is an HTTP REST API.
  • ...75 more annotations...
  • This API is the real Kubernetes user interface.
  • Kubernetes is fully controlled through this API
  • every Kubernetes operation is exposed as an API endpoint and can be executed by an HTTP request to this endpoint.
  • the main job of kubectl is to carry out HTTP requests to the Kubernetes API
  • Kubernetes maintains an internal state of resources, and all Kubernetes operations are CRUD operations on these resources.
  • Kubernetes is a fully resource-centred system
  • Kubernetes API reference is organised as a list of resource types with their associated operations.
  • This is how kubectl works for all commands that interact with the Kubernetes cluster.
  • kubectl simply makes HTTP requests to the appropriate Kubernetes API endpoints.
  • it's totally possible to control Kubernetes with a tool like curl by manually issuing HTTP requests to the Kubernetes API.
  • Kubernetes consists of a set of independent components that run as separate processes on the nodes of a cluster.
  • components on the master nodes
  • Storage backend: stores resource definitions (usually etcd is used)
  • API server: provides Kubernetes API and manages storage backend
  • Controller manager: ensures resource statuses match specifications
  • Scheduler: schedules Pods to worker nodes
  • component on the worker nodes
  • Kubelet: manages execution of containers on a worker node
  • triggers the ReplicaSet controller, which is a sub-process of the controller manager.
  • the scheduler, who watches for Pod definitions that are not yet scheduled to a worker node.
  • creating and updating resources in the storage backend on the master node.
  • The kubelet of the worker node your ReplicaSet Pods have been scheduled to instructs the configured container runtime (which may be Docker) to download the required container images and run the containers.
  • Kubernetes components (except the API server and the storage backend) work by watching for resource changes in the storage backend and manipulating resources in the storage backend.
  • However, these components do not access the storage backend directly, but only through the Kubernetes API.
    • 張 旭
       
      很精彩,相互之間都是使用 API call 溝通,良好的微服務行為。
  • double usage of the Kubernetes API for internal components as well as for external users is a fundamental design concept of Kubernetes.
  • All other Kubernetes components and users read, watch, and manipulate the state (i.e. resources) of Kubernetes through the Kubernetes API
  • The storage backend stores the state (i.e. resources) of Kubernetes.
  • command completion is a shell feature that works by the means of a completion script.
  • A completion script is a shell script that defines the completion behaviour for a specific command. Sourcing a completion script enables completion for the corresponding command.
  • kubectl completion zsh
  • /etc/bash_completion.d directory (create it, if it doesn't exist)
  • source <(kubectl completion bash)
  • source <(kubectl completion zsh)
  • autoload -Uz compinit compinit
  • the API reference, which contains the full specifications of all resources.
  • kubectl api-resources
  • displays the resource names in their plural form (e.g. deployments instead of deployment). It also displays the shortname (e.g. deploy) for those resources that have one. Don't worry about these differences. All of these name variants are equivalent for kubectl.
  • .spec
  • custom columns output format comes in. It lets you freely define the columns and the data to display in them. You can choose any field of a resource to be displayed as a separate column in the output
  • kubectl get pods -o custom-columns='NAME:metadata.name,NODE:spec.nodeName'
  • kubectl explain pod.spec.
  • kubectl explain pod.metadata.
  • browse the resource specifications and try it out with any fields you like!
  • JSONPath is a language to extract data from JSON documents (it is similar to XPath for XML).
  • with kubectl explain, only a subset of the JSONPath capabilities is supported
  • Many fields of Kubernetes resources are lists, and this operator allows you to select items of these lists. It is often used with a wildcard as [*] to select all items of the list.
  • kubectl get pods -o custom-columns='NAME:metadata.name,IMAGES:spec.containers[*].image'
  • a Pod may contain more than one container.
  • The availability zones for each node are obtained through the special failure-domain.beta.kubernetes.io/zone label.
  • kubectl get nodes -o yaml kubectl get nodes -o json
  • The default kubeconfig file is ~/.kube/config
  • with multiple clusters, then you have connection parameters for multiple clusters configured in your kubeconfig file.
  • Within a cluster, you can set up multiple namespaces (a namespace is kind of "virtual" clusters within a physical cluster)
  • overwrite the default kubeconfig file with the --kubeconfig option for every kubectl command.
  • Namespace: the namespace to use when connecting to the cluster
  • a one-to-one mapping between clusters and contexts.
  • When kubectl reads a kubeconfig file, it always uses the information from the current context.
  • just change the current context in the kubeconfig file
  • to switch to another namespace in the same cluster, you can change the value of the namespace element of the current context
  • kubectl also provides the --cluster, --user, --namespace, and --context options that allow you to overwrite individual elements and the current context itself, regardless of what is set in the kubeconfig file.
  • for switching between clusters and namespaces is kubectx.
  • kubectl config get-contexts
  • just have to download the shell scripts named kubectl-ctx and kubectl-ns to any directory in your PATH and make them executable (for example, with chmod +x)
  • kubectl proxy
  • kubectl get roles
  • kubectl get pod
  • Kubectl plugins are distributed as simple executable files with a name of the form kubectl-x. The prefix kubectl- is mandatory,
  • To install a plugin, you just have to copy the kubectl-x file to any directory in your PATH and make it executable (for example, with chmod +x)
  • krew itself is a kubectl plugin
  • check out the kubectl-plugins GitHub topic
  • The executable can be of any type, a Bash script, a compiled Go program, a Python script, it really doesn't matter. The only requirement is that it can be directly executed by the operating system.
  • kubectl plugins can be written in any programming or scripting language.
  • you can write more sophisticated plugins with real programming languages, for example, using a Kubernetes client library. If you use Go, you can also use the cli-runtime library, which exists specifically for writing kubectl plugins.
  • a kubeconfig file consists of a set of contexts
  • changing the current context means changing the cluster, if you have only a single context per cluster.
張 旭

