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張 旭

architecture - Difference between a "coroutine" and a "thread"? - Stack Overflow - 0 views

  • Co stands for cooperation. A co routine is asked to (or better expected to) willingly suspend its execution to give other co-routines a chance to execute too. So a co-routine is about sharing CPU resources (willingly) so others can use the same resource as oneself is using.
  • A thread on the other hand does not need to suspend its execution. Being suspended is completely transparent to the thread and the thread is forced by underlying hardware to suspend itself.
  • co-routines can not be concurrently executed and race conditions can not occur.
  • ...8 more annotations...
  • Concurrency is the separation of tasks to provide interleaved execution.
  • Parallelism is the simultaneous execution of multiple pieces of work in order to increase speed.
  • With threads, the operating system switches running threads preemptively according to its scheduler, which is an algorithm in the operating system kernel.
  • With coroutines, the programmer and programming language determine when to switch coroutines
  • In contrast to threads, which are pre-emptively scheduled by the operating system, coroutine switches are cooperative, meaning the programmer (and possibly the programming language and its runtime) controls when a switch will happen.
  • preemption
  • Coroutines are a form of sequential processing: only one is executing at any given time
  • Threads are (at least conceptually) a form of concurrent processing: multiple threads may be executing at any given time.
  •  
    "Co stands for cooperation. A co routine is asked to (or better expected to) willingly suspend its execution to give other co-routines a chance to execute too. So a co-routine is about sharing CPU resources (willingly) so others can use the same resource as oneself is using."
張 旭

kube-proxy | Kubernetes - 0 views

  • The Kubernetes network proxy runs on each node. This reflects services as defined in the Kubernetes API on each node and can do simple TCP, UDP, and SCTP stream forwarding or round robin TCP, UDP, and SCTP forwarding across a set of backends.
  • Service cluster IPs and ports are currently found through Docker-links-compatible environment variables specifying ports opened by the service proxy.
  •  
    "The Kubernetes network proxy runs on each node. This reflects services as defined in the Kubernetes API on each node and can do simple TCP, UDP, and SCTP stream forwarding or round robin TCP, UDP, and SCTP forwarding across a set of backends."
張 旭

20 年軟體工程生涯所學到的 20 件事 (摘譯) - Ant ATField - 0 views

  • 你永遠無法償還所有的技術債、你永遠無法設計出完美的界面、你的測試總是太慢。
  • 這不是一個不把事情做得更好的藉口,而是給你一個視角,不要擔心優雅和完美
  • 有新團隊成員要加入?注意他們在哪裡感到困惑,以及他們問了什麼問題。
  • ...14 more annotations...
  • 軟體是達到目標的手段,而不是目標本身。目標是定向的,但手段要可隨時變通。
  • 不需要維護的程式
  • 10 倍工程師是愚蠢神話。有人能在 1 天內完成另一個有能力、努力工作、有類似經驗的工程師在 2 週內完成的工作,這種想法很愚蠢。
  • 。一個人能夠成為 10 倍工程師的唯一方法,是你把他們和 0.1x 的工程師相比。
  • between a senior engineer and a junior engineer is that they’ve formed opinions about the way things should be
  • 沒有什麼比一個對自己的工具或如何建構軟體沒有意見的資深工程師更讓我擔心了。
  • 如果你正在使用你的工具,而你對它們不愛也不恨,那麼你需要去體驗更多。
  • 你的資料可能會比你的程式長壽。花點精力保持秩序和乾淨
  • 存活下來的老技術是鯊魚,不是恐龍。
  • 軟體工程師應該定期撰寫部落格、日記、文件,總之做任何需要他們保持書面溝通能力之事。
  • 如果你把一個人從他們的工作成果中抽離,他們就會對他們的工作不那麼關心。這也是跨職能團隊運作良好的主要原因,也是 DevOps 變得如此流行的原因。從頭到尾擁有整個過程,並直接負責交付價值。讓一群充滿熱情的人對設計、建構和交付一個軟體 (或任何東西) 擁有完全的自主,這終將發生令人驚奇之事。
  • 面試最好是用來瞭解某人是誰,以及他們對某一專業領域的興趣如何。嘗試找出他們會成為多好的團隊成員是一個沒有結果的努力。
  • 你在建構一個系統的過程中會學到很多東西,你最終會迭代成一個比你當初設計的更好的系統。
  • stop sharpening the saw, and just start cutting shit
張 旭

