If you’re interested in cloud-native technologies and containers, you’ve probably heard of Docker and Kubernetes and are wondering how they work together. Is it Kubernetes versus Docker, Kubernetes plus Docker, or both? 

What’s the distinction between Kubernetes and Docker? 

Docker is a set of software development tools for creating, sharing, and running individual containers, whereas Kubernetes is a system for scaling containerized applications. 

Consider containers to be standardized packaging for microservices that contain all of the required application code and dependencies. Docker is responsible for creating the containers. A container can run on any device, including a laptop, the cloud, local servers, and even edge devices. 

A modern application is made up of numerous containers. Kubernetes is in charge of running them in production. Because containers are simple to replicate, applications can auto-scale: they can expand or contract processing capacities to meet user demands. 

Docker and Kubernetes are two mostly complementary technologies. Docker, on the other hand, offers a system called Docker Swarm for running containerized applications at scale—Kubernetes vs Docker Swarm. Let’s look at how Kubernetes and Docker complement each other and compete. 

What is Docker? 

Docker has become synonymous with containers, just as Xerox is shorthand for paper copies and “Google” is shorthand for internet search. However, Docker is more than just containers. 

Docker is a set of tools that allows developers to create, share, run, and orchestrate containerized applications. 

What is Kubernetes? 

Kubernetes is a container orchestration platform that is open source and used for managing, automating, and scaling containerized applications. Because of its greater flexibility and scalability, Kubernetes is the de facto standard for container orchestration, though Docker Swarm is also an orchestration tool. 

Join us at Linux2Cloud for the on-demand sessions to learn more about Kubernetes and Docker. 

The Top 15 Docker Containers 

Docker is a tool for shipping and running applications that every techie has heard of. With all of the attention it is receiving these days, developers and tech behemoths such as Google are developing services to support it. 

Whether or not you have an immediate need for Docker, here is a list of the 15 most popular Docker containers. 

1. Alpinism 

It is a minimal Alpine Linux image with a package index. It is 5 MB in size and is based on musl libc and BusyBox. The image has access to a much larger package repository than other BusyBox-based images. Alpine Linux is an excellent image base for utilities and production software. 

2. BusyBox 

BusyBox, with on-disk sizes ranging from 1 to 5 Mb (depending on the variant), is an excellent component for creating space-efficient distributions. BusyBox is a small executable that combines many common UNIX utilities. The utilities have fewer options than full-featured GNU; however, the included options function and behave similarly to their GNU counterparts. As a result, BusyBox offers a reasonably comprehensive environment for any small or embedded system. 

3. Nginx 

Nginx is a reverse proxy server, load balancer, and origin server that is open source. It is compatible with Linux, BSD variants, Mac OS X, Solaris, AIX, HP-UX, and other *nix platforms. It also has a Microsoft Windows proof-of-concept port. This one should be used if you are still determining your requirements. It is intended to be a disposable container as well as the foundation for other images. 

4. Ubuntu 

Ubuntu is the most popular operating system for public clouds and OpenStack clouds worldwide. Furthermore, the container platform can scale your containers quickly and securely. 

5. PostgreSQL 

PostgreSQL, also known as “Postgres,” is capable of handling work ranging from single-machine applications to internet-facing applications with multiple users. The image contains numerous environmental variables that are easy to overlook. The only required variable is POSTGRES PASSWORD; the rest are optional. Please keep in mind that the Docker-specific variables will only have an effect if you start the container with an empty data directory; any pre-existing databases will be ignored upon container startup. 

6. Redis 

Redis is a networked, open-source data store with optional durability. The “Protected mode” is turned off by default for easy access via Docker networking. As a result, exposing the port outside your host (for example, with -p on docker run) makes it accessible to anyone without a password. Setting a password (via a configuration file) is thus strongly advised. 

7. Node 

Node.js is a server-side and networking application platform. Javascript applications can be run in the Node.js runtime on Mac OS X, Windows, and Linux without modification. Node.js includes an asynchronous I/O library that supports file, socket, and HTTP communication. Because of HTTP and socket support, Node.js can function as a web server without the need for additional software such as Apache. 

8. Apache 

HTTPd Apache is a Web server application that was instrumental in the early development of the internet. This image only contains Apache HTTPd with the upstream defaults. There is no PHP installed, but it should be simple to extend. If you want PHP with Apache HTTPd, look at the PHP image and look for the -apache tags. Add a Dockerfile to the project to run an HTML server, where public-HTML/ is the directory containing all HTML. 