How Percona XtraBackup Works - 0 views

  • Percona XtraBackup is based on InnoDB‘s crash-recovery functionality.
  • it performs crash recovery on the files to make them a consistent, usable database again
  • InnoDB maintains a redo log, also called the transaction log. This contains a record of every change to InnoDB data.
  • ...14 more annotations...
  • When InnoDB starts, it inspects the data files and the transaction log, and performs two steps. It applies committed transaction log entries to the data files, and it performs an undo operation on any transactions that modified data but did not commit.
  • Percona XtraBackup works by remembering the log sequence number (LSN) when it starts, and then copying away the data files.
  • Percona XtraBackup runs a background process that watches the transaction log files, and copies changes from it.
  • Percona XtraBackup needs to do this continually
  • Percona XtraBackup needs the transaction log records for every change to the data files since it began execution.
  • Percona XtraBackup uses Backup locks where available as a lightweight alternative to FLUSH TABLES WITH READ LOCK.
  • Locking is only done for MyISAM and other non-InnoDB tables after Percona XtraBackup finishes backing up all InnoDB/XtraDB data and logs.
  • xtrabackup tries to avoid backup locks and FLUSH TABLES WITH READ LOCK when the instance contains only InnoDB tables. In this case, xtrabackup obtains binary log coordinates from performance_schema.log_status
  • When backup locks are supported by the server, xtrabackup first copies InnoDB data, runs the LOCK TABLES FOR BACKUP and then copies the MyISAM tables.
  • the STDERR of xtrabackup is not written in any file. You will have to redirect it to a file, e.g., xtrabackup OPTIONS 2> backupout.log
  • During the prepare phase, Percona XtraBackup performs crash recovery against the copied data files, using the copied transaction log file. After this is done, the database is ready to restore and use.
  • the tools enable you to do operations such as streaming and incremental backups with various combinations of copying the data files, copying the log files, and applying the logs to the data.
  • To restore a backup with xtrabackup you can use the --copy-back or --move-back options.
  • you may have to change the files’ ownership to mysql before starting the database server, as they will be owned by the user who created the backup.
  •  
    "Percona XtraBackup is based on InnoDB's crash-recovery functionality."
張 旭

