A cloud computing container is a wrapped, lightweight runtime environment that enables applications and their dependencies to operate uniformly across multiple public clouds. Containers virtualize everything an application requires to execute, such as system tools, libraries, and configuration, all into a single container image.
Unlike traditional virtualization, a container image shares the host operating system (kernel). This helps to ensure high performance and efficient resource utilization for cloud-native applications.
Containerized applications can be traced back to the 1980s when the chroot system was created for UNIX; chroot worked in virtual isolation in an isolated environment, just like containers in cloud computing. The term containers became mainstream with the release of Docker in 2013.
Docker utilized existing Linux kernel features like namespaces and cgroups to provide lightweight operating system-level virtualization. It was easy to use and has significant performance benefits over virtual machines.
Join us as we learn more about container workloads and discover how containers power the serverless cloud revolution.
Container Technology vs. Virtual Machines
The main distinction between virtual machines and containers is their architectural design and resource utilization. VMs are fully self-contained units within the physical hardware of a host. In contrast, containers share certain central resources while maintaining separate environments within physical hosts.
A virtual machine utilizes software and the host server hardware to establish an abstraction layer between the host’s physical resources and the underlying OS (virtual operating system). The host’s CPU, memory, storage, and other components are partitioned into isolated virtual environments, allowing its complete operating system and applications.
VMs provide a heightened level of isolation and security. With each VM running its own operating system, vulnerabilities or system failures in other guest OS have no impact on other VMs. Furthermore, unlike containers, VMs offer the flexibility to run various operating systems, making them valuable for applications requiring different OS environments.
Containers, and virtual machine containers, however, also provide an isolated environment for applications to run, but they are more lightweight and efficient. Unlike VMs, containers share the host system’s underlying OS kernel and do not require a complete OS within each instance. Containerized applications house the application and its dependencies (OS or load libraries, binaries), translating to lesser resources and quicker start times.
Containers have a clear advantage in terms of performance. They impose less overhead because they don’t require a full OS to function. As a result, they boast faster startup times and enhanced portability, thanks to their smaller size.
Managing VM Operating System and Containers
In terms of management, VMs traditionally require management of each container engine and virtual environment. Modern hypervisors and virtualization management tools have eased this, but it can still be a significant task. However, orchestrators like Kubernetes offer a highly automated, flexible, and efficient container management system.
If an application requires running on a different platform or needs high isolation and security, VMs may be a better option. If efficiency, portability, and performance are key drivers for your business, especially if you follow DevOps practices and CI/CD pipelines, containers have the edge.
How Cloud Containers Work And Their Benefits
When an application is run in a container, the container encapsulates everything the application needs to run, including code, runtime, system tools, system libraries, file storage, or container images. This is abstracted away from the underlying infrastructure, guaranteeing that the application will run in any environment.
Cloud Containers interact with a shared operating system on the container images host server through a container runtime environment such as Docker, K8s, and RTK. Orchestration tools like Kubernetes schedule cloud containers to run on a cluster, manage workloads, ensure traffic flow, and oversee security and database functions.
Benefits of Cloud Containers
- Portability and Consistency: A key advantage of sizing cloud containers is their ability to create consistent environments. A containerized environment runtime creates an identical climate that can be run anywhere; on-premises, public cloud, or private cloud. The containerized apps’ runtime will work on a Linux host OS, a Windows host OS, or even a Mac machine OS kernel.
- Scalability: Containers provide effortless scalability, allowing you to adjust resources based on application demands quickly. Containers are rapid and consume very few resources. As a result, scaling up and down clusters is rapid.
- Efficient Resource Utilization: By leveraging the host system software, containers enable developers to optimize resource utilization and consume fewer resources than VMs. This effectively allows you to accommodate more applications within a single physical server than virtual machines.
- Microservices Architecture: Containerization is ideal for microservices architecture, as each service can be developed, updated, and scaled independently in its container.
- CI/CD Integration: Containers seamlessly integrate into continuous integration and continuous deployment (CI/CD) pipelines. Developers can swiftly create, tend then deploy containers and applications with enhanced speed and reliability.