9. Python 

Modules, exceptions, dynamic typing, high-level data types, and classes are all built into Python. It can also be used as an extension language in applications that require a programmable interface. It is portable and works on a variety of Unix variants, including Mac OS X and Windows 2000 and later. Many simple, single-file projects may necessitate assistance in writing a complete Dockerfile. In such cases, you can use the Python Docker image to run a Python script. 

10. MongoDB 

MongoDB is an open-source database program that uses schemata and JSON-like documents. The MongoDB server in the image operates on the standard MongoDB port, 27017, and connects via Docker networks, just like a remote MongoDB 

11. MySQL 

MySQL has established itself as a leading database for web-based applications, supporting a wide range of personal projects and websites. It is simple to start a MySQL instance: -e MYSQL ROOT PASSWORD=my-secret-pw -d mysql:tag $ docker run -name some-mysql -e MYSQL ROOT PASSWORD=my-secret-pw -d mysql . 

12. Memcached 

Memcached is a system for distributed memory caching. Its APIs provide a large hash table distributed across multiple machines. When the table is full, older data is purged in the least recently used order. Memcached applications typically layer requests and additions into RAM before exiting to a slower backing store. 

13. Traefik 

Traefik is an HTTP reverse proxy and load balancer that allows for the rapid deployment of microservices. It automatically integrates with the existing Docker infrastructure and dynamically configures itself. The only configuration step should be to point Traefik to your orchestrator. 

14. MariaDB 

MariaDB Server is a well-known open-source database server developed by MySQL developers. It is simple to start a MariaDB instance with the most recent version: $ docker run –detach –name some-mariadb –env MARIADB USER=example-user –env MARIADB PASSWORD=my cool secret –env MARIADB ROOT PASSWORD=my-secret-pw mariadb:latest \sor: $ docker network create some-network $ docker run –detach –network some-network –name some-mariadb –env MARIADB USER=example-user –env MA 

15. RabbitMQ 

RabbitMQ is a free and open-source message broker that uses the Advanced Message Queuing Protocol. It saves data based on the “Node Name,” which is usually the hostname. In Docker, we should explicitly specify -h/-hostname for each daemon so that the user does not get a random hostname and can keep track of the data. 

Bottom Line 

Docker Swarm and Kubernetes are both production-grade container orchestration platforms, though their strengths differ. 

Docker Swarm, also known as Docker in swarm mode, is the most straightforward orchestrator to deploy and manage. It may be a good option for a company that is just getting started with container production. Swarm covers 80% of all use cases with only 20% of the complexity of Kubernetes.

Kubernetes is open-source software that allows you to deploy and manage containerized applications at scale. Kubernetes can manage clusters on Amazon EC2 instances, run containers on those instances, and perform deployment, maintenance, and scaling tasks.

Kubernetes enables using the same set of tools to run containerized applications on-premises and in the cloud.

AWS provides Amazon Elastic Kubernetes Service (EKS), a managed, certified Kubernetes-compatible service with community-supported service integrations for running Kubernetes on AWS and on-premises.

Kubernetes is a project that is open source. Kubernetes enables you to run containerized applications wherever you want without changing your operational tools. Kubernetes is regularly maintained and improved by a large community of volunteers.

Kubernetes’ large community creates and maintains Kubernetes-compatible software that can be used to enhance and extend application architectures.

Kubernetes Security Best Practices on AWS

Understanding the Model of Shared Responsibility

When using managed services such as EKS, security and compliance are viewed as shared responsibilities. In general, AWS is responsible for “inside” cloud security, and the cloud customer is responsible for “inside” cloud security.

AWS manages the Kubernetes control plane through EKS. This includes the Kubernetes master server, the etcd database, and any other infrastructure that AWS requires to provide secure and reliable services.

Identity and access management (IAM), pod security, runtime security, and network security are primarily the responsibility of EKS customers.

AWS is also in charge of keeping Kubernetes patch releases and security patches up to date for EKS-optimised Amazon Machine Images (AMIs). Customers who use managed node groups (MNGs) must upgrade their node groups to the most recent AMI using the EKS API, CLI, Cloudformation, or the AWS console.