Best practices for writing Dockerfiles | Docker Documentation - 0 views

  • 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
       
      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.
crazylion lee

Good Copy * Email copy from great companies - 0 views

  •  
    "mail copy from great companies. Brought to you by Front."
張 旭

The Backup Cycle - Full Backups - 0 views

  • xtrabackup will not overwrite existing files, it will fail with operating system error 17, file exists.
  • Log copying thread checks the transactional log every second to see if there were any new log records written that need to be copied, but there is a chance that the log copying thread might not be able to keep up with the amount of writes that go to the transactional logs, and will hit an error when the log records are overwritten before they could be read.
  • It is safe to cancel at any time, because xtrabackup does not modify the database.
  • ...15 more annotations...
  • need to prepare it in order to restore it.
  • Data files are not point-in-time consistent until they are prepared, because they were copied at different times as the program ran, and they might have been changed while this was happening.
  • You can run the prepare operation on any machine; it does not need to be on the originating server or the server to which you intend to restore.
  • you simply run xtrabackup with the --prepare option and tell it which directory to prepare,
  • All following prepares will not change the already prepared data files
  • It is not recommended to interrupt xtrabackup process while preparing backup
  • Backup validity is not guaranteed if prepare process was interrupted.
  • If you intend the backup to be the basis for further incremental backups, you should use the --apply-log-only option when preparing the backup, or you will not be able to apply incremental backups to it.
  • Backup needs to be prepared before it can be restored.
  • xtrabackup --copy-back --target-dir=/data/backups/
  • The datadir must be empty before restoring the backup.
  • MySQL server needs to be shut down before restore is performed.
  • You cannot restore to a datadir of a running mysqld instance (except when importing a partial backup).
  • rsync -avrP /data/backup/ /var/lib/mysql/
  • chown -R mysql:mysql /var/lib/mysql
張 旭

How to write excellent Dockerfiles - 0 views

  • minimize image size, build time and number of layers.
  • maximize build cache usage
  • Container should do one thing
    • 張 旭
       
      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
       
      不是說要用 COPY 嗎?
張 旭

Best practices for writing Dockerfiles - Docker Documentation - 0 views

  • Run only one process per container
  • use current Official Repositories as the basis for your image
  • put long or complex RUN statements on multiple lines separated with backslashes.
  • ...16 more annotations...
  • CMD instruction should be used to run the software contained by your image, along with any arguments
  • CMD should be given an interactive shell (bash, python, perl, etc)
  • COPY them individually, rather than all at once
  • COPY is preferred
  • using ADD to fetch packages from remote URLs is strongly discouraged
  • always use COPY
  • 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 above
  • ENTRYPOINT instruction can also be used in combination with a helper script
  • The VOLUME instruction should be used to expose any database storage area, configuration storage, or files/folders created by your docker container.
  • use USER to change to a non-root user
  • avoid installing or using sudo
  • avoid switching USER back and forth frequently.
  • always use absolute paths for your WORKDIR
  • ONBUILD is only useful for images that are going to be built FROM a given image
  • The “onbuild” image will fail catastrophically if the new build's context is missing the resource being added.
張 旭

Use multi-stage builds | Docker Documentation - 0 views

  • Maintaining two Dockerfiles is not ideal.
  • This is failure-prone and hard to maintain. It’s easy to insert another command and forget to continue the line using the \ character
  • create a container from it to copy the artifact out
  • ...4 more annotations...
  • You only need the single Dockerfile. You don’t need a separate build script,
  • You don’t need to create any intermediate images and you don’t need to extract any artifacts to your local system at all.
  • Debugging a specific build stage
  • You can use the COPY --from instruction to copy from a separate image, either using the local image name, a tag available locally or on a Docker registry, or a tag ID.
張 旭

The Twelve-Factor App - 0 views

  • A copy of the revision tracking database is known as a code repository, often shortened to code repo or just repo.
  • always a one-to-one correlation between the codebase and the app
  • If there are multiple codebases, it’s not an app – it’s a distributed system.
  • ...4 more annotations...
  • Each component in a distributed system is an app
  • only one codebase per app, but there will be many deploys of the app.
  • A deploy is a running instance of the app.
  • The codebase is the same across all deploys, although different versions may be active in each deploy.
  •  
    "A copy of the revision tracking database is known as a code repository, often shortened to code repo or just repo."
張 旭

