Linux containers are hugely complicated and not user-friendly. Having realized the fact that several complexities are coming in the way of massively producing and fluently using containers, an open-source project got initiated with the goal of deriving a sophisticated and modular platform comprising an enabling engine for simplifying and streamlining various containers' lifecycle phases. That is, the Docker platform is built to automate the crafting, packaging, shipping, deployment and delivery of any software application embedded inside a lightweight, extensible, and self-sufficient container.
Docker is being positioned as the most flexible and futuristic containerization technology in realizing highly competent and enterprise-class distributed applications. This is to make deft and decisive impacts as the brewing trend in the IT industry is that instead of large monolithic applications distributed on a single physical or virtual server, companies are building smaller, self-defined and sustainable, easily manageable and discrete ones. In short, services are becoming microservices these days to give the fillip to the containerization movement.
The Docker platform enables artistically assembling applications from disparate and distributed components and eliminates any kind of deficiencies and deviations that could come when shipping code. Docker through a host of scripts and tools simplifies the isolation of software applications and makes them self-sustainable by running them in transient containers. Docker brings the required separation for each of the applications from one another as well as from the underlying host. We have been hugely accustomed to virtual machines that are formed through an additional layer of indirection in order to bring the necessary isolation.
This additional layer and overhead consumes a lot of precious resources and hence it is an unwanted cause for the slowdown of the system. On the other hand, Docker containers share all the resources (compute, storage and networking) to the optimal level and hence can run much faster. Docker images, being derived in a standard form, can be widely shared and stocked easily for producing bigger and better application containers. In short, the Docker platform lays a stimulating and scintillating foundation for optimal consumption, management, and maneuverability of various IT infrastructures
The Docker platform is an open-source containerization solution that smartly and swiftly automates the bundling of any software applications and services into containers and accelerates the deployment of containerized applications in any IT environments (local or remote systems, virtualized or bare metal machines, generalized or embedded devices, etc.). The container lifecycle management tasks are fully taken care of by the Docker platform. The whole process starts with the formation of a standardized and optimized image for the identified software and its dependencies. Now the Docker platform takes the readied image to form the containerized software. There are image repositories made available publicly as well as in private locations. Developers and operations teams can leverage them to speed up software deployment in an automated manner.
The Docker ecosystem is rapidly growing with a number of third-party product and tool developers in order to make Docker an enterprise-scale containerization platform. It helps to skip the setup and maintenance of development environments and language-specific tooling. Instead, it focuses on creating and adding new features, fixing issues and shipping software. Build once and run everywhere is the endemic mantra of the Docker-enabled containerization. Concisely speaking, the Docker platform brings in the following competencies.
- Agility: Developers have freedom to define environments and the ability to create applications. IT Operation team can deploy applications faster allowing the business to outpace competition.
- Controllability: Developers own all the code from infrastructure to application.
- Manageability: IT operation team members have the manageability to standardize, secure, and scale the operating environment while reducing overall costs to the organization.
Precisely speaking, Docker containers wrap a piece of software in a complete filesystem that contains everything needed to run: source code, runtime, system tools, and system libraries (anything that can be installed on a server). This guarantees that the software will always run the same, regardless of its operating environment:
Containers running on a single machine share the same operating system kernel. They start instantly and use less RAM. Container images are constructed from layered filesystems and share common files, making disk usage and image downloads much more efficient.
- Docker containers are based on open standards. This standardization enables containers to run on all major Linux distributions and other operating systems such as Windows and macOS.
There are several benefits being associated with Docker containers as enlisted below.
- Efficiency: Containers running on a single machine all leverage a common kernel so they are lightweight, start instantly and make more efficient use of RAM.
- Resource sharing among workloads allows greater efficiency compared to the use of dedicated and single-purpose equipment. This sharing enhances the utilization rate of resources
- Resource partitioning ensures that resources are appropriately segmented to meet up the system requirements of each workload. Another objective for this partitioning is to prevent any kind of untoward interactions among workloads.
- Resource as a Service (RaaS): Various resources can be individually and collectively chosen, provisioned and given to applications directly or to users to run applications.
- Native Performance: Containers guarantee higher performance due to its lightweight nature and less wastage
- Portability: Applications, dependencies, and configurations are all bundled together in a complete filesystem, ensuring applications work seamlessly in any environment (virtual machines, bare metal servers, local or remote, generalized or specialized machines, etc.). The main advantage of this portability is it is possible to change the runtime dependencies (even programming language) between deployments. Couple this with Volume plugins and your containers are truly portable.
- Real-time Scalability: Any number of fresh containers can be provisioned in a few seconds in order to meet up the user and data loads. On the reverse side, additionally provisioned containers can be knocked down when the demand goes down. This ensures higher throughput and capacity on demand. Tools like:
- Docker Swarm
- Kubernetes (https://kubernetes.io/)
- Apache Mesos(http://mesos.apache.org/)
- DC/OS (https://dcos.io/)
To name but a few of the clustering solutions which further simplify elastic scaling
- High Availability: By running with multiple containers, redundancy can be built into the application. If one container fails, then the surviving peers – which are providing the same capability – continue to provide service. With orchestration, failed containers can be automatically recreated (rescheduled) either on the same or a different host, restoring full capacity and redundancy.
- Maneuverability: Applications running in Docker containers can be easily modified, updated or extended without impacting other containers in the host.
- Flexibility: Developers are free to use whichever programming languages and development tools they prefer.
- Clusterability: Containers can be clustered for specific purposes on demand and there are integrated management platforms for cluster-enablement and management.
- Composability: Software services hosted in containers can be discovered, matched for, and linked to form business-critical, process-aware and composite services.
- Security: Containers isolate applications from one another and the underlying infrastructure by providing an additional layer of protection for the application
- Predictability: With immutable images, the image always exhibits the same behavior everywhere because the code is contained in the image. That means a lot in terms of deployment and in the management of the application lifecycle.
- Repeatability: With Docker, one can build an image, test that image and then use that same image in production.
- Replicability: With containers, it is easy to instantiate identical copies of full application stack and configuration. These can then be used by new hires, partners, support teams, and others to safely experiment in isolation.