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張 旭

Handling Arguments in Bash Scripts - DEV Community - 0 views

  • positional arguments. They hold the arguments given after your script as it was run on the command line
  • $0: The Script Name
  • $#: Argument Count
  • ...2 more annotations...
  • $?: Most Recent Exit Code
  • When you quote $*, it will output all of the arguments received as one single string, separated by a space1 regardless of how they were quoted going in, but it will quote that string so that it doesn't get split up later.
  •  
    "positional arguments. They hold the arguments given after your script as it was run on the command line"
張 旭

Bash If Statements: Beginner to Advanced - DEV Community - 0 views

  • "[" is a command. It's actually syntactic sugar for the built-in command test which checks and compares its arguments. The "]" is actually an argument to the [ command that tells it to stop checking for arguments!
  • why > and < get weird inside single square brackets -- Bash actually thinks you're trying to do an input or output redirect inside a command!
  • the [[ double square brackets ]] and (( double parens )) are not exactly commands. They're actually Bash language keywords, which is what makes them behave a little more predictably.
  • ...8 more annotations...
  • The [[ double square brackets ]] work essentially the same as [ single square brackets ], albeit with some more superpowers like more powerful regex support.
  • The (( double parentheses )) are actually a construct that allow arithmetic inside Bash.
  • If the results inside are zero, it returns an exit code of 1. (Essentially, zero is "falsey.")
  • the greater and less-than symbols work just fine inside arithmetic parens.
  • exit code 0 for success.
  • exit code 1 for failure.
  • If the regex works out, the return code of the double square brackets is 0, and thus the function returns 0. If not, everything returns 1. This is a really great way to name regexes.
  • the stuff immediately after the if can be any command in the whole wide world, as long as it provides an exit code, which is pretty much always.
  •  
    ""[" is a command. It's actually syntactic sugar for the built-in command test which checks and compares its arguments. The "]" is actually an argument to the [ command that tells it to stop checking for arguments!"
crazylion lee

實戰篇-打造人性化 Telegram Bot - zaoldyeck - Medium - 0 views

  •  
    "Telegram Bot"
crazylion lee

FreeOTP - 0 views

shared by crazylion lee on 11 Mar 19 - No Cached
crazylion lee

GitHub - arminc/clair-scanner: Docker containers vulnerability scan - 0 views

  •  
    "Docker containers vulnerability scan"
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
chiehting

Top 5 Kubernetes Best Practices From Sandeep Dinesh (Google) - DZone Cloud - 0 views

  • Best Practices for Kubernetes
  • #1: Building Containers
  • Don’t Trust Arbitrary Base Images!
  • ...29 more annotations...
  • There’s a lot wrong with this: you could be using the wrong version of code that has exploits, has a bug in it, or worse it could have malware bundled in on purpose—you just don’t know.
  • Keep Base Images Small
  • Node.js for example, it includes an extra 600MB of libraries you don’t need.
  • Use the Builder Pattern
  • #2: Container Internals
  • Use a Non-Root User Inside the Container
  • Make the File System Read-Only
  • One Process per Container
  • Don’t Restart on Failure. Crash Cleanly Instead.
  • Log Everything to stdout and stderr
  • #3: Deployments
  • Use the “Record” Option for Easier Rollbacks
  • Use Weave Cloud
  • Use Sidecars for Proxies, Watchers, Etc.
  • Don’t Use Sidecars for Bootstrapping!
  • Don’t Use :Latest or No Tag
  • Readiness and Liveness Probes are Your Friend
  • #4: Services
  • Don’t Use type: LoadBalancer
  • Type: Nodeport Can Be “Good Enough”
  • Use Static IPs They Are Free!
  • Map External Services to Internal Ones
  • #5: Application Architecture
  • Use Helm Charts
  • All Downstream Dependencies Are Unreliable
  • Use Plenty of Descriptive Labels
  • Make Sure Your Microservices Aren’t Too Micro
  • Use Namespaces to Split Up Your Cluster
  • Role-Based Access Control
張 旭