What is a DNS Zone? Master and Slave DNS Zone and how to create it. - 0 views

  • DNS zone is a container of DNS settings and DNS records of a DNS namespace.
  • The DNS namespace can have single or multiple DNS zones, each managed by a particular DNS host/service.
  • Don’t directly associate a DNS zone with a specific domain.
  • ...9 more annotations...
  • DNS zones can be on the same servers
  • A DNS zone may contain multiple domain names or a single one;
  • Master zones, contain a read/write copy of the zone data.
  • There could be only one Master zone on one DNS server at a time.
  • If you want to have redundancy, you must have the zone data accessible on multiple servers.
  • The Slave zone is a read-only copy of the zone data.
  • Most of the times Slave DNS zones are copies of Master zones.
  • If you try to change a DNS record on a Secondary zone, it can redirect you to another zone with read/write access. By itself, it can’t change it.
  • the primary purposes of a Slave zone is to serve as a backup
張 旭

- 0 views

  • A fast-forward merge can happen when the current branch has no extra commits compared to the branch we’re merging.
  • With a no-fast-forward merge, Git creates a new merging commit on the active branch.
  • We can manually remove the changes we don't want to keep, save the changes, add the changed file again, and commit the changes
  • ...14 more annotations...
  • A git rebase copies the commits from the current branch, and puts these copied commits on top of the specified branch.
  • The branch that we're rebasing always has the latest changes that we want to keep!
  • A git rebase changes the history of the project as new hashes are created for the copied commits!
  • Rebasing is great whenever you're working on a feature branch, and the master branch has been updated.
  • An interactive rebase can also be useful on the branch you're currently working on, and want to modify some commits.
  • A git reset gets rid of all the current staged files and gives us control over where HEAD should point to.
  • A soft reset moves HEAD to the specified commit (or the index of the commit compared to HEAD)
  • Git should simply reset its state back to where it was on the specified commit: this even includes the changes in your working directory and staged files!
  • By reverting a certain commit, we create a new commit that contains the reverted changes!
  • Performing a git revert is very useful in order to undo a certain commit, without modifying the history of the branch.
  • By cherry-picking a commit, we create a new commit on our active branch that contains the changes that were introduced by the cherry-picked commit.
  • a fetch simply downloads new data.
  • A git pull is actually two commands in one: a git fetch, and a git merge
  • git reflog is a very useful command in order to show a log of all the actions that have been taken
張 旭

Creating Highly Available clusters with kubeadm | Kubernetes - 0 views

  • If instead, you prefer to copy certs across control-plane nodes manually or using automation tools, please remove this flag and refer to Manual certificate distribution section below.
  • if you are using a kubeadm configuration file set the podSubnet field under the networking object of ClusterConfiguration.
  • manually copy the certificates from the primary control plane node to the joining control plane nodes.
  • ...1 more annotation...
  • Copy only the certificates in the above list. kubeadm will take care of generating the rest of the certificates with the required SANs for the joining control-plane instances.
crazylion lee

How to record your terminal session on Linux - 0 views

  •  
    "Recording a terminal session may be important in helping someone learn a process, sharing information in an understandable way, and also presenting a series of commands in a proper manner. Whatever the purpose, there are many times when copy-pasting text from the terminal won't be very helpful while capturing a video of the process is quite far-fetched and may not be always possible. In this quick guide, we will take a look at the easiest way to record and share a terminal session in .gif format."
crazylion lee