The package-lock.json file - 0 views

  • You don't commit to Git your node_modules folder, which is generally huge, and when you try to replicate the project on another machine by using the npm install command,
  • Even if a patch or minor release should not introduce breaking changes
  • The package-lock.json sets your currently installed version of each package in stone, and npm will use those exact versions when running npm ci
  • ...1 more annotation...
  • The package-lock.json file needs to be committed to your Git repository
  •  
    "You don't commit to Git your node_modules folder, which is generally huge, and when you try to replicate the project on another machine by using the npm install command,"
張 旭

GoJS - 0 views

shared by 張 旭 on 20 May 22 - No Cached
張 旭

How to Set Up Squid Proxy for Private Connections on Ubuntu 20.04 | DigitalOcean - 0 views

  • it’s a good idea to keep the deny all rule at the bottom of this configuration block.
  •  
    "it's a good idea to keep the deny all rule at the bottom of this configuration block."
張 旭

Using Traefik as a reverse proxy | Blog Eleven Labs - 0 views

  • a proxy is associated with the client(s), while a reverse proxy is associated with the server(s); a reverse proxy is usually an internal-facing proxy used as a ‘front-end’ to control and protect access to a server on a private network.
  • the restart: always instruction will allow our reverse-proxy service to restart automatically, on its own.
  • add an [api] section to enable the dashboard and the API
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  • double the $ symbols in order to escape the $ symbols as it tries to reference a variable.
  • stay consistent with names inside routers and middlewares.
  • providers.file
  • the service name is always in the form of [service name]@[provider
  • write different routing rules for a service and how to generate SSL certificates
  • traefik.http.services.home.loadbalancer.server.port=8123 indicates that the service port I want to expose is 8123.
  •  
    "a proxy is associated with the client(s), while a reverse proxy is associated with the server(s); a reverse proxy is usually an internal-facing proxy used as a 'front-end' to control and protect access to a server on a private network."
張 旭

The Squeaky Blog | Why we don't use a staging environment - 0 views

  • Pre-live environments are never at parity with production
  • multiple people use staging to validate their changes before release.
  • Branches are then constantly out of sync with each other, and problems often surface when you merge, rebase, and backfill hotfixes.
  • ...10 more annotations...
  • Big Bang releases
  • there is a lengthy suite of tests and checks that run before it is deployed to staging. During this period, which could end up being hours, engineers will likely pick up another task. I’ve seen people merge, and then forget that their changes are on staging, more times than I can count.
  • only merge code that is ready to go live
  • written sufficient tests and have validated our changes in development.
  • All branches are cut from main, and all changes get merged back into main.
  • If we ever have an issue in production, we always roll forward.
  • Feature flags can be enabled on a per-user basis so we can monitor performance and gather feedback
  • Experimental features can be enabled by users in their account settings.
  • we have monitoring, logging, and alarms around all of our services. We also blue/green deploy, by draining and replacing a percentage of containers.
  • Dropping your staging environment in favour of true continuous integration and deployment can create a different mindset for shipping software.
  •  
    "Pre-live environments are never at parity with production "
張 旭

