Pratica di Shadowing: 100+ Docker Concepts you Need to Know - Impara a parlare inglese con i video
Creazione lezione...
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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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Vocabolario e note di pronuncia per questa lezione
Questo video contiene 105 frasi e 1837 parole da ripetere con lo shadowing. Il parlato dura 8:27. Chi parla va veloce, circa 217 parole al minuto: aspettati suoni legati e ridotti. Solo il 79% delle parole rientra nelle 3.000 più comuni dell’inglese, quindi il lessico è impegnativo.
Vocaboli chiave di questo video
15 parole del video che vale la pena imparare, con pronuncia e significato:
| Parola | Pronuncia | Significato |
|---|---|---|
| container sostantivo | /kənˈteɪ.nəɹ/ | contenitore, recipiente |
| server sostantivo | /ˈsɝvɚ/ | server |
| cloud sostantivo | /ˈklaʊ̯d/ | nuvola, nube |
| instruction sostantivo | /ɪnˈstɹʌkʃən/ | istruzione, addestramento |
| desktop sostantivo | /ˈdɛsktɒp/ | computer fisso, calcolatore fisso |
| layer sostantivo | /ˈleɪ̯ɚ/ | strato |
| install verbo | /ɪnˈstɔl/ | installare |
| database sostantivo | /ˈdeɪtəˌbeɪs/ | database, base di dati |
| disk sostantivo | /dɪsk/ | disco |
| execute verbo | /ˈɛksɪˌkjuːt/ | giustiziare |
| directory sostantivo | /dɪˈɹɛktəɹi/ | elenco, lista |
| package sostantivo | /ˈpæk.ɪd͡ʒ/ | pacco |
| solve verbo | /sɒlv/ | risolvere |
| remote aggettivo | /ɹəˈməʊt̞/ | remoto |
| terminal sostantivo | /ˈtɚmɪnəl/ | terminal, terminale |
I phrasal verb che sentirai
| Parola | Significato |
|---|---|
| point out verbo | additare |
| shut down verbo | spegnere |
| slow down verbo | rallentare, decelerare |
Pronuncia a cui fare attenzione
Chi parla usa 18 contrazioni e forme ridotte, come we're, you'll, you're. Pronunciale nella forma breve, così come le senti.
- I suoni “sh” e “zh”: instruction /ɪnˈstɹʌkʃən/, allocation /ˌæl.əˈkeɪ.ʃən/, extension /ɪkˈstɛnʃən/, efficient /ɪˈfɪʃənt/, congratulations /kənˌɡɹæt͡ʃəˈleɪʃ(ə)nz/
- Parole lunghe — attenzione all’accento: directory /dɪˈɹɛktəɹi/, developer /dɪˈvɛləpɚ/, allocation /ˌæl.əˈkeɪ.ʃən/, dependency /dɪˈpɛndənsi/, complicated /ˈkɑm.plɪˌkeɪ.tɪd/
Come esercitarsi con questo video
- Ascolta tutto il video una volta senza parlare e annota le parole che non conosci.
- Inizia a velocità 0,75×, fai shadowing frase per frase e torna alla velocità normale quando diventa facile.
- Registrati e confronta con l’originale, facendo attenzione a parole come container, server, cloud.
La grammatica di questo video
Le strutture che chi parla usa di più, con le parole esatte del video:
| Struttura | Nel video |
|---|---|
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | is delivered · is called · are often broken |
| Frasi relative who / which + frase — un’informazione in più su una persona o una cosa | servers, which are · stateless, which means · colon, which is |
| Present perfect have/has + participio passato — un’azione passata che conta ancora adesso | has actually changed · has finally come · we've looked |
Cos'è la tecnica dello Shadowing?
Shadowing è una tecnica di apprendimento delle lingue supportata da studi scientifici, originariamente sviluppata per la formazione dei traduttori professionisti e resa popolare dal poliglotta Dr. Alexander Arguelles. Il metodo è semplice ma potente: ascolti un audio in inglese di madrelingua e lo ripeti immediatamente ad alta voce — come un'ombra che segue il parlante con un ritardo di solo 1–2 secondi. A differenza dell'ascolto passivo o degli esercizi di grammatica, lo shadowing costringe il tuo cervello e i muscoli della bocca a elaborare e riprodurre simultaneamente i modelli di discorso reale. La ricerca dimostra che migliora significativamente la precisione della pronuncia, l'intonazione, il ritmo, il discorso connesso, la comprensione dell'ascolto e la fluidità del parlato — rendendolo uno dei metodi più efficaci per la preparazione alla prova di speaking dell'IELTS e per la comunicazione reale in inglese.