danielstjules/jsinspect · GitHub - 0 views

  •  
    "Detect copy-pasted and structurally similar code"
crazylion lee

zenorocha/clipboard.js - 0 views

  •  
    "Modern copy to clipboard. No Flash"
張 旭

Template Designer Documentation - Jinja2 Documentation (2.10) - 0 views

  • A Jinja template doesn’t need to have a specific extension
  • A Jinja template is simply a text file
  • tags, which control the logic of the template
  • ...106 more annotations...
  • {% ... %} for Statements
  • {{ ... }} for Expressions to print to the template output
  • use a dot (.) to access attributes of a variable
  • the outer double-curly braces are not part of the variable, but the print statement.
  • If you access variables inside tags don’t put the braces around them.
  • If a variable or attribute does not exist, you will get back an undefined value.
  • the default behavior is to evaluate to an empty string if printed or iterated over, and to fail for every other operation.
  • if an object has an item and attribute with the same name. Additionally, the attr() filter only looks up attributes.
  • Variables can be modified by filters. Filters are separated from the variable by a pipe symbol (|) and may have optional arguments in parentheses.
  • Multiple filters can be chained
  • Tests can be used to test a variable against a common expression.
  • add is plus the name of the test after the variable.
  • to find out if a variable is defined, you can do name is defined, which will then return true or false depending on whether name is defined in the current template context.
  • strip whitespace in templates by hand. If you add a minus sign (-) to the start or end of a block (e.g. a For tag), a comment, or a variable expression, the whitespaces before or after that block will be removed
  • not add whitespace between the tag and the minus sign
  • mark a block raw
  • Template inheritance allows you to build a base “skeleton” template that contains all the common elements of your site and defines blocks that child templates can override.
  • The {% extends %} tag is the key here. It tells the template engine that this template “extends” another template.
  • access templates in subdirectories with a slash
  • can’t define multiple {% block %} tags with the same name in the same template
  • use the special self variable and call the block with that name
  • self.title()
  • super()
  • put the name of the block after the end tag for better readability
  • if the block is replaced by a child template, a variable would appear that was not defined in the block or passed to the context.
  • setting the block to “scoped” by adding the scoped modifier to a block declaration
  • If you have a variable that may include any of the following chars (>, <, &, or ") you SHOULD escape it unless the variable contains well-formed and trusted HTML.
  • Jinja2 functions (macros, super, self.BLOCKNAME) always return template data that is marked as safe.
  • With the default syntax, control structures appear inside {% ... %} blocks.
  • the dictsort filter
  • loop.cycle
  • Unlike in Python, it’s not possible to break or continue in a loop
  • use loops recursively
  • add the recursive modifier to the loop definition and call the loop variable with the new iterable where you want to recurse.
  • The loop variable always refers to the closest (innermost) loop.
  • whether the value changed at all,
  • use it to test if a variable is defined, not empty and not false
  • Macros are comparable with functions in regular programming languages.
  • If a macro name starts with an underscore, it’s not exported and can’t be imported.
  • pass a macro to another macro
  • caller()
  • a single trailing newline is stripped if present
  • other whitespace (spaces, tabs, newlines etc.) is returned unchanged
  • a block tag works in “both” directions. That is, a block tag doesn’t just provide a placeholder to fill - it also defines the content that fills the placeholder in the parent.
  • Python dicts are not ordered
  • caller(user)
  • call(user)
  • This is a simple dialog rendered by using a macro and a call block.
  • Filter sections allow you to apply regular Jinja2 filters on a block of template data.
  • Assignments at top level (outside of blocks, macros or loops) are exported from the template like top level macros and can be imported by other templates.
  • using namespace objects which allow propagating of changes across scopes
  • use block assignments to capture the contents of a block into a variable name.
  • The extends tag can be used to extend one template from another.
  • Blocks are used for inheritance and act as both placeholders and replacements at the same time.
