シャドーイング練習: 100+ Docker Concepts you Need to Know - 動画で英語スピーキングを学ぶ
レッスンを作成中...
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Welcome to Docker 101.
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If your goal is to ship software in the real world, one of the most powerful concepts to understand is containerization.
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When developing locally, it solves the age-old problem of it works on my machine, and when deploying in the cloud, it solves the age-old problem of this architecture doesn't scale.
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Over the next few minutes, we'll unlock the power inside this container by learning 101 different concepts and terms related to computer science, the cloud, and of course Docker.
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I'm guessing you know what a computer is, right?
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box that has three important components inside.
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A CPU for calculating things, random access memory for the applications you're using right now, and a disk to store things you might use later.
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This is bare metal hardware, but in order to use it, we need an operating system.
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Most importantly, the OS provides a kernel that sits on top of the bare metal, allowing software applications to run on it.
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In the olden days, you would go to the store and buy software to physically install it on your machine.
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But nowadays, most software is delivered via the internet through the magic of networking.
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When you watch a YouTube video, your computer is called the client, but you and billions of other users are getting that data from remote computers called servers.
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When an app starts reaching millions of people, weird things begin to happen.
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The CPU becomes exhausted handling all the incoming requests, disk IO slows down, network bandwidth gets maxed out, and the database becomes too large to query effectively.
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On top of that, you wrote some garbage code that's causing race conditions, memory leaks, and unhandled errors that will eventually grind your server to a halt.
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The big question is how do we scale our infrastructure?
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A server can scale up in two ways, vertically or horizontally.
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To scale vertically, you take your one server and increase its RAM and CPU.
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This can take you pretty far, but eventually you hit a ceiling.
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The other option is to scale horizontally, where you distribute your code to multiple smaller servers, which are often broken down into microservices that can run and scale independently.
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But distributed systems like this aren't very practical when talking about bare metal, because actual resource allocation varies.
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One way engineers address this is with virtual machines, using tools like Hypervisor.
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It can isolate and run multiple operating systems on a single machine.
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That helps, but a VM's allocation of CPU and memory is still fixed.
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And that's where Docker comes in, the sponsor of today's video.
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Applications running on top of the Docker engine all share the same host operating system kernel
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and use resources dynamically based on their needs.
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Under the hood, Docker's running a daemon or persistent process that makes all this magic possible and gives us OS-level virtualization.
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What's awesome is that any developer can easily harness this power by simply installing Docker Desktop.
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It allows you to develop software without having to make massive changes to your local system.
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But here's how Docker works in three easy steps.
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First, you start with a Docker file.
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This is like a blueprint that tells Docker how to configure the environment that runs your application.
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The Docker file is then used to build an image, which contains an OS, your dependencies, and your code, like a template for running your application.
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And we can upload this image to the cloud to places like Docker Hub and share it with the world.
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But an image by itself doesn't do anything.
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You need to run it as a container, which itself is an isolated package running your code that in theory could scale infinitely in the cloud.
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Containers are stateless, which means when they shut down, all the data inside them is lost.
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But that makes them portable, and they can run on every major cloud platform without vendor lock-in.
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Pretty cool, but the best way to learn Docker is to actually run a container.
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Let's do that right now by creating a Docker file.
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A Docker file contains a collection of instructions, which by convention are in all caps.
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From is usually the first instruction you'll see, which points to a base image to get started.
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This will often be a Linux distro, and may be followed by a colon, which is an optional image tag, and in this case specifies the version of the OS.
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Next, we have the working directory instruction, which creates a source directory and CDs into it, and that's where we'll put our source code.
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All commands from here on out will be executed from this working directory.
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Next, we can use the run instruction to use a Linux package manager to install our dependencies.
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Run lets you run any command just like you would from the command line.
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Currently we're running as the root user, but for better security we could also create a non-root user with the user instruction.
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Now we can use copy to copy the code on our local machine over to the image.
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You're halfway there, let's take a brief intermission.
