DevOps teams are constantly balancing between iterating and improving application development on one hand, and ensuring a smooth and continuous rollout on the other hand. A lot of computing space is needed for scaling apps quickly, which can take a toll on budget. The need to configure applications for each operating system and computing environment can hold DevOps teams back and decrease productivity.
Containerization is a great solution for boosting DevOps productivity by allowing the application to run on all environments and operating systems, using very little computing resources. This makes for easier deployment and configuration, saving DevOps teams countless hours