Queues - Laravel - The PHP Framework For Web Artisans - 0 views

  • Laravel queues provide a unified API across a variety of different queue backends, such as Beanstalk, Amazon SQS, Redis, or even a relational database.
  • The queue configuration file is stored in config/queue.php
  • a synchronous driver that will execute jobs immediately (for local use)
  • ...56 more annotations...
  • A null queue driver is also included which discards queued jobs.
  • In your config/queue.php configuration file, there is a connections configuration option.
  • any given queue connection may have multiple "queues" which may be thought of as different stacks or piles of queued jobs.
  • each connection configuration example in the queue configuration file contains a queue attribute.
  • if you dispatch a job without explicitly defining which queue it should be dispatched to, the job will be placed on the queue that is defined in the queue attribute of the connection configuration
  • pushing jobs to multiple queues can be especially useful for applications that wish to prioritize or segment how jobs are processed
  • specify which queues it should process by priority.
  • If your Redis queue connection uses a Redis Cluster, your queue names must contain a key hash tag.
  • ensure all of the Redis keys for a given queue are placed into the same hash slot
  • all of the queueable jobs for your application are stored in the app/Jobs directory.
  • Job classes are very simple, normally containing only a handle method which is called when the job is processed by the queue.
  • we were able to pass an Eloquent model directly into the queued job's constructor. Because of the SerializesModels trait that the job is using, Eloquent models will be gracefully serialized and unserialized when the job is processing.
  • When the job is actually handled, the queue system will automatically re-retrieve the full model instance from the database.
  • The handle method is called when the job is processed by the queue
  • The arguments passed to the dispatch method will be given to the job's constructor
  • delay the execution of a queued job, you may use the delay method when dispatching a job.
  • dispatch a job immediately (synchronously), you may use the dispatchNow method.
  • When using this method, the job will not be queued and will be run immediately within the current process
  • specify a list of queued jobs that should be run in sequence.
  • Deleting jobs using the $this->delete() method will not prevent chained jobs from being processed. The chain will only stop executing if a job in the chain fails.
  • this does not push jobs to different queue "connections" as defined by your queue configuration file, but only to specific queues within a single connection.
  • To specify the queue, use the onQueue method when dispatching the job
  • To specify the connection, use the onConnection method when dispatching the job
  • defining the maximum number of attempts on the job class itself.
  • to defining how many times a job may be attempted before it fails, you may define a time at which the job should timeout.
  • using the funnel method, you may limit jobs of a given type to only be processed by one worker at a time
  • using the throttle method, you may throttle a given type of job to only run 10 times every 60 seconds.
  • If an exception is thrown while the job is being processed, the job will automatically be released back onto the queue so it may be attempted again.
  • dispatch a Closure. This is great for quick, simple tasks that need to be executed outside of the current request cycle
  • When dispatching Closures to the queue, the Closure's code contents is cryptographically signed so it can not be modified in transit.
  • Laravel includes a queue worker that will process new jobs as they are pushed onto the queue.
  • once the queue:work command has started, it will continue to run until it is manually stopped or you close your terminal
  • queue workers are long-lived processes and store the booted application state in memory.
  • they will not notice changes in your code base after they have been started.
  • during your deployment process, be sure to restart your queue workers.
  • customize your queue worker even further by only processing particular queues for a given connection
  • The --once option may be used to instruct the worker to only process a single job from the queue
  • The --stop-when-empty option may be used to instruct the worker to process all jobs and then exit gracefully.
  • Daemon queue workers do not "reboot" the framework before processing each job.
  • you should free any heavy resources after each job completes.
  • Since queue workers are long-lived processes, they will not pick up changes to your code without being restarted.
  • restart the workers during your deployment process.
  • php artisan queue:restart
  • The queue uses the cache to store restart signals
  • the queue workers will die when the queue:restart command is executed, you should be running a process manager such as Supervisor to automatically restart the queue workers.
  • each queue connection defines a retry_after option. This option specifies how many seconds the queue connection should wait before retrying a job that is being processed.
  • The --timeout option specifies how long the Laravel queue master process will wait before killing off a child queue worker that is processing a job.
  • When jobs are available on the queue, the worker will keep processing jobs with no delay in between them.
  • While sleeping, the worker will not process any new jobs - the jobs will be processed after the worker wakes up again
  • the numprocs directive will instruct Supervisor to run 8 queue:work processes and monitor all of them, automatically restarting them if they fail.
  • Laravel includes a convenient way to specify the maximum number of times a job should be attempted.
  • define a failed method directly on your job class, allowing you to perform job specific clean-up when a failure occurs.
  • a great opportunity to notify your team via email or Slack.
  • php artisan queue:retry all
  • php artisan queue:flush
  • When injecting an Eloquent model into a job, it is automatically serialized before being placed on the queue and restored when the job is processed
張 旭

