शैडोइंग अभ्यास: 100+ Docker Concepts you Need to Know - वीडियो के साथ अंग्रेजी बोलना सीखें

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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इस पाठ की शब्दावली और बोलने के सुझाव

इस वीडियो में शैडोइंग के लिए 105 वाक्य और 1837 शब्द हैं। बोला गया हिस्सा 8:27 लंबा है। वक्ता तेज़ बोलता है, लगभग 217 शब्द प्रति मिनट, इसलिए जुड़ी हुई और कमज़ोर ध्वनियाँ ज़्यादा मिलेंगी। केवल 79% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं, इसलिए शब्दावली कठिन है।

इस वीडियो की मुख्य शब्दावली

वीडियो के 15 सीखने लायक शब्द, उच्चारण और अर्थ के साथ:

शब्द	उच्चारण	अर्थ
container संज्ञा	/kənˈteɪ.nəɹ/	पात्र, डिब्बा
server संज्ञा	/ˈsɝvɚ/	सर्वर
cloud संज्ञा	/ˈklaʊ̯d/	मेघ, बादल
instruction संज्ञा	/ɪnˈstɹʌkʃən/	उपदेश, शिक्षण
layer संज्ञा	/ˈleɪ̯ɚ/	परत, तह
database संज्ञा	/ˈdeɪtəˌbeɪs/	डेटाबेस
disk संज्ञा	/dɪsk/	डिस्क, चक्र
directory संज्ञा	/dɪˈɹɛktəɹi/	डायरेक्टरी
package संज्ञा	/ˈpæk.ɪd͡ʒ/	पैकेज, पैकेट
solve क्रिया	/sɒlv/	सुलझाना, हल करना
remote विशेषण	/ɹəˈməʊt̞/	दूर, दूरस्थ
developer संज्ञा	/dɪˈvɛləpɚ/	विकासक
cluster संज्ञा	/ˈklʌstɚ/	गुच्छ
upload क्रिया	/ˈʌpˌloʊd/	चढ़ाना, उपारोपण
expose क्रिया	/ɪkˈspoʊz/	खोलना, उघाड़ना

ध्यान देने योग्य उच्चारण

वक्ता 18 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे we're, you'll, you're। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।

“sh” और “zh” की ध्वनियाँ: instruction /ɪnˈstɹʌkʃən/, allocation /ˌæl.əˈkeɪ.ʃən/, extension /ɪkˈstɛnʃən/, efficient /ɪˈfɪʃənt/, congratulations /kənˌɡɹæt͡ʃəˈleɪʃ(ə)nz/
लंबे शब्द — बलाघात सही रखें: directory /dɪˈɹɛktəɹi/, developer /dɪˈvɛləpɚ/, allocation /ˌæl.əˈkeɪ.ʃən/, dependency /dɪˈpɛndənsi/, complicated /ˈkɑm.plɪˌkeɪ.tɪd/

इस वीडियो से अभ्यास कैसे करें

पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
0.75× गति से शुरू करें, एक-एक वाक्य की शैडोइंग करें, और सहज लगने पर सामान्य गति पर लौटें।
अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर container, server, cloud जैसे शब्दों पर ध्यान दें।

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचना	वीडियो में
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता है	is delivered · is called · are often broken
Relative clauses who / which + उपवाक्य — व्यक्ति या वस्तु के बारे में अतिरिक्त जानकारी	servers, which are · stateless, which means · colon, which is
Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी है	has actually changed · has finally come · we've looked

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

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इस वीडियो की मुख्य शब्दावली

ध्यान देने योग्य उच्चारण

इस वीडियो से अभ्यास कैसे करें

इस वीडियो का व्याकरण

शैडोइंग तकनीक क्या है?