Red/Blue Team and Penetration Testing Practice

Divide the security personnel into two groups: red and blue. The red team investigates vulnerabilities in various systems, while the blue team handles vulnerability defence.

If you need more security personnel to form a separate team, consider hiring a third-party organization familiar with Kubernetes exploits.

Kubesploit is a penetration testing framework for conducting tests. It can simulate real-world attacks on Kubernetes clusters, allowing the blue team to practise responding to them and assess their effectiveness. You can attack your cluster regularly to find vulnerabilities and misconfigurations.

Auditing and Logging

Audit log collection and analysis can be beneficial for a variety of reasons.

Logs are useful for determining the root cause of production issues. When a sufficient number of logs are collected, they can also be used to detect abnormal behaviour. EKS transmits audit logs to Amazon Cloudwatch.

The EKS-managed Kubernetes control plane manages audit logs. Amazon provides instructions for enabling and disabling control plane logs for Kubernetes API servers, controller managers, and schedulers.

Scan Images for Vulnerabilities Regularly

Container images, like virtual machines, can contain vulnerable binaries and application libraries. The best way to avoid threats is to scan images regularly with an automated scanner.

Images in the Amazon Elastic Container Registry (ECR) can be scanned automatically or on demand (every 24 hours). Clair, an open-source image scanning solution, is currently used by ECR.

The results of the scan are written to EventBridge’s ECR event stream. The scan results can also be viewed in the ECR console. Vulnerabilities rated as HIGH or CRITICAL should be deleted or rebuilt. When an image that has been deployed becomes vulnerable, it should be replaced as soon as possible.

Network Governance

Pod-to-pod communication is enabled by default in a Kubernetes cluster. Although this flexibility is beneficial during development, it is not considered safe for production.

Kubernetes network policies allow you to limit network traffic between pods as well as between pods and external services. Kubernetes network policies cover layers 3 and 4 of the OSI model.

Network policies identify the source and destination pods using pod selectors and labels, but they can also include IP addresses, port numbers, protocol numbers, or a combination of these.

Key Takeaways:

These are some key takeaways on the basics of Kubernetes deployment and how to secure it on AWS:

➔     Understanding the shared responsibility model—When using managed services like EKS, security and compliance are considered shared responsibilities.

➔     Practise red/blue team and penetration testing—the red team investigates vulnerabilities in various systems, while the blue team defends against them.

➔     Auditing and logging—collecting and analyzing audit logs can help determine the root cause of production issues.

➔     At-rest encryption—Kubernetes provides three AWS native storage options that support data-at-rest encryption.

➔     Scan images for vulnerabilities regularly—vulnerable binaries and application libraries can be found in container images. The best way to avoid threats is to scan images with an automated scanner regularly.

➔     Network policies— identify the source and destination pods using pod selectors and labels.

We at Linux2cloud, hope this will be useful as you secure your Kubernetes deployment on AWS. For Kubernetes and AWS courses, contact us.

Kubernetes and Docker Compose are container orchestration frameworks. Kubernetes runs containers across a network of physical or virtual computers. Docker Compose runs containers on a single host machine. In this blog post, we will compare Kubernetes and Docker-compose.

What exactly is Docker-compose?

Compose is a Docker application for defining and running multi-container Docker applications. Compose uses a YAML file to configure the services in your application. Then, you create and start all of the services specified in your configuration with a single command. Work in all environments, including production, staging, development, testing, and continuous integration workflows, to create work.

The orchestration is configured by Compose using the docker-compose.yml file. It specifies which images are required, which ports must be opened, whether they have access to the host filesystem, which commands must be executed upon startup, and other information. A docker-compose.yml file that incorporates a database into the stack while still using Dockerfile. The docker-compose.yml file looks like this:

version: ‘3’

services:

  web:

    build: .

    ports:

     – “8080:80”

  db:

    image: mysql

    ports:

    – “3306:3306”

    environment:

    – MYSQL_ROOT_PASSWORD=password

    – MYSQL_USER=user

    – MYSQL_PASSWORD=password

    – MYSQL_DATABASE=demodb

The docker-compose.yml file will be written once and reused. Create a Dockerfile for a stack element with docker-compose.yml and reuse it for multiple stacks. Dockerfiles are simple text files containing the commands to assemble an image that will be used to deploy containers, whereas Docker-compose.yml files are used to define and run multi-container Docker applications.

As a result, the workflow will work as follows:

1)    Create Dockerfiles to build images.

