Shadowing Practice: 100+ Docker Concepts you Need to Know - Learn English Speaking with Video
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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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Bu dersin kelimeleri ve konuşma notları
Bu videoda gölgeleme çalışması için 105 cümle ve 1837 kelime var. Konuşma bölümü 8:27 sürüyor. Konuşmacı hızlı konuşuyor, dakikada yaklaşık 217 kelime; bu yüzden birbirine bağlanan ve zayıflayan sesler duyacaksınız. Kelimelerin yalnızca %79’i İngilizcede en sık kullanılan 3.000 kelime arasında, bu yüzden kelime dağarcığı zorlayıcı.
Bu videodaki önemli kelimeler
Videodan öğrenmeye değer 15 kelime, telaffuzu ve anlamıyla:
| Kelime | Telaffuz | Anlam |
|---|---|---|
| container isim | /kənˈteɪ.nəɹ/ | kap, konteyner |
| server isim | /ˈsɝvɚ/ | sunucu, server |
| cloud isim | /ˈklaʊ̯d/ | bulut |
| desktop isim | /ˈdɛsktɒp/ | masaüstü |
| layer isim | /ˈleɪ̯ɚ/ | katman, tabaka |
| install fiil | /ɪnˈstɔl/ | indirmek |
| database isim | /ˈdeɪtəˌbeɪs/ | veritabanı, veri tabanı |
| disk isim | /dɪsk/ | disk, ağırşak |
| execute fiil | /ˈɛksɪˌkjuːt/ | idam etmek |
| directory isim | /dɪˈɹɛktəɹi/ | dizin, klasör |
| package isim | /ˈpæk.ɪd͡ʒ/ | paket |
| solve fiil | /sɒlv/ | çözmek, halletmek |
| remote sıfat | /ɹəˈməʊt̞/ | uzak, uzaktan kontrol |
| terminal isim | /ˈtɚmɪnəl/ | terminal |
| developer isim | /dɪˈvɛləpɚ/ | geliştirici |
Duyacağınız deyimsel fiiller
| Kelime | Anlam |
|---|---|
| slow down fiil | yavaşlamak |
Dikkat edilecek telaffuzlar
Konuşmacı we're, you'll, you're gibi kısaltılmış biçimleri 18 kez kullanıyor. Bunları duyduğunuz gibi kısa söyleyin.
- “sh” ve “zh” sesleri: instruction /ɪnˈstɹʌkʃən/, allocation /ˌæl.əˈkeɪ.ʃən/, extension /ɪkˈstɛnʃən/, efficient /ɪˈfɪʃənt/, congratulations /kənˌɡɹæt͡ʃəˈleɪʃ(ə)nz/
- Uzun kelimeler — vurguyu doğru yere koyun: directory /dɪˈɹɛktəɹi/, developer /dɪˈvɛləpɚ/, allocation /ˌæl.əˈkeɪ.ʃən/, dependency /dɪˈpɛndənsi/, complicated /ˈkɑm.plɪˌkeɪ.tɪd/
Bu videoyla nasıl çalışılır
- Videonun tamamını konuşmadan bir kez dinleyin ve bilmediğiniz kelimeleri not edin.
- 0,75× hızla başlayın, cümle cümle tekrar edin ve kolaylaşınca normal hıza dönün.
- Kendinizi kaydedin ve orijinaliyle karşılaştırın; container, server, cloud gibi kelimelere özellikle dikkat edin.
Bu videodaki dil bilgisi
Konuşmacının en çok kullandığı yapılar, videodaki sözcüklerin aynısıyla:
| Yapı | Videoda |
|---|---|
| Edilgen yapı be + fiilin üçüncü hâli — kimin yaptığı değil, ne olduğu önemli | is delivered · is called · are often broken |
| İlgi cümlecikleri who / which + cümle — bir kişi ya da şey hakkında ek bilgi | servers, which are · stateless, which means · colon, which is |
| Present perfect have/has + fiilin üçüncü hâli — geçmişte olan ama şimdi de önemli olan bir eylem | has actually changed · has finally come · we've looked |
Gölgeleme Tekniği Nedir?
Gölgeleme, başlangıçta profesyonel tercüman eğitimi için geliştirilen ve çok dilli Dr. Alexander Arguelles tarafından popüler hale getirilen, bilim destekli bir dil öğrenme tekniğidir. Yöntem basit ama güçlüdür: ana dili İngilizce olan bir sesi dinler ve hemen yüksek sesle tekrar edersiniz — konuşmacıyı 1-2 saniye gecikmeyle takip eden bir gölge gibi. Pasif dinleme veya dilbilgisi alıştırmalarının aksine, gölgeleme beyninizi ve ağız kaslarınızı gerçek konuşma kalıplarını eşzamanlı olarak işlemeye ve yeniden üretmeye zorlar. Araştırmalar, telaffuz doğruluğu, tonlama, ritim, bağlı konuşma, dinleme anlama ve konuşma akıcılığını önemli ölçüde geliştirdiğini göstermektedir — bu da onu IELTS Konuşma hazırlığı ve gerçek dünya İngilizce iletişimi için en etkili yöntemlerden biri yapar.