跟讀練習: 100+ Docker Concepts you Need to Know - 通過影片學習英語口語

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105 句

如果句子過短或過長，請點選 Edit 進行調整。

Welcome to Docker 101.

If your goal is to ship software in the real world, one of the most powerful concepts to understand is containerization.

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.

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.

I'm guessing you know what a computer is, right?

box that has three important components inside.

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.

This is bare metal hardware, but in order to use it, we need an operating system.

Most importantly, the OS provides a kernel that sits on top of the bare metal, allowing software applications to run on it.

In the olden days, you would go to the store and buy software to physically install it on your machine.

But nowadays, most software is delivered via the internet through the magic of networking.

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.

When an app starts reaching millions of people, weird things begin to happen.

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.

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.

The big question is how do we scale our infrastructure?

A server can scale up in two ways, vertically or horizontally.

To scale vertically, you take your one server and increase its RAM and CPU.

This can take you pretty far, but eventually you hit a ceiling.

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.

But distributed systems like this aren't very practical when talking about bare metal, because actual resource allocation varies.

One way engineers address this is with virtual machines, using tools like Hypervisor.

It can isolate and run multiple operating systems on a single machine.

That helps, but a VM's allocation of CPU and memory is still fixed.

And that's where Docker comes in, the sponsor of today's video.

Applications running on top of the Docker engine all share the same host operating system kernel

and use resources dynamically based on their needs.

Under the hood, Docker's running a daemon or persistent process that makes all this magic possible and gives us OS-level virtualization.

What's awesome is that any developer can easily harness this power by simply installing Docker Desktop.

It allows you to develop software without having to make massive changes to your local system.

But here's how Docker works in three easy steps.

First, you start with a Docker file.

This is like a blueprint that tells Docker how to configure the environment that runs your application.

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.

And we can upload this image to the cloud to places like Docker Hub and share it with the world.

But an image by itself doesn't do anything.

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.

Containers are stateless, which means when they shut down, all the data inside them is lost.

But that makes them portable, and they can run on every major cloud platform without vendor lock-in.

Pretty cool, but the best way to learn Docker is to actually run a container.

Let's do that right now by creating a Docker file.

A Docker file contains a collection of instructions, which by convention are in all caps.

From is usually the first instruction you'll see, which points to a base image to get started.

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.

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.

All commands from here on out will be executed from this working directory.

Next, we can use the run instruction to use a Linux package manager to install our dependencies.

Run lets you run any command just like you would from the command line.

Currently we're running as the root user, but for better security we could also create a non-root user with the user instruction.

Now we can use copy to copy the code on our local machine over to the image.

You're halfway there, let's take a brief intermission.

Now to run this code we have an API key, which we can set as an environment variable with the env instruction.

We're building a web server that people can connect to, which requires a port for external traffic.

Use the expose instruction to make that port accessible.

Finally, that brings us to the command instruction, which is the command you want to run when starting up a container.

In this case, it will run our web server.

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.

That's everything we need for the Dockerfile.

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,

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.

Okay, we have a Dockerfile, so now what?

When you install Docker Desktop, that also installed the Docker CLI, which you can run from the terminal.

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.

When you run the command, it's a good idea to use the T flag to tag it with a recognizable name.

Notice how it builds the image in layers.

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,

and that makes your workflow as a developer far more efficient.

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

that get copied there.

Now open Docker Desktop and view the image there.

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.

It works by extracting the software bill of material from the image and compares it to a bunch of security advisory databases.

When there's a match, it's given a severity rating, so you can prioritize your security efforts.

But now the time has finally come to run a container.

We can accomplish that by simply clicking on the run button.

Under the hood, it executes the docker run command, and we can now access our server on localhost.

In addition, we can see the running container here in docker desktop, which is the equivalent to the docker psst command,

which you can run from the terminal to get a breakdown of all the running and stop containers on your machine.

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.

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.

You can still see the shutdown container here in the UI, or use remove to get rid of it.

But now you might want to run your container in the cloud.

Docker push will upload your image to a remote registry, where it can then run on a cloud like AWS with Elastic Container Service,

or it can be launched on serverless platforms like Google Cloud Run.

Conversely, you may want to use someone else's Docker image, which can be downloaded from the cloud with Docker Pool.

And now you can run any developer's code without having to make any changes to your local environment or machine.

Congratulations, you're now a bona fide and certified Docker expert.

I hereby grant you permission to print out this certificate and bring it to your next job interview.