2)    Using the Dockerfile images defined in docker-compose.yml, build complex stacks (consisting of individual containers).

3)    Deploy the entire stack with the docker-compose command.

Common Docker Compose Use Cases

Docker Compose is a well-known tool for creating a microservice infrastructure environment that connects different services across a network. Docker Compose is used frequently in our test suites to create and destroy isolated testing environments. Furthermore, for scalability, we can look at Docker Swarm, a Docker project that works at the orchestration level, similar to Kubernetes.

In comparison, Docker Swarm has fewer features than Kubernetes.

What exactly is Kubernetes?

“Kubernetes” is a Greek word that means “helmsman” or “pilot,” which explains how the logo came to be. Let us now turn to the technical side of things. Due to the limitations of Docker, Kubernetes enters the picture to fill the gaps in the Docker containerization process. K8s is a containerization orchestration platform that allows you to run dynamically scaling containerized applications and manage them through an API.

The architecture of Kubernetes is straightforward: it consists of Master nodes and Worker nodes, with the Master communicating with the Worker via an API server. Multiple Master nodes may exist to provide High Availability, an important aspect of application deployment and a benefit of Kubernetes.

Kubernetes supports declarative and imperative approaches, allowing us to create, update, delete, or scale Objects using templates. As an example, consider the following deployment template:

apiVersion: apps/v1

kind: Deployment

metadata:

  name: nginx-deployment

  labels:

    app: nginx

spec:

  replicas: 3

  selector:

    matchLabels:

      app: nginx

  template:

    metadata:

      labels:

        app: nginx

    spec:

      containers:

      – name: nginx

        image: nginx:1.14.2

        ports:

        – containerPort: 80

Differences between Kubernetes and Docker-compose

In a nutshell, Kubernetes and Docker are container orchestration frameworks. The primary distinction is that Kubernetes manages containers across multiple computers, virtual or physical, whereas Docker Compose manages containers on a single host machine.

Kubernetes has solved several significant application administration issues, including:

• resource optimization
• Self-healing containers
• Downtimes during application redeployment
• Auto-scaling
• Finally, Kubernetes orchestrates the deployment of multiple isolated containers so that resources are always available and can be distributed optimally.

On the other hand, Docker Compose can configure all of the application’s service dependencies to get started with, say, our automated tests. As a result, it is a potent tool for local development.

Which is better, Docker or Kubernetes?

Seriously, both! Docker can be used on your laptop to create container images, which can then be run on a Kubernetes cluster. Alternatively, instead of Kubernetes, you can use Docker Swarm to orchestrate your containers.

Should you start with Docker or Kubernetes?

If you intend to work with Kubernetes, you should first become acquainted with Docker. Docker will teach you the basics of containers, such as creating an image, running containers, and adding storage and environment variables.

Then connecting Kubernetes concepts like Pods and PersistentVolumes to your container knowledge will be much easier.

Docker-related activities

Docker allows you to do a variety of things, including:

• With a docker build and a Dockerfile, you can create container images (also known as Docker images) for your applications.
• Docker Engine can be used to run your own container images.
• Push images to a private image registry to share with coworkers or other teams.
• Push images to Docker Hub to share them on the internet (a public image registry)
• Use Docker Hub images to run third-party containers such as databases.
• Docker Compose allows you to run multi-container applications.

In addition to these useful developer features, Docker Swarm mode is a utility for managing a cluster of Docker instances. Swarm allows you to manage containers running on multiple servers.

Kubernetes-related activities

What should you do with a Kubernetes cluster once it’s up and running? Why are people interested in Kubernetes?

• Create and deploy your own container-based applications.
• Deploy third-party container-based applications such as databases or web apps.
• Connect your apps to each other, for example, so that your back-end API can communicate with the database, or connect many containers into a microservices architecture.
• Stop existing containers and start new ones with the updated software to upgrade applications.
• Collect metrics on your apps, such as memory and CPU usage.

Learn more about Docker & Kubernetes

Conclusion

In this Blog, we looked at how Docker Compose and Kubernetes differ. Docker Compose can be useful when we need to define and run multi-container Docker applications. Suppose you want to learn how to build and run containers, and install Docker on your laptop. Then, use Kubernetes to orchestrate and run your containers in production! Kubernetes is a powerful but complex framework for managing clustered containerized applications.