  • The include statement is useful to include a template and return the rendered contents of that file into the current namespace
  • Included templates have access to the variables of the active context by default.
  • putting often used code into macros
  • imports are cached and imported templates don’t have access to the current template variables, just the globals by default.
  • Macros and variables starting with one or more underscores are private and cannot be imported.
  • By default, included templates are passed the current context and imported templates are not.
  • imports are often used just as a module that holds macros.
  • Integers and floating point numbers are created by just writing the number down
  • Everything between two brackets is a list.
  • Tuples are like lists that cannot be modified (“immutable”).
  • A dict in Python is a structure that combines keys and values.
  • // Divide two numbers and return the truncated integer result
  • The special constants true, false, and none are indeed lowercase
  • all Jinja identifiers are lowercase
  • (expr) group an expression.
  • The is and in operators support negation using an infix notation
  • in Perform a sequence / mapping containment test.
  • | Applies a filter.
  • ~ Converts all operands into strings and concatenates them.
  • use inline if expressions.
  • always an attribute is returned and items are not looked up.
  • default(value, default_value=u'', boolean=False)¶ If the value is undefined it will return the passed default value, otherwise the value of the variable
  • dictsort(value, case_sensitive=False, by='key', reverse=False)¶ Sort a dict and yield (key, value) pairs.
  • format(value, *args, **kwargs)¶ Apply python string formatting on an object
  • groupby(value, attribute)¶ Group a sequence of objects by a common attribute.
  • grouping by is stored in the grouper attribute and the list contains all the objects that have this grouper in common.
  • indent(s, width=4, first=False, blank=False, indentfirst=None)¶ Return a copy of the string with each line indented by 4 spaces. The first line and blank lines are not indented by default.
  • join(value, d=u'', attribute=None)¶ Return a string which is the concatenation of the strings in the sequence.
  • map()¶ Applies a filter on a sequence of objects or looks up an attribute.
  • pprint(value, verbose=False)¶ Pretty print a variable. Useful for debugging.
  • reject()¶ Filters a sequence of objects by applying a test to each object, and rejecting the objects with the test succeeding.
  • replace(s, old, new, count=None)¶ Return a copy of the value with all occurrences of a substring replaced with a new one.
  • round(value, precision=0, method='common')¶ Round the number to a given precision
  • even if rounded to 0 precision, a float is returned.
  • select()¶ Filters a sequence of objects by applying a test to each object, and only selecting the objects with the test succeeding.
  • sort(value, reverse=False, case_sensitive=False, attribute=None)¶ Sort an iterable. Per default it sorts ascending, if you pass it true as first argument it will reverse the sorting.
  • striptags(value)¶ Strip SGML/XML tags and replace adjacent whitespace by one space.
  • tojson(value, indent=None)¶ Dumps a structure to JSON so that it’s safe to use in <script> tags.
  • trim(value)¶ Strip leading and trailing whitespace.
  • unique(value, case_sensitive=False, attribute=None)¶ Returns a list of unique items from the the given iterable
  • urlize(value, trim_url_limit=None, nofollow=False, target=None, rel=None)¶ Converts URLs in plain text into clickable links.
  • defined(value)¶ Return true if the variable is defined
  • in(value, seq)¶ Check if value is in seq.
  • mapping(value)¶ Return true if the object is a mapping (dict etc.).
  • number(value)¶ Return true if the variable is a number.
  • sameas(value, other)¶ Check if an object points to the same memory address than another object
  • undefined(value)¶ Like defined() but the other way round.
  • A joiner is passed a string and will return that string every time it’s called, except the first time (in which case it returns an empty string).
  • namespace(...)¶ Creates a new container that allows attribute assignment using the {% set %} tag
  • The with statement makes it possible to create a new inner scope. Variables set within this scope are not visible outside of the scope.
  • activate and deactivate the autoescaping from within the templates
  • With both trim_blocks and lstrip_blocks enabled, you can put block tags on their own lines, and the entire block line will be removed when rendered, preserving the whitespace of the contents
張 旭