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Now to run this code we have an API key, which we can set as an environment variable with the env instruction.
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We're building a web server that people can connect to, which requires a port for external traffic.
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Use the expose instruction to make that port accessible.
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Finally, that brings us to the command instruction, which is the command you want to run when starting up a container.
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In this case, it will run our web server.
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There can only be one command per container, although you might also add an entry point, allowing you to pass arguments to the command when you run it.
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That's everything we need for the Dockerfile.
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But as an added touch, we could also use label to add some extra metadata, or we could run a health check to make sure it's running properly,
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or if the container needs to store data that's going to be used later or be used by multiple containers, we could mount a volume to it with a persistent disk.
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Okay, we have a Dockerfile, so now what?
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When you install Docker Desktop, that also installed the Docker CLI, which you can run from the terminal.
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Run Docker help to see all the possible commands, but the one we need right now is Docker build, which will turn this Docker file into an image.
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When you run the command, it's a good idea to use the T flag to tag it with a recognizable name.
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Notice how it builds the image in layers.
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Every layer is identified by a SHA-256 hash, which means if you modify your Docker file, each layer will be cached, so it only has to rebuild what has actually changed,
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and that makes your workflow as a developer far more efficient.
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In addition, it's important to point out that sometimes you don't want certain files to end up in a Docker image, in which case you can add them to the Docker ignore file to exclude them from the actual files
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that get copied there.
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Now open Docker Desktop and view the image there.
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Not only does it give us a detailed breakdown, but thanks to Docker Scout, we're able to proactively identify any security vulnerabilities for each layer of the image.
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It works by extracting the software bill of material from the image and compares it to a bunch of security advisory databases.
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When there's a match, it's given a severity rating, so you can prioritize your security efforts.
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But now the time has finally come to run a container.
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We can accomplish that by simply clicking on the run button.
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Under the hood, it executes the docker run command, and we can now access our server on localhost.
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In addition, we can see the running container here in docker desktop, which is the equivalent to the docker psst command,
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which you can run from the terminal to get a breakdown of all the running and stop containers on your machine.
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If we click on it though, we can inspect the logs from this container, or view the file system, and we can even execute commands directly inside the running container.
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Now when it comes time to shut it down, we can use Docker stop to stop it gracefully, or Docker kill to forcefully stop it.
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You can still see the shutdown container here in the UI, or use remove to get rid of it.
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But now you might want to run your container in the cloud.
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Docker push will upload your image to a remote registry, where it can then run on a cloud like AWS with Elastic Container Service,
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or it can be launched on serverless platforms like Google Cloud Run.
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Conversely, you may want to use someone else's Docker image, which can be downloaded from the cloud with Docker Pool.
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And now you can run any developer's code without having to make any changes to your local environment or machine.
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Congratulations, you're now a bona fide and certified Docker expert.
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I hereby grant you permission to print out this certificate and bring it to your next job interview.
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But Docker itself is only the beginning.
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There's a good chance your application has more than one service, in which case you'll want to know about Docker Compose, a tool for managing multi-container applications.
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It allows you to define multiple applications and their Docker images in a single YAML file, like a frontend, a backend, and a database.
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The Docker Compose up command will spin up all the containers simultaneously, while the down command will stop them.
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That works on an individual server, but once you reach massive scale, you'll likely need an orchestration tool like Kubernetes to run and manage containers all over the world.
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It works like this.
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You have a control plane that exposes an API that can manage the cluster.
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Now, the cluster has multiple nodes or machines, each one containing a kubelet and multiple pods.
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A pod is the minimum deployable unit in Kubernetes, which itself has one or more containers inside of it.
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What makes Kubernetes so effective is that you can describe the desired state of the system, and it will automatically scale up or scale down,
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while also providing fault tolerance to automatically heal if one of your servers goes down.
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It gets pretty complicated, but the good news is that you probably don't need Kubernetes.
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It was developed at Google based on its Borg system and is really only necessary for highly complex high-traffic systems.