Queue Workers: How they work - Diving Laravel - 0 views

  • define workers as a simple PHP process that runs in the background with the purpose of extracting jobs from a storage space and run them with respect to several configuration options.
  • have to manually restart the worker to reflect any code change you made in your application.
  • avoiding booting up the whole app on every job
  • ...7 more annotations...
  • instruct Laravel to create an instance of your application and start executing jobs, this instance will stay alive indefinitely which means the action of starting your Laravel application happens only once when the command was run & the same instance will be used to execute your jobs
  • This will start an instance of the application, process a single job,
  • and then kill the script.
  • Using queue:listen ensures that a new instance of the app is created for every job, that means you don't have to manually restart the worker in case you made changes to your code, but also means more server resources will be consumed.
  • the queue:listen command runs the WorkCommand inside a loop
  • The connection this worker will be pulling jobs from
  • The queue the worker will use to find jobs
  •  
    "define workers as a simple PHP process that runs in the background with the purpose of extracting jobs from a storage space and run them with respect to several configuration options."
張 旭

Introduction To The Queue System - Diving Laravel - 0 views

  • Laravel is shipped with a built-in queue system that helps you run tasks in the background
  • The QueueManager is registered into the container and it knows how to connect to the different built-in queue drivers
  • for example when we called the Queue::push() method, what happened is that the manager selected the desired queue driver, connected to it, and called the push method on that driver.
  • ...2 more annotations...
  • All calls to methods that don't exist in the QueueManager class will be sent to the loaded driver
  • when you do Queue::push() you're actually calling the push method on the queue driver you're using
  •  
    "Laravel is shipped with a built-in queue system that helps you run tasks in the background "
張 旭

DevOps - 0 views

  • 对于运维来说,知识的传承非常重要,非常有必要建立运维的知识库。一方面 有利于对事件的复盘回顾,另一方面也有助于日后参加运维的人员尽快熟悉与掌握系统的运维技能
  • 云平台主要从以下3个方面对DevOps提供支撑(括号内为承载此能力的软件工具): 1. 基于IaaS的自服务与环境编排能力(VMWare) 2. 基于PaaS的弹性伸缩能力(K8s) 3. 基于SaaS的软件服务能力
  • 考虑自建私有云,至少是混合云。
  • ...11 more annotations...
  • 内网建立所谓的私库,作为代理与外网的公共库同步。
  • 很难做到真正意义上的DevOps to Production
  • 可视化是为了实时展现持续交付流水线执行情况与单元测试的执行报告
  • 通过持续交付流水线串联自动化测试,在测试环境部署成功后触发自动化测试。
  • 测试阶段也需要测试报告的可视化与结果通知
  • 企业的持续交付流水线往往都打不通到生产环境
  • Service Desk不是某一款软件的名字,而是ITIL(信息技术基础架构库,可认为是ITSM的落地实现)里面承载变更管理与事件管理的工具统称。
  • 构建底层的云平台,是整个DevOps基础架构的基石
  • 架构不是一成不变的,而是应该随着实际需求变化而持续演化,能力也要跟着持续提升。
  • 并行测试的执行环境通过PaaS平台按需自动生成,测试执行完毕后自动销毁。
  • 即使是雷同的项目,在对编译构建上的一些细枝末节的差别也很可能导致它们的持续交付流水线设计非常不一样。
  •  
    "对于运维来说,知识的传承非常重要,非常有必要建立运维的知识库。一方面 有利于对事件的复盘回顾,另一方面也有助于日后参加运维的人员尽快熟悉与掌握系统的运维技能。"
張 旭

Scalable architecture without magic (and how to build it if you're not Google) - DEV Co... - 0 views

