Never install locally

Summary

This video script introduces the concept of containers as a fast, portable, and isolated development environment that sits between virtual machines and native applications. It explains how containers share the host's kernel to save resources and provides a developer-friendly way to maintain multiple environments without conflicts. The script covers the basics of creating a container with Docker, using Dockerfiles and container images with layered file systems, and discusses the benefits of containerization in development, such as solving the 'it works on my machine' problem. It also touches on deploying containers, using container registries, and the potential of container orchestration with platforms like Kubernetes.

Takeaways

• 🚀 Containers are a lightweight, fast, and portable way to deploy applications, providing isolated environments that can be set up quickly.
• 🔄 Unlike VMs, containers share the host's kernel and emulate a minimal file system, making them more resource-efficient and faster to start.
• 💻 The kernel is the core of an OS, acting as a bridge between software requests and hardware actions, handling low-level tasks like CPU and memory management.
• 🛠️ Containers allow developers to work in multiple environments without compromising their local machine, enabling the maintenance of legacy apps alongside new projects.
• 🔗 The 'it works on my machine' problem is mitigated by containers, ensuring consistent environments across different machines and platforms.
• 🛑 A container platform like Docker provides the necessary tools to create and manage containers, leveraging the benefits of containerization.
• 📚 Container images are made of layered file systems, where changes are tracked as differences from previous layers, similar to source control.
• 📝 Dockerfiles are used to script the creation of container images, executing commands in sequence and layering the changes.
• 🔄 Multiple containers can be run from a single image, with each container having its own dedicated file system layer for runtime changes.
• 🔒 Containers can be tagged with unique identifiers, such as versions, and published to a container registry for storage and distribution.
• 🌐 Modern cloud platforms support container deployment, and container orchestration platforms like Kubernetes can manage large-scale container deployments.

Q & A

What is a container in the context of software development?

A container is a lightweight, portable, and isolated environment that can run an application and its dependencies. It shares the host system's kernel but has its own file system and runtime.

How do containers differ from virtual machines?

Containers are quicker to spin up and typically less resource-intensive than virtual machines. While VMs emulate hardware and run a full OS, containers share the host's kernel and emulate only a minimal file system.

What is the role of the kernel in operating systems?

The kernel is the core of an operating system, acting as a bridge between software requests and hardware actions. It is responsible for critical tasks such as CPU and memory management, device I/O, file systems, and process management.

How can containers help with the 'it works on my machine' problem?

Containers provide a consistent environment across different machines because they include a full OS at their core. This ensures that the application runs the same way regardless of where it's deployed, eliminating environment discrepancies.

What is a Dockerfile and what is its purpose?

A Dockerfile is a script containing a series of commands that Docker executes to build an image. Each command creates a new layer in the image, allowing for the creation of custom images based on base images or previous layers.

How do container images form with overlapping layers?

Container images are formed by tracking changes to file systems as differences from previous layers and composing these changes to create the final system state. This is similar to how source control tracks changes in code.

What is a container registry and what is its function?

A container registry is an online storage system for container images. It allows developers to store, manage, and distribute container images, making it easier to share and reuse them across different environments.

How can container platforms like Docker help in software development?

Container platforms provide the necessary tools to create, build, and run containers. They allow developers to work in multiple environments simultaneously without compromising their local machine, ensuring consistency and reducing conflicts.

What is the significance of tagging a container image with a version?

Tagging a container image with a version allows developers to uniquely identify and reference the image later. It helps in managing different versions of an application and ensures that the correct version is deployed.

How do container orchestration platforms like Kubernetes work?

Container orchestration platforms manage the deployment, scaling, and operation of containerized applications. They allow developers to describe the desired state of their deployment, and the platform handles the details of achieving that state.

What are the benefits of using containerization in application deployment?

Containerization offers benefits such as portability, consistency, and efficiency in application deployment. It simplifies the development and deployment process, reduces environment-related issues, and allows for better resource utilization.

Outlines

00:00

🚀 Understanding Containers vs. Virtual Machines

This paragraph introduces the concept of containers, highlighting their speed, portability, and isolated environments compared to virtual machines (VMs). Containers are faster to spin up and less resource-intensive than VMs, sitting between VMs and native applications in terms of performance. Unlike VMs that rely heavily on a host's hypervisor, containers share the host's kernel, allowing for more efficient resource utilization. The kernel, as the core of an operating system, manages critical tasks like CPU and memory management, bridging the gap between software and hardware.

05:03

💻 The Developer's Advantage: Working Across Multiple Environments

This paragraph explains how containers benefit developers by allowing them to work in multiple environments simultaneously without compromising their local machine. Containers enable developers to maintain legacy applications alongside cutting-edge technology without conflict. They also solve the 'it works on my machine' problem by providing a consistent environment across different machines, whether local, on a server, or in the cloud. This consistency is due to the container's ability to replicate an OS environment exactly, ensuring that the application runs the same everywhere.