But Docker itself is only the beginning.

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.

It allows you to define multiple applications and their Docker images in a single YAML file, like a frontend, a backend, and a database.

The Docker Compose up command will spin up all the containers simultaneously, while the down command will stop them.

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.

It works like this.

You have a control plane that exposes an API that can manage the cluster.

Now, the cluster has multiple nodes or machines, each one containing a kubelet and multiple pods.

A pod is the minimum deployable unit in Kubernetes, which itself has one or more containers inside of it.

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,

while also providing fault tolerance to automatically heal if one of your servers goes down.

100

It gets pretty complicated, but the good news is that you probably don't need Kubernetes.

101

It was developed at Google based on its Borg system and is really only necessary for highly complex high-traffic systems.

102

If that sounds like you though, you can also use extensions on Docker Desktop to debug your pods.

103

And with that, we've looked at 100 concepts related to containerization.

104

Big shout out to Docker for making this video possible.

105

Thanks for watching, and I will see you in the next one.

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流利口語所需的一切

AI 發音評分逐句打分

音標練習掌握每個音

詞彙學習建立你的詞庫

詞彙遊戲邊玩邊學

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本課的詞彙與口語要點

這段影片共有 105 個句子、1837 個單詞可供跟讀。講話部分時長為 8:27。說話人語速較快，每分鐘約 217 個詞，會出現較多連讀和弱讀。只有 79% 的單詞屬於英語最常用的 3,000 詞，詞彙難度較高。

影片中的重點詞彙

影片中 15 個值得學習的單詞，附發音和釋義：

單詞	發音	釋義
container 名詞	/kənˈteɪ.nəɹ/	容器
server 名詞	/ˈsɝvɚ/	伺服器 /伺服器, 伺服器
cloud 名詞	/ˈklaʊ̯d/	йүн, 雲 /雲
instruction 名詞	/ɪnˈstɹʌkʃən/	教導 /教導
desktop 名詞	/ˈdɛsktɒp/	桌面
layer 名詞	/ˈleɪ̯ɚ/	層 /層
install 動詞	/ɪnˈstɔl/	安裝 /安裝
database 名詞	/ˈdeɪtəˌbeɪs/	資料庫 /資料庫
disk 名詞	/dɪsk/	圓盤 /圓盤
execute 動詞	/ˈɛksɪˌkjuːt/	處決 /處決, 處死 /處死
directory 名詞	/dɪˈɹɛktəɹi/	名錄 /名錄, 簿
package 名詞	/ˈpæk.ɪd͡ʒ/	包裹, 包
solve 動詞	/sɒlv/	解決 /解決
remote 形容詞	/ɹəˈməʊt̞/	遠 /遠, 遙遠 /遙遠
terminal 名詞	/ˈtɚmɪnəl/	航站, 航廈 /航廈

影片中出現的短語動詞

單詞	釋義
go down 動詞	下降, 下去
point out 動詞	指, 指出
slow down 動詞	減速 /減速, 放慢

需要注意的發音

說話人用了 18 次縮略和弱讀形式，例如 we're, you'll, you're。請按聽到的簡短形式來說。

“sh” 和 “zh” 音: instruction /ɪnˈstɹʌkʃən/, allocation /ˌæl.əˈkeɪ.ʃən/, extension /ɪkˈstɛnʃən/, efficient /ɪˈfɪʃənt/, congratulations /kənˌɡɹæt͡ʃəˈleɪʃ(ə)nz/
長單詞——注意重音位置: directory /dɪˈɹɛktəɹi/, developer /dɪˈvɛləpɚ/, allocation /ˌæl.əˈkeɪ.ʃən/, dependency /dɪˈpɛndənsi/, complicated /ˈkɑm.plɪˌkeɪ.tɪd/

如何用這段影片練習

先完整聽一遍影片，不要開口，記下不認識的單詞。
先用 0.75 倍速逐句跟讀，熟練之後再回到正常速度。
錄下自己的聲音並與原聲對比，特別注意 container, server, cloud 這類單詞。

影片中的語法

說話人最常用的結構，並附上影片中的原話：

結構	影片中的用法
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	is delivered · is called · are often broken
定語從句 who / which + 從句 — 補充說明人或事物	servers, which are · stateless, which means · colon, which is
現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事	has actually changed · has finally come · we've looked

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: 100+ Docker Concepts you Need to Know - 通過影片學習英語口語

選擇練習模式

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