Containers have been in the market for over a decade, and it is estimated that by 2025 over 85% of the organizations will containerize their applications. It is one of the driving technologies that is helping organizations adapt to the latest technological innovations quickly. It is not a rare occurrence to hear the name in organizations that are DevOps enabled.
Containers are an important tool that helps with smoothening the interactions between the various environments be it development or staging, thereby saving a lot of time, efforts, money, and resources. Let's visit the role of the containers in DevOps.
Table of Contents:
What are Containers?
In simple words, containers are software package units that contain relevant code and its dependencies. It can run across various computing environments.
A rough timeline of Containers’ evolution:
The onset of container technology
It became popular with the introduction of system partitioning
This was the renaissance period in the history of container technology
The emergence of Dockers - a game-changing technology with an easy-to-use GUI interface that redefined containers forever
Kubernetes – Container management technology that has made containers even more popular than before
The Popularity of Containers in DevOps
These days almost every organization follows DevOps practices. DevOps started around when flicker came up with “10+ Deploys Per Day: Dev and Ops Cooperation” around 2009 and is still going strong. Continuous Integration and Continuous Delivery (CI/CD) is at the core of the DevOps mindset.
- CI (Continuous Integration): Automatic building and compiling of code that assists teams with early detection of technical issues.
- CD (Continuous Delivery): It is a way of getting all the changes- bug fixes, configuration changes, new feature additions, and more in a production environment safely, quickly, and sustainably.
Containers improve the CI/CD process and fasten the production rate.
Several times you might have seen applications crashing when they are moved from one environment to another. For example, let’s say an application broke down while moving the code from the development environment to the staging/UAT environment. These issues are mainly due to configuration mis-settings, missing libraries, or dependencies. Containers provide OS-level virtualization i.e., the code/application becomes OS distribution independent. It contains all the necessary dependencies and configuration settings to fight against any breakage due to change in the computing environments.
Other important reasons why containers are essential in your CI/CD process – They enable the DevOps mindset and bring the Development and Operations teams together to solve the problem of the last mile.
- Easy Integration: Flexibility to integrate with existing technology.
- Production: Helps with faster deployment, patching, and application scaling.
- Consistent: Enables higher system consistency due to no dependence on the system configuration.
- Resource: Lightweight in nature which means it shares the machine’s kernel and does not need the frequent association of OS with applications thus saving a lot of computational resources.
What is Application Containerization?
Application Containerization would mean OS-level virtualization to run and deploy distributed services. In other words, multiple applications can use the same OS kernel on a single system.
Application containerization helps to increase:
Containerized application can be used across any system without any code change provided the systems are using a uniform operating system.
Since the code remains the same with the dependencies, file systems, and binaries, they are considered a single image. One can even do version control at this image level.
So how does application containerization work?
Application containers have files, environment variables, libraries, and other dependencies to run the software. This information is gathered in the form of an executable image. These images then get deployed by the container engine.
Docker: It helps with application containerization. They are usually lightweight executable standalone container image that packs everything required to run an application. They are one of the crucial DevOps tools in the market.
Docker Swarm – This tool helps with the scheduling and clustering of containers. It helps teams to manage Docker clusters as a single virtual system.
System Container: System container is one of the oldest forms of container technologies. It is a standalone OS associated solution that runs without specialized software like Dockers.
Scalability and Orchestration
As organizations grow systems become more and more complex hence comes the dire need to scale the containers. There are various options to scale:
- Kubernetes: It is an open-source tool developed by Google. It is a cluster container management and deployment tool that is used to scale containers. Kubernetes can assist with scheduling any numbers of replicas of the containers as a group of a single node for fast software module production.
- Cloudify’s Docker Orchestration Tool: It is an orchestration tool by Cloudify that helps developers with describing – complex topologies, middleware tier, application layers and so on.
Some of the best practices for container scalability and orchestrations are:
- Investing time in understanding the architecture of your container-based application.
- Understanding your application’s scalability- via implementing proof of concepts with workloads and massive data.
- Focusing on the security aspects - as they need to scale well with your applications.
This section will cover some of the popular tools that are used to execute different container-related activities.
Tools for running the containers:
Docker: It is one of the top tools for running containers and we have covered it in earlier section.
CRI-O: It is an open-source and exceptionally lightweight tool that is used to implement the runtime interface of a container.
Microsoft Containers: They are equipped with various tools for running, developing, and publishing Docker images in windows environment.
Tools for cluster management and deployment:
Kubernetes is top in the chart that we have already covered in the above section.
Apache Mesos: It is a computational resource abstraction tool that can run Docker and rkt images simultaneously inside the same cluster. DC/OS acts as the data center for this tool.
Docker Swarm: We have discussed about it in earlier section.
Container Storage Tool:
BlockBridge: It is a storage platform that uses Docker, Kubernetes, OpenStack for safe storage.
EMC: It is a free and open-source tool that uses a code library for storage purpose.
Container Security Tool:
Twistlock: A Docker image is usually the combination of an operating system, servers, and many software components. Securing those multiple constituents becomes harder and harder. Twistlock’s vast database can audit the docker image for major threat and vulnerability detection.
Aporeto: Through this tool, you can program and enforce security policies as per your requirements. The main purpose of this tool is to encrypt the workloads between the containers.
Container Use Cases
Some of the popular container use cases are:
They smoothen – deployment and scalability of any distributed applications, including microservices.
Platform as a Service:
They provide the platforms to help developers get rid of the infrastructure management requirements and help with – application management and deployment.
With containerization, you can easily perform batch processing jobs. All these jobs are packed into a container and you can define the containers to start those jobs and even scale them as per your environment.
How is it Different from Virtual Machines?
To begin with, both are different technologies and have different purposes. We will focus on two major differences between the containers and virtual machines that might help you with decision making. They are:
They virtualize on the OS level. That means each container would have one application and related dependencies.
Virtual Machines are about virtualizing physical hardware. Here the host machine runs the virtual machine, its dependencies, and libraries.
For example, a host machine like Linux can run multiple types of virtual machines like Windows, Apple iOS, and so on.
They are fast, flexible, and uses fewer server/computer resources.
Virtual Machines use more resources in comparison.
Containers help organizations to deploy products faster, reduce their cycle time while keeping the product quality intact. If anything, the popularity of containers will increase as more and more organizations are turning to a DevOps mindset.
If making your applications reliable and resource optimal is one of your top priorities, then talk to us. Our DevOps CoE team would help with defining your end-to-end containerization strategy and implementation.