  • Don’t mess up write-first and read-first databases.
  • keep them stateless.
  • you should know how to make a scalable setup on bare metal.
  • ...29 more annotations...
  • Different programming languages are for different tasks.
  • Go or C which are compiled to run on bare metal.
  • To run NodeJS on multiple cores, you have to use something like PM2, but since this you have to keep your code stateless.
  • Python have very rich and sugary syntax that’s great for working with data while keeping your code small and expressive.
  • SQL is almost always slower than NoSQL
  • databases are often read-first or write-first
  • write-first, just like Cassandra.
  • store all of your data to your databases and leave nothing at backend
  • Functional code is stateless by default
  • It’s better to go for stateless right from the very beginning.
  • deliver exactly the same responses for same requests.
  • Sessions? Store them at Redis and allow all of your servers to access it.
  • Only the first user will trigger a data query, and all others will be receiving exactly the same data straight from the RAM
  • never, never cache user input
  • Only the server output should be cached
  • Varnish is a great cache option that works with HTTP responses, so it may work with any backend.
  • a rate limiter – if there’s not enough time have passed since last request, the ongoing request will be denied.
  • different requests blasting every 10ms can bring your server down
  • Just set up entry relations and allow your database to calculate external keys for you
  • the query planner will always be faster than your backend.
  • Backend should have different responsibilities: hashing, building web pages from data and templates, managing sessions and so on.
  • For anything related to data management or data models, move it to your database as procedures or queries.
  • a distributed database.
  • your code has to be stateless
  • Move anything related to the data to the database.
  • For load-balancing a database, go for cluster.
  • DB is balancing requests, as well as your backend.
  • Users from different continents are separated with DNS.
  • Keep is scalable, keep is stateless.
  •  
    "Don't mess up write-first and read-first databases."
張 旭

The Twelve-Factor App - 0 views

  • The process formation is the array of processes that are used to do the app’s regular business
  • one-off administrative or maintenance tasks for the app
  • One-off admin processes should be run in an identical environment as the regular long-running processes of the app.
  • ...2 more annotations...
  • Admin code must ship with application code to avoid synchronization issues.
  • Twelve-factor strongly favors languages which provide a REPL shell out of the box, and which make it easy to run one-off scripts.
張 旭

The Twelve-Factor App - 0 views

  • Logs are the stream of aggregated, time-ordered events collected from the output streams of all running processes and backing services.
  • Logs have no fixed beginning or end, but flow continuously as long as the app is operating.
  • each running process writes its event stream, unbuffered, to stdout.
  • ...2 more annotations...
  • long-term archival. These archival destinations are not visible to or configurable by the app, and instead are completely managed by the execution environment.
  • Most significantly, the stream can be sent to a log indexing and analysis system such as Splunk, or a general-purpose data warehousing system such as Hadoop/Hive.
張 旭

The Twelve-Factor App - 0 views

  • Keep development, staging, and production as similar as possible
  • Developers write code, ops engineers deploy it.
  • The twelve-factor app is designed for continuous deployment by keeping the gap between development and production small
  • ...4 more annotations...
  • Backing services, such as the app’s database, queueing system, or cache, is one area where dev/prod parity is important
  • The twelve-factor developer resists the urge to use different backing services between development and production, even when adapters theoretically abstract away any differences in backing services.
  • declarative provisioning tools such as Chef and Puppet combined with light-weight virtual environments such as Docker and Vagrant allow developers to run local environments which closely approximate production environments.
  • all deploys of the app (developer environments, staging, production) should be using the same type and version of each of the backing services.
  •  
    "as similar as possible "
張 旭

The Twelve-Factor App - 0 views

  • they can be started or stopped at a moment’s notice.
  • Processes should strive to minimize startup time
  • Processes shut down gracefully when they receive a SIGTERM signal from the process manager.
  • ...4 more annotations...
  • returning the current job to the work queue
  • all jobs are reentrant, which typically is achieved by wrapping the results in a transaction, or making the operation idempotent
  • Processes should also be robust against sudden death, in the case of a failure in the underlying hardware.
  • a twelve-factor app is architected to handle unexpected, non-graceful terminations
張 旭

The Twelve-Factor App - 0 views

  • PHP processes run as child processes of Apache, started on demand as needed by request volume.
  • Java processes take the opposite approach, with the JVM providing one massive uberprocess that reserves a large block of system resources (CPU and memory) on startup, with concurrency managed internally via threads
  • Processes in the twelve-factor app take strong cues from the unix process model for running service daemons.
  • ...3 more annotations...
  • application must also be able to span multiple processes running on multiple physical machines.
  • The array of process types and number of processes of each type is known as the process formation.
  • Twelve-factor app processes should never daemonize or write PID files.
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