🛠 Creating and Managing Containers with Docker

Here, the process of creating a container is detailed, emphasizing the use of Docker as a container platform. Containers start from a base file system and are constructed through layers of changes, similar to how source control tracks changes in code. These layers are added through commands in a Dockerfile, which Docker executes to build the final image. Multiple containers can run from a single image, each with its dedicated file system layer that persists until the container is deleted. This section also notes that containers can be accessed like virtual machines, offering flexibility in managing and exploring their environments.

🔗 Networking and Deploying Containers

This paragraph covers how containers communicate via virtualized network layers and the steps needed for publishing an application. Containers are tagged with unique identifiers, like versions, and then published to a container registry—online storage for images. Docker's default registry can be overridden, and containers can be deployed on modern cloud platforms or any machine with a compatible container runtime. This method provides more control and better value for money, though it may involve additional steps.

☁️ Advanced Deployment: Kubernetes and Container Orchestration

The final paragraph introduces Kubernetes as a container orchestration platform, allowing for the creation of a container-based cloud. With Kubernetes, developers can define the desired state of their deployment, and the platform manages the implementation details. The paragraph concludes with the creator's expression of a desire to produce content full-time, thanking the audience for their support and encouraging further engagement.

Keywords

💡Container

A container in the context of the video refers to a lightweight, portable, and isolated software environment that can run applications consistently across different computing environments. It is central to the video's theme as it discusses the benefits of using containers for development and deployment, such as speed and resource efficiency. The script uses the term to illustrate how containers are different from virtual machines and how they can be used to solve common development problems.

💡OS (Operating System)

The term OS in the video script denotes the underlying system software that manages computer hardware and software resources. It is mentioned as being pre-configured in a container, allowing for a consistent development environment. The video emphasizes the importance of the OS in containers for ensuring compatibility and reducing issues like 'it works on my machine'.

💡Docker

Docker is a container platform mentioned in the script, which provides tools to create, deploy, and run containers. It is highlighted as being well-supported and is used as an example to demonstrate how to make a container. The script explains Docker's role in the process of containerization, which is integral to the video's message about modern application deployment techniques.

💡Container Image

A container image is a lightweight, stand-alone, and executable package that includes everything needed to run an application as a container. The script describes how images are formed with overlapping layers and how they serve as the base for creating containers. This concept is crucial to understanding the efficiency and flexibility of container deployment.

💡Dockerfile

A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. In the script, it is mentioned as the file where commands are added to create a custom container image. It exemplifies the script's theme by showing how developers can define the environment for their applications.

💡File System Layer

The file system layer mentioned in the script refers to the individual layers that make up a container image, with each layer representing changes to the file system. The concept is important as it explains how container images are built incrementally and allows for efficient storage and distribution of container images.

💡Isolation

Isolation in the video script refers to the separation of the application environment from the underlying host system. It is a key feature of containers, allowing for secure and independent application deployment. The script discusses how isolation benefits development by preventing conflicts between applications and their dependencies.

💡Kernel

The kernel is the core component of an operating system that manages the system's resources and provides services for the running applications. The script explains that containers share the host's kernel, which is different from virtual machines that have their own. This distinction is important for understanding the efficiency and performance of containers.

💡Container Registry

A container registry, as mentioned in the script, is a remote storage system where container images can be stored and managed. It is an essential part of the container lifecycle, allowing developers to share and deploy their containerized applications. The script uses the term to illustrate the distribution aspect of containerization.

💡Orchestration

Orchestration in the context of the video refers to the automated management of container deployment, scaling, and operations. The script briefly introduces Kubernetes as an orchestration platform, which is significant for understanding how complex deployments can be handled efficiently using containers.

💡It works on my machine

This phrase is a common issue in development where an application works in one environment but not in another. The script discusses how containerization can solve this problem by providing a consistent environment across different machines, which is a key benefit highlighted in the video's message about container technology.

Highlights

Containers are pre-configured environments that can be deployed and run immediately, offering a fast and portable solution for application development and deployment.

Containers differ from VMs by being quicker to spin up and less resource-intensive, providing a balance between VMs and native applications.

Containers share the host's kernel and emulate a minimal file system, unlike VMs which are tricked by the hypervisor layer into thinking they run on real hardware.

The kernel acts as a bridge between software requests and hardware capabilities, managing critical tasks such as CPU, memory, device I/O, file systems, and process management.

Developers can work in multiple environments simultaneously without compromising their local machine, thanks to the OS capabilities provided by containers.

Containers help solve the 'it works on my machine' problem by ensuring the same environment across different machines and cloud platforms.

A container platform like Docker provides tools necessary for creating and running containers, leveraging the support of a large community.

Container images are formed with overlapping layers, similar to how source control tracks changes, allowing for efficient extension of custom images from any previous layer.

Dockerfiles contain commands executed by Docker to create an image, with each change added as a new layer, demonstrating the power of layering in container images.

Containers can be created from a single image, with each having a dedicated file system layer for runtime changes, ensuring isolation and persistence.

