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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.
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

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

  • Storage(儲存) 實際上一直都不是一個簡單處理的問題,從軟體面來看實際上牽扯到非常多的層級,譬如 Linux Kernel, FileSystem, Block/File-Level, Cache, Snapshot, Object Storage 等各式各樣的議題可以討論。
  • DRBD
  • 異地備援,容錯機制,快照,重複資料刪除等超多相關的議題基本上從來沒有一個完美的解法能夠滿足所有使用情境。
  • ...20 more annotations...
  • 管理者可能會直接在 NFS Server 上進行 MDADM 來設定相關的 Block Device 並且基於上面提供 Export 供 NFS 使用,甚至底層套用不同的檔案系統 (EXT4/BTF4) 來獲取不同的功能與效能。
  • Kubernetes 就只是 NFS Client 的角色
  • CSI(Container Storage Interface)。CSI 本身作為 Kubernetes 與 Storage Solution 的中介層。
  • 基本上 Pod 裡面每個 Container 會使用 Volume 這個物件來代表容器內的掛載點,而在外部實際上會透過 PVC 以及 PV 的方式來描述這個 Volume 背後的儲存方案伺服器的資訊。
  • 整體會透過 CSI 的元件們與最外面實際上的儲存設備連接,所有儲存相關的功能是否有實現,有支援全部都要仰賴最後面的實際提供者, kubernetes 只透過 CSI 的標準去執行。
  • 在網路部分也有與之對應的 CNI(Container Network Interface). kubernetes 透過 CNI 這個介面來與後方的 網路解決方案 溝通
  • CNI 最基本的要求就是在在對應的階段為對應的容器提供網路能力
  • 目前最常見也是 IPv4 + TCP/UDP 的傳輸方式,因此才會看到大部分的 CNI 都在講這些。
  • 希望所有容器彼此之間可以透過 IPv4 來互相存取彼此,不論是同節點或是跨節點的容器們都要可以滿足這個需求。
  • 容器間到底怎麼傳輸的,需不需要封裝,透過什麼網卡,要不要透過 NAT 處理? 這一切都是 CNI 介面背後的實現
  • 外部網路存取容器服務 (Service/Ingress)
  • kubernetes 在 Service/Ingress 中間自行實現了一個模組,大抵上稱為 kube-proxy, 其底層可以使用 iptables, IPVS, user-space software 等不同的實現方法,這部分是跟 CNI 完全無關。
  • CNI 跟 Service/Ingress 是會衝突的,也有可能彼此沒有配合,這中間沒有絕對的穩定整合。
  • CNI 一般會處理的部份,包含了容器內的 網卡數量,網卡名稱,網卡IP, 以及容器與外部節點的連接能力等
  • CRI (Container Runtime Interface) 或是 Device Plugin
  • 對於 kubernetes 來說,其實本身並不在意到底底下的容器化技術實際上是怎麼實現的,你要用 Docker, rkt, CRI-O 都無所謂,甚至背後是一個偽裝成 Container 的 Virtaul Machine virtlet 都可以。
  • 去思考到底為什麼自己本身的服務需要容器化,容器化可以帶來什麼優點
  • 太多太多的人都認為只要寫一個 Dockerfile 將原先的應用程式們全部包裝起來放在一起就是一個很好的容器 來使用了。
  • 最後就會發現根本把 Container 當作 Virtual Machine 來使用,然後再補一句 Contaienr 根本不好用啊
  • 容器化 不是把直接 Virtual Machine 的使用習慣換個環境使用就叫做 容器化,而是要從概念上去暸解與使用
張 旭

HTTPS 升级指南 - 阮一峰的网络日志 - 0 views

  • 域名认证(Domain Validation):最低级别认证,可以确认申请人拥有这个域名。
  • 公司认证(Company Validation):确认域名所有人是哪一家公司,证书里面会包含公司信息。
  • 扩展认证(Extended Validation):最高级别的认证,浏览器地址栏会显示公司名。
  • ...8 more annotations...
  • 多域名
  • 单域名
  • 通配符
  • 网站的响应头里面,加入一个强制性声明
  • Strict-Transport-Security: max-age=31536000; includeSubDomains
  • 确保浏览器只在使用 HTTPS 时,才发送Cookie。
  • Set-Cookie:
  • ; Secure
張 旭

SSL Certificate Features - 0 views

  • A certificate authority issues certificates in the form of a tree structure.
  • All certificates below the root certificate inherit the trustworthiness of the root certificate.
  • Any certificate signed by a trusted root certificate will also be trusted.
  • ...9 more annotations...
  • the browser has all of the certificates in the chain to link it up to a trusted root certificate.
  • Any certificate in between your certificate and the root certificate is called a chain or intermediate certificate.
  • These must be installed to the web server with the primary certificate for your web site so that user's browers can link your certificate to a trusted authority.
  • Chain Certificate
  • Intermediate Certificate
  • Root Certificate
  • EV (Extended Validation) certificate
  • wildcard certificate
  • domain-validated certificate
  •  
    "A certificate authority issues certificates in the form of a tree structure."
張 旭

Ruby on Rails 實戰聖經 | 網站效能 - 0 views

  • 依照慣例是_count結尾,型別是integer,有預設值0。
  • lol_dba提供了Rake任務可以幫忙找忘記加的索引。
  • Bullet是一個外掛可以在開發時偵測N+1 queries問題。
  • ...19 more annotations...
  • 存取資料庫是一種相對很慢的I/O的操作:每一條SQL query都得耗上時間、執行回傳的結果也會被轉成ActiveRecord物件全部放進記憶體
  • 如果需要撈出全部的資料做處理,強烈建議最好不要用all方法,因為這樣會把全部的資料一次放進記憶體中,如果資料有成千上萬筆的話,效能就墜毀了。
  • .find_each( :batch_size => 100 )
  • .find_in_batches( :batch_size => 100 )
  • 在Transaction交易範圍內的SQL效能會加快,因為最後只需要COMMIT一次即可
  • Elasticsearch全文搜尋引擎和elasticsearch-rails gem
  • QueryReviewer這個套件透過SQL EXPLAIN分析SQL query的效率
  • 必要時可以採用逆正規化的設計。犧牲空間,增加修改的麻煩,但是讓讀取這事件變得更快更簡單。
  • 將成本轉嫁到寫入,而最佳化了讀取時間
  • 在效能還沒有造成問題前,就為了優化效能而修改程式和架構,只會讓程式更混亂不好維護
  • 當效能還不會造成問題時,程式的維護性比考慮效能重要
  • 會拖慢整體效能的程式,只佔全部程式的一小部分而已,所以我們只最佳化會造成問題的程式。
  • 善用分析工具找效能瓶頸,最佳化前需要測量,最佳化後也要測量比較。
  • rack-mini-profiler在頁面的左上角顯示花了多少時間,並且提供報表,推薦安裝
  • 如果是不需要權限控管的靜態檔案,可以直接放在public目錄下讓使用者下載。
  • Web伺服器得先安裝好x_sendfile功能
  • 如果要讓你的Assets例如CSS, JavaScript, Images也讓使用者透過CDN下載,只要修改config/environments/production.rb的config.action_controller.asset_host為CDN網址即可。
  • 有時候「執行速度較快」的程式碼不代表好維護、好除錯的程式碼
  • Ruby不是萬能,有時候直接呼叫外部程式是最快的作法
張 旭

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

  • 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.
  •  
    "Persistent volumes exist beyond containers, pods, and nodes. "
張 旭

Introduction to GitLab Flow | GitLab - 0 views

  • Git allows a wide variety of branching strategies and workflows.
  • not integrated with issue tracking systems
  • The biggest problem is that many long-running branches emerge that all contain part of the changes.
  • ...47 more annotations...
  • most organizations practice continuous delivery, which means that your default branch can be deployed.
  • Merging everything into the master branch and frequently deploying means you minimize the amount of unreleased code, which is in line with lean and continuous delivery best practices.
  • you can deploy to production every time you merge a feature branch.
  • deploy a new version by merging master into the production branch.
  • you can have your deployment script create a tag on each deployment.
  • to have an environment that is automatically updated to the master branch
  • commits only flow downstream, ensures that everything is tested in all environments.
  • first merge these bug fixes into master, and then cherry-pick them into the release branch.
  • Merging into master and then cherry-picking into release is called an “upstream first” policy
  • “merge request” since the final action is to merge the feature branch.
  • “pull request” since the first manual action is to pull the feature branch
  • it is common to protect the long-lived branches
  • After you merge a feature branch, you should remove it from the source control software
  • When you are ready to code, create a branch for the issue from the master branch. This branch is the place for any work related to this change.
  • A merge request is an online place to discuss the change and review the code.
  • If you open the merge request but do not assign it to anyone, it is a “Work In Progress” merge request.
  • Start the title of the merge request with “[WIP]” or “WIP:” to prevent it from being merged before it’s ready.
  • To automatically close linked issues, mention them with the words “fixes” or “closes,” for example, “fixes #14” or “closes #67.” GitLab closes these issues when the code is merged into the default branch.
  • If you have an issue that spans across multiple repositories, create an issue for each repository and link all issues to a parent issue.
  • With Git, you can use an interactive rebase (rebase -i) to squash multiple commits into one or reorder them.
  • you should never rebase commits you have pushed to a remote server.
  • Rebasing creates new commits for all your changes, which can cause confusion because the same change would have multiple identifiers.
  • if someone has already reviewed your code, rebasing makes it hard to tell what changed since the last review.
  • never rebase commits authored by other people.
  • it is a bad idea to rebase commits that you have already pushed.
  • always use the “no fast-forward” (--no-ff) strategy when you merge manually.
  • you should try to avoid merge commits in feature branches
  • people avoid merge commits by just using rebase to reorder their commits after the commits on the master branch. Using rebase prevents a merge commit when merging master into your feature branch, and it creates a neat linear history.
  • you should never rebase commits you have pushed to a remote server
  • Sometimes you can reuse recorded resolutions (rerere), but merging is better since you only have to resolve conflicts once.
  • not frequently merge master into the feature branch.
  • utilizing new code,
  • resolving merge conflicts
  • updating long-running branches.
  • just cherry-picking a commit.
  • If your feature branch has a merge conflict, creating a merge commit is a standard way of solving this.
  • keep your feature branches short-lived.
  • split your features into smaller units of work
  • you should try to prevent merge commits, but not eliminate them.
  • Your codebase should be clean, but your history should represent what actually happened.
  • Splitting up work into individual commits provides context for developers looking at your code later.
  • push your feature branch frequently, even when it is not yet ready for review.
  • Commit often and push frequently
  • A commit message should reflect your intention, not just the contents of the commit.
  • Testing before merging
  • When using GitLab flow, developers create their branches from this master branch, so it is essential that it never breaks. Therefore, each merge request must be tested before it is accepted.
  • When creating a feature branch, always branch from an up-to-date master
  •  
    "Git allows a wide variety of branching strategies and workflows."
張 旭

vSphere Storage for Kubernetes | vSphere Storage for Kubernetes - 0 views

  • Containers are ephemeral by nature
  • stateful applications
  • When containers are re-scheduled, they can die on one host and might get scheduled on a different host.
  • ...3 more annotations...
  • the storage should also be shifted and made available on the new host for the container to start gracefully.
  • The underlying infrastructure should handle the complexity of unmounting and mounting.
  • Kubernetes provides abstractions to ensure that the storage details are separated from allocation and usage of storage.
張 旭

Dynamic Provisioning | vSphere Storage for Kubernetes - 0 views

  • Storage Policy based Management (SPBM). SPBM provides a single unified control plane across a broad range of data services and storage solutions
  • Kubernetes StorageClasses allow the creation of PersistentVolumes on-demand without having to create storage and mount it into K8s nodes upfront
  • When a PVC is created, the PersistentVolume will be provisioned on a compatible datastore with the most free space that satisfies the gold storage policy requirements.
  • ...2 more annotations...
  • When a PVC is created, the vSphere Cloud Provider checks if the user specified datastore satisfies the gold storage policy requirements. If it does, the vSphere Cloud Provider will provision the PersistentVolume on the user specified datastore. If not, it will create an error telling the user that the specified datastore is not compatible with gold storage policy requirements.
  • The Kubernetes user will have the ability to specify custom vSAN Storage Capabilities during dynamic volume provisioning.
  •  
    "Storage Policy based Management (SPBM). SPBM provides a single unified control plane across a broad range of data services and storage solutions"
張 旭

vSphere Cloud Provider | vSphere Storage for Kubernetes - 0 views

  • Containers are stateless and ephemeral but applications are stateful and need persistent storage.
  • Cloud Provider
  • Kubernetes cloud providers are an interface to integrate various node (i.e. hosts), load balancers and networking routes
  • ...8 more annotations...
  • VMware offers a Cloud Provider known as the vSphere Cloud Provider (VCP) for Kubernetes which allows Pods to use enterprise grade persistent storage.
  • A vSphere datastore is an abstraction which hides storage details (such as LUNs) and provides a uniform interface for storing persistent data.
  • the datastores can be of the type vSAN, VMFS, NFS & VVol.
  • VMFS (Virtual Machine File System) is a cluster file system that allows virtualization to scale beyond a single node for multiple VMware ESX servers.
  • NFS (Network File System) is a distributed file protocol to access storage over network like local storage.
  • vSphere Cloud Provider supports every storage primitive exposed by Kubernetes
  • Kubernetes PVs are defined in Pod specifications.
  • PVCs when using Dynamic Provisioning (preferred).
張 旭

Modules - Configuration Language - Terraform by HashiCorp - 0 views

  • provider blocks can appear in any module, it is recommended that they be placed only in the root module of a configuration
  • In all cases it is recommended to keep explicit provider configurations only in the root module and pass them (whether implicitly or explicitly) down to descendent modules
  • Provider configurations are used for all operations on associated resources, including destroying remote objects and refreshing state.
  • ...5 more annotations...
  • all resources created for a particular provider configuration must be destroyed before that provider configuration is removed, unless the related resources are re-configured to use a different provider configuration first.
  • a child module automatically inherits default (un-aliased) provider configurations from its parent.
  • recommended in the common case where only a single configuration is needed for each provider across the entire configuration.
  • the providers argument within a module block can be used to define explicitly which provider configs are made available to the child module.
  • Once the providers argument is used in a module block, it overrides all of the default inheritance behavior, so it is necessary to enumerate mappings for all of the required providers.
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