Introducing CNAME Flattening: RFC-Compliant CNAMEs at a Domain's Root - 0 views

  • you can now safely use a CNAME record, as opposed to an A record that points to a fixed IP address, as your root record in CloudFlare DNS without triggering a number of edge case error conditions because you’re violating the DNS spec.
  • CNAME Flattening allowed us to use a root domain while still maintaining DNS fault-tolerance across multiple IP addresses.
  • Traditionally, the root record of a domain needed to point to an IP address (known as an A -- for "address" -- Record).
  • ...13 more annotations...
  • WordPlumblr allows its users to use custom domains that point to the WordPlumblr infrastructure
  • A CNAME is an alias. It allows one domain to point to another domain which, eventually if you follow the CNAME chain, will resolve to an A record and IP address.
  • For example, WordPlumblr might have assigned the CNAME 6equj5.wordplumblr.com for Foo.com. Foo.com and the other customers may have all initially resolved, at the end of the CNAME chain, to the same IP address.
  • you usually don't want to address memory directly but, instead, you set up a pointer to a block of memory where you're going to store something. If the operating system needs to move the memory around then it just updates the pointer to point to wherever the chunk of memory has been moved to.
  • CNAMEs work great for subdomains like www.foo.com or blog.foo.com. Unfortunately, they don't work for a naked domain like foo.com itself.
  • the DNS spec enshrined that the root record -- the naked domain without any subdomain -- could not be a CNAME.
  • Technically, the root could be a CNAME but the RFCs state that once a record has a CNAME it can't have any other entries associated with it
  • a way to support a CNAME at the root, but still follow the RFC and return an IP address for any query for the root record.
  • extended our authoritative DNS infrastructure to, in certain cases, act as a kind of DNS resolver.
  • if there's a CNAME at the root, rather than returning that record directly we recurse through the CNAME chain ourselves until we find an A Record.
  • allows the flexibility of having CNAMEs at the root without breaking the DNS specification.
  • We cache the CNAME responses -- respecting the DNS TTLs, just like a recursor should -- which means often we have the answer without having to traverse the chain.
  • CNAME flattening solved email resolution errors for us which was very key.
張 旭

Kubernetes YAML Generator - 0 views

shared by 張 旭 on 24 Mar 22 - No Cached
張 旭

Considerations for large clusters | Kubernetes - 0 views

  • A cluster is a set of nodes (physical or virtual machines) running Kubernetes agents, managed by the control plane.
  • Kubernetes v1.23 supports clusters with up to 5000 nodes.
  • criteria: No more than 110 pods per node No more than 5000 nodes No more than 150000 total pods No more than 300000 total containers
  • ...14 more annotations...
  • In-use IP addresses
  • run one or two control plane instances per failure zone, scaling those instances vertically first and then scaling horizontally after reaching the point of falling returns to (vertical) scale.
  • Kubernetes nodes do not automatically steer traffic towards control-plane endpoints that are in the same failure zone
  • store Event objects in a separate dedicated etcd instance.
  • start and configure additional etcd instance
  • Kubernetes resource limits help to minimize the impact of memory leaks and other ways that pods and containers can impact on other components.
  • Addons' default limits are typically based on data collected from experience running each addon on small or medium Kubernetes clusters.
  • When running on large clusters, addons often consume more of some resources than their default limits.
  • Many addons scale horizontally - you add capacity by running more pods
  • The VerticalPodAutoscaler can run in recommender mode to provide suggested figures for requests and limits.
  • Some addons run as one copy per node, controlled by a DaemonSet: for example, a node-level log aggregator.
  • VerticalPodAutoscaler is a custom resource that you can deploy into your cluster to help you manage resource requests and limits for pods.
  • The cluster autoscaler integrates with a number of cloud providers to help you run the right number of nodes for the level of resource demand in your cluster.
  • The addon resizer helps you in resizing the addons automatically as your cluster's scale changes.
張 旭