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If that sounds like you though, you can also use extensions on Docker Desktop to debug your pods.
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And with that, we've looked at 100 concepts related to containerization.
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Big shout out to Docker for making this video possible.
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Thanks for watching, and I will see you in the next one.
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このレッスンの語彙とスピーキングのポイント
この動画には、シャドーイング用の文が105文、単語が1837語あります。 音声の長さは8:27です。 話す速さは速く、1分あたり約217語です。音のつながりや弱く発音される音が多くなります。 英語の頻出3,000語に含まれる単語は79%だけなので、語彙は難しめです。
この動画の重要語彙
動画に出てくる覚えておきたい単語15語を、発音と意味つきで紹介します。
| 単語 | 発音 | 意味 |
|---|---|---|
| container 名詞 | /kənˈteɪ.nəɹ/ | 容器 |
| server 名詞 | /ˈsɝvɚ/ | サーバー |
| cloud 名詞 | /ˈklaʊ̯d/ | 雲, 雲霞 |
| instruction 名詞 | /ɪnˈstɹʌkʃən/ | 指示 |
| desktop 名詞 | /ˈdɛsktɒp/ | 机の上 |
| layer 名詞 | /ˈleɪ̯ɚ/ | 層, 膜 |
| install 動詞 | /ɪnˈstɔl/ | 導入する, インストールする |
| database 名詞 | /ˈdeɪtəˌbeɪs/ | データベース |
| disk 名詞 | /dɪsk/ | ディスク, 円盤 |
| execute 動詞 | /ˈɛksɪˌkjuːt/ | 処刑する, 消す |
| directory 名詞 | /dɪˈɹɛktəɹi/ | 一覧, 名鑑 |
| package 名詞 | /ˈpæk.ɪd͡ʒ/ | 包み, パケット |
| solve 動詞 | /sɒlv/ | 解決する |
| remote 形容詞 | /ɹəˈməʊt̞/ | 遠い, 遠隔な |
| terminal 名詞 | /ˈtɚmɪnəl/ | ターミナル, エアターミナル |
動画に出てくる句動詞
| 単語 | 意味 |
|---|---|
| go down 動詞 | 降りる, 降下する |
| point out 動詞 | 指す, 指し示す |
| shut down 動詞 | シャットダウン |
| slow down 動詞 | 遅らせる |
注意したい発音
話し手はwe're, you'll, you'reなど、短縮形や弱形を18回使っています。聞こえたとおりの短い形で発音しましょう。
- 「sh」と「zh」の音: instruction /ɪnˈstɹʌkʃən/, allocation /ˌæl.əˈkeɪ.ʃən/, extension /ɪkˈstɛnʃən/, efficient /ɪˈfɪʃənt/, congratulations /kənˌɡɹæt͡ʃəˈleɪʃ(ə)nz/
- 長い単語（アクセントの位置に注意）: directory /dɪˈɹɛktəɹi/, developer /dɪˈvɛləpɚ/, allocation /ˌæl.əˈkeɪ.ʃən/, dependency /dɪˈpɛndənsi/, complicated /ˈkɑm.plɪˌkeɪ.tɪd/
この動画での練習方法
- まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
- まず0.75倍速で一文ずつシャドーイングし、慣れてきたら通常の速度に戻します。
- 自分の声を録音して元の音声と比べます。container, server, cloudなどの単語に特に注意しましょう。
この動画の文法
話し手がよく使っている文型を、動画の実際の表現とともに紹介します。
| 文型 | 動画での表現 |
|---|---|
| 受動態 be + 過去分詞 — 誰がするかより、何が起きるかに焦点を当てる | is delivered · is called · are often broken |
| 関係詞節 who / which + 節 — 人や物について情報を加える | servers, which are · stateless, which means · colon, which is |
| 現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係している | has actually changed · has finally come · we've looked |
シャドーイングとは？英語上達に効果的な理由
シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。