- Isolation: Each container operates independently of others, so issues or vulnerabilities in one do not directly affect another.
What Is a Container in the Cloud?
When we talk about containers in the cloud, we are referring to deploying this technology in cloud environments. Cloud providers offer services that organize, run, and manage cloud containers. The Atlantic.Net Cloud Platform (ACP) is perfect for hosting a Docker runtime environment; choose the host you want and build your containers in the cloud. We even offer super simple 1-click Docker deployments, and our blog has extensive documentation on how to run various types of Docker containers on ACP
If you prefer container orchestration platforms, there are several options available. The cloud provider AWS has its Elastic Container Service (ECS) and Elastic Kubernetes Service (EKS), Google Cloud offers the Google Kubernetes Engine (GKE), and Azure provides Azure container instances via the Azure Kubernetes Service (AKS). However, consider your cloud billing, as these individual container orchestration services can be costly.
Using containers in the cloud allows organizations to make the most of public cloud infrastructure resources, offering benefits such as scaling, load balancing, and seamless application deployment and updating mechanisms.
Containers and Batch Processing
Containerization has brought a transformative change to many areas of computing, including batch processing. Batch processing refers to the execution of a series of tasks (or jobs) without manual intervention. Containers have become increasingly prevalent in batch processing due to their isolated, lightweight, and portable nature.
Containers allow individual tasks to be packaged along with all their dependencies, ensuring consistent execution across various environments.
Cloud Containers provide an isolated environment for each job, eliminating the potential conflict of resources between different jobs. This can be particularly crucial if cloud-native applications require different versions of a certain library, which might conflict if run on the same machine.
Efficiency and Speed
Containers are lightweight and start quickly. This is a significant advantage in a batch processing environment, where tasks need to start and stop frequently. This efficiency enables more jobs to run on the same hardware, improving overall system utilization.
A batch job can run on any system that supports container runtime, whether it’s a local server or a cloud environment, without worrying about differences in underlying hardware infrastructure.
With containers, batch jobs can be scaled horizontally with ease. Container orchestration tools like Kubernetes can automate the process of starting additional containers as needed based on the load or schedule.
Cloud Containers ensure that batch jobs are run in a consistent environment, from development to testing, to production. This Consistency helps eliminate bugs caused by discrepancies between different environments and reduces the time spent on debugging and resolving such issues.
Understanding the fundamentals of container networking can help businesses ensure efficient and secure inter-service communication.
Container Network Models
There are several network models that containers can use. In the Docker container ecosystem itself, for instance, there are five network drivers:
- Bridge: This is the default network driver. If you don’t specify a driver, Docker creates a bridge network for you. Each container connected to this network gets its own IP address on a subnet internal to the host.
- Host: Removes the network isolation between the container and the Docker host, using the host’s networking directly.
- Overlay: This is used when creating a Swarm (a group of Docker hosts networked together) for distributed networks across multiple hosts or cloud providers.
- Macvlan: Assigns a MAC address to each container’s virtual network interface, making it appear as a physical device on your network.
- None: This provides a container with a network stack but no interfaces to connect with other containers.
In a dynamic container environment, service discovery is essential. Service discovery mechanisms configure the deployment environments that allow containers to find and communicate with each other.
Network Policies and Security
Network policies define how groups of containers are allowed to communicate with each other and other network endpoints. They act like firewall rules for specific pods. In Kubernetes, the Network Policy API allows the creation of policies to control network traffic direction at the Pod level.
When you deploy workloads, load balancing is a crucial concept when distributing network traffic across multiple containers to ensure no single container becomes a bottleneck.
Running Containers on Atlantic.Net
With Atlantic.Net, you can effortlessly deploy and manage your containerized applications with a choice of seven data centers. We support popular container runtimes like Docker offering you the flexibility to choose the tools that best suit your needs. Whether you’re running on Linux, Windows, or Unix, our container platform always ensures reliable service.
Join us today and tap into the container revolution. Discover the power and flexibility of running containers on the ACP cloud platform, and unlock new possibilities for your cloud-native applications.
Don’t miss out on this opportunity – get started now!