Runtime changes in containers do not affect other containers using the same image, and the new layer persists until the container is deleted.

Developers can enter running containers to explore and interact with the environment, similar to accessing a VM.

Container communication is simplified with virtualized network layers, facilitating easy interaction between different containers.

When ready for publication, containers can be tagged with unique identifiers such as versions and published to a container registry for storage and retrieval.

Container registries act as online storage for images, with Docker's default being the official Docker registry, but other registries can be used as well.

Modern cloud platforms support deploying containers as standalone units, or containers can be deployed on any machine with a compatible runtime.

Container orchestration platforms like Kubernetes allow for creating a container-based cloud, managing deployment states declaratively.

The video creator expresses a desire to make such educational content full-time, hinting at the potential for a Patreon or similar support system.

Transcripts

and I don't just mean your code and its libraries, I mean the OS too,

all pre-configured to run as soon as you deploy it.

That's a container. They're lightning fast, portable, yet

isolated environments that you can create in mere moments,

and after this video you're going to wonder how you ever developed and

deployed applications without them.

But that's just a VM!

No, firstly, please sit down. Secondly, no, not quite.

Okay, it's true that both give you an isolated environment where you can run

an OS, but containers are quite a bit quicker

to spin up, and typically less resource intensive.

If there was a scale with VMs on one side and normal native applications on the

other, containers would sit somewhere in the middle.

Virtual machines are pretty much just tricked by the host's hypervisor layer

into thinking they're actually running on real hardware.

Containers, on the other hand, are more friendly with the host system and just

emulate a minimal file system, while piggybacking resources by sharing

the host's kernel. The kernel is the... no, not that kernel.

Close enough. The kernel is the core of any operating system.

It's the bridge between what the software asks for and what the hardware

actually does. It's responsible for all sorts of

critical low-level tasks like CPU and memory management, device I.O.,

file systems, and process management. So how does this all help us as

developers? Well, now that we have an OS at our

fingertips, we can work in several different

environments at once without having to really compromise anything on our local

machine. For example, we can maintain an old app

using the OS and package dependencies it was originally built on top of,

while also being able to use bleeding edge tech for our next multi-million

dollar project without having to worry about any conflicts in doing so.

We're also now able to put an end to the it works on my machine problem,

which is a pretty common phrase to hear in the tech industry, unfortunately.

Because a container is essentially a full OS at its core,

you can be sure that wherever it runs you're going to get the exact same

environment, whether it's on your colleague's

machine, your server machine, or somewhere in the cloud.

Now we've got the basics out of the way. Let's see how we can make a container

of our own. The first thing we're going to need is

a container platform. This will give us all the tools we need to create and run

our container, and for this video I'll be using Docker,

just because it's the most well supported. All containers run from a base

file system and some metadata, presented to us as a container image.

And the way container images work is kind of fascinating,

because they are formed with overlapping layers.

Here's a banana to kind of badly demonstrate this idea.

Okay, so in the context of a file system, I mean that instead of changing data at

its source, file changes are tracked by their

differences to the previous layer, and then composed together to achieve

the final system state. It's somewhat similar to how source

control tracks changes in your code. This concept is really powerful for

containers, because it lets us extend our custom image from

any previous image or image layer. There's loads of pre-made and officially

supported base images out there, that you can match to your project's core

requirements, and then add your own packages, code and configuration to.

To do this in Docker, we add the commands we want to execute to a

file called a Dockerfile. Docker will execute each command in sequence,

and then add each generated change to the final image as a new file system

layer, or a metadata layer. We can run as many containers as we

like from a single image. We can do this because when a container

is first created, the image's file system is extended with a new file system

layer, completely dedicated to that container.

This means that we can make any runtime changes we like, and it won't affect

other containers using that same image. What's more, this new layer will persist

until we delete the container, so we can stop and start them as we like,

without losing any data. We can even enter our running containers,

like we do with a VM. With Linux containers, for example,

we can start a shell prompt when executing it, giving us access to the

environment to explore and kind of just play around with as we please.

Communication between containers is usually pretty simple as well,

as most runtimes virtualize a network layer for you.

When our app is ready to be published into the world, we're going to want to

tag it with something unique, like a version, so that we can reference

it again later. We can then publish it to something

called a container registry, which is just like an online storage

warehouse for our images. By default, Docker assumes that you're

using the official Docker registry. However, this can be easily overridden

if you wish to use another. When it comes to deployment, many modern

cloud platforms have built-in support for deploying containers as

standalone units. Alternatively, you can install a

compatible container runtime on whatever machine you want to use, and

pull your image from the registry you pushed to earlier.

It does require a few more steps doing it this way, but you generally get better

value for money and quite a bit more control. If you

want to go even deeper, container orchestration platforms such as

Kubernetes essentially allow you to create your own container-based cloud.

You describe the desired state of your deployment declaratively,

and let Kubernetes handle the details of how to get there.

And that's it. Oh, I'd really love to make these videos full-time for you all,

and with enough support, that might just be possible. Thank you,

and I'll see you next time.