Replication - Redis - 0 views

  • leader follower (master-slave) replication
  • slave Redis instances to be exact copies of master instances.
  • The slave will automatically reconnect to the master every time the link breaks, and will attempt to be an exact copy of it regardless of what happens to the master.
  • ...2 more annotations...
  • the master keeps the slave updated by sending a stream of commands to the slave
  • When a partial resynchronization is not possible, the slave will ask for a full resynchronization.
張 旭

Auto DevOps | GitLab - 0 views

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

Incremental Backup - 0 views

  • xtrabackup supports incremental backups, which means that they can copy only the data that has changed since the last backup.
  • You can perform many incremental backups between each full backup, so you can set up a backup process such as a full backup once a week and an incremental backup every day, or full backups every day and incremental backups every hour.
  • each InnoDB page contains a log sequence number, or LSN. The LSN is the system version number for the entire database. Each page’s LSN shows how recently it was changed.
  • ...18 more annotations...
  • In full backups, two types of operations are performed to make the database consistent: committed transactions are replayed from the log file against the data files, and uncommitted transactions are rolled back.
  • You should use the --apply-log-only option to prevent the rollback phase.
  • An incremental backup copies each page whose LSN is newer than the previous incremental or full backup’s LSN.
  • Incremental backups do not actually compare the data files to the previous backup’s data files.
  • you can use --incremental-lsn to perform an incremental backup without even having the previous backup, if you know its LSN
  • Incremental backups simply read the pages and compare their LSN to the last backup’s LSN.
  • without a full backup to act as a base, the incremental backups are useless.
  • The xtrabackup binary writes a file called xtrabackup_checkpoints into the backup’s target directory. This file contains a line showing the to_lsn, which is the database’s LSN at the end of the backup.
  • from_lsn is the starting LSN of the backup and for incremental it has to be the same as to_lsn (if it is the last checkpoint) of the previous/base backup.
  • If you do not use the --apply-log-only option to prevent the rollback phase, then your incremental backups will be useless.
  • run --prepare as usual, but prevent the rollback phase
  • If you restore it and start MySQL, InnoDB will detect that the rollback phase was not performed, and it will do that in the background, as it usually does for a crash recovery upon start.
  • xtrabackup --prepare --apply-log-only --target-dir=/data/backups/base \ --incremental-dir=/data/backups/inc1
  • The final data is in /data/backups/base, not in the incremental directory.
  • Do not run xtrabackup --prepare with the same incremental backup directory (the value of –incremental-dir) more than once.
  • xtrabackup --prepare --target-dir=/data/backups/base \ --incremental-dir=/data/backups/inc2
  • --apply-log-only should be used when merging all incrementals except the last one.
  • Even if the --apply-log-only was used on the last step, backup would still be consistent but in that case server would perform the rollback phase.
張 旭

Replication - MongoDB Manual - 0 views

  • A replica set in MongoDB is a group of mongod processes that maintain the same data set.
  • Replica sets provide redundancy and high availability, and are the basis for all production deployments.
  • With multiple copies of data on different database servers, replication provides a level of fault tolerance against the loss of a single database server.
  • ...18 more annotations...
  • replication can provide increased read capacity as clients can send read operations to different servers.
  • A replica set is a group of mongod instances that maintain the same data set.
  • A replica set contains several data bearing nodes and optionally one arbiter node.
  • one and only one member is deemed the primary node, while the other nodes are deemed secondary nodes.
  • A replica set can have only one primary capable of confirming writes with { w: "majority" } write concern; although in some circumstances, another mongod instance may transiently believe itself to also be primary.
  • The secondaries replicate the primary’s oplog and apply the operations to their data sets such that the secondaries’ data sets reflect the primary’s data set
  • add a mongod instance to a replica set as an arbiter. An arbiter participates in elections but does not hold data
  • An arbiter will always be an arbiter whereas a primary may step down and become a secondary and a secondary may become the primary during an election.
  • Secondaries replicate the primary’s oplog and apply the operations to their data sets asynchronously.
  • These slow oplog messages are logged for the secondaries in the diagnostic log under the REPL component with the text applied op: <oplog entry> took <num>ms.
  • Replication lag refers to the amount of time that it takes to copy (i.e. replicate) a write operation on the primary to a secondary.
  • When a primary does not communicate with the other members of the set for more than the configured electionTimeoutMillis period (10 seconds by default), an eligible secondary calls for an election to nominate itself as the new primary.
  • The replica set cannot process write operations until the election completes successfully.
  • The median time before a cluster elects a new primary should not typically exceed 12 seconds, assuming default replica configuration settings.
  • Factors such as network latency may extend the time required for replica set elections to complete, which in turn affects the amount of time your cluster may operate without a primary.
  • Your application connection logic should include tolerance for automatic failovers and the subsequent elections.
  • MongoDB drivers can detect the loss of the primary and automatically retry certain write operations a single time, providing additional built-in handling of automatic failovers and elections
  • By default, clients read from the primary [1]; however, clients can specify a read preference to send read operations to secondaries.
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