Using cache in GitLab CI with Docker-in-Docker | $AYMDEV() - 0 views

  • optimize our images.
  • When you build an image, it is made of multiple layers: we add a layer per instruction.
  • If we build the same image again without modifying any file, Docker will use existing layers rather than re-executing the instructions.
  • ...21 more annotations...
  • an image is made of multiple layers, and we can accelerate its build by using layers cache from the previous image version.
  • by using Docker-in-Docker, we get a fresh Docker instance per job which local registry is empty.
  • docker build --cache-from "$CI_REGISTRY_IMAGE:latest" -t "$CI_REGISTRY_IMAGE:new-tag"
  • But if you maintain a CHANGELOG in this format, and/or your Git tags are also your Docker tags, you can get the previous version and use cache the this image version.
  • script: - export PREVIOUS_VERSION=$(perl -lne 'print "v${1}" if /^##\s\[(\d\.\d\.\d)\]\s-\s\d{4}(?:-\d{2}){2}\s*$/' CHANGELOG.md | sed -n '2 p') - docker build --cache-from "$CI_REGISTRY_IMAGE:$PREVIOUS_VERSION" -t "$CI_REGISTRY_IMAGE:$CI_COMMIT_TAG" -f ./prod.Dockerfile .
  • « Docker layer caching » is enough to optimize the build time.
  • Cache in CI/CD is about saving directories or files across pipelines.
  • We're building a Docker image, dependencies are installed inside a container.We can't cache a dependencies directory if it doesn't exists in the job workspace.
  • Dependencies will always be installed from a container but will be extracted by the GitLab Runner in the job workspace. Our goal is to send the cached version in the build context.
  • We set the directories to cache in the job settings with a key to share the cache per branch and stage.
  • - docker cp app:/var/www/html/vendor/ ./vendor
  • after_script
  • - docker cp app:/var/www/html/node_modules/ ./node_modules
  • To avoid old dependencies to be mixed with the new ones, at the risk of keeping unused dependencies in cache, which would make cache and images heavier.
  • If you need to cache directories in testing jobs, it's easier: use volumes !
  • version your cache keys !
  • sharing Docker image between jobs
  • In every job, we automatically get artifacts from previous stages.
  • docker save $DOCKER_CI_IMAGE | gzip > app.tar.gz
  • I personally use the « push / pull » technique,
  • we docker push after the build, then we docker pull if needed in the next jobs.
張 旭

Docker image building on GitLab CI | $AYMDEV() - 0 views

  • Continuous Integration (or CI) is a practice where you continously test an application to detect errors as soon as possible.
  • Docker is a container technology, many CI tools execute jobs (the tasks of a pipeline) in container to have an isolated environment.
  • Docker in Docker (« DinD » in short) means executing Docker in a Docker container.
  • ...11 more annotations...
  • images are saved in the host registry, we can benefit from Docker layer caching
  • All jobs will share the same environment, if many of them run simultaneously they might get into conflicts.
  • storage management (accumulating images)
  • The Docker socket binding technique means making a volume of /var/run/docker.sock between host and containers.
  • all containers would share the same Docker daemon.
  • Add privileged = true in the [runners.docker] section, the privileged mode is mandatory to use DinD.
  • To avoid that the runner only run one job at a time, change the concurrent value on the first line.
  • To avoid building a Docker image at each job, it can be built in a first job, pushed to the image registry provided by GitLab, and pulled in the next jobs.
  • functional tests depending on a database.
  • Docker Compose allows you to easily start multiple containers, but it has no more feature than Docker itself
  • Docker in Docker works well, but has its drawbacks, like Docker layer caching which needs some more commands to be used.
張 旭

Docker can now run within Docker - Docker Blog - 0 views

  • Docker 0.6 is the new “privileged” mode for containers. It allows you to run some containers with (almost) all the capabilities of their host machine, regarding kernel features and device access.
  • Among the (many!) possibilities of the “privileged” mode, you can now run Docker within Docker itself.
  • in the new privileged mode.
  • ...8 more annotations...
  • that /var/lib/docker should be a volume. This is important, because the filesystem of a container is an AUFS mountpoint, composed of multiple branches; and those branches have to be “normal” filesystems (i.e. not AUFS mountpoints).
  • /var/lib/docker, the place where Docker stores its containers, cannot be an AUFS filesystem.
  • we use them as a pass-through to the “normal” filesystem of the host machine.
  • The /var/lib/docker directory of the nested Docker will live somewhere in /var/lib/docker/volumes on the host system.
  • since the private Docker instances run in privileged mode, they can easily escalate to the host, and you probably don’t want this! If you really want to run something like this and expose it to the public, you will have to fine-tune the LXC template file, to restrict the capabilities and devices available to the Docker instances.
  • When you are inside a privileged container, you can always nest one more level
  • the LXC tools cannot start nested containers if the devices control group is not in its own hierarchy.
  • if you use AppArmor, you need a special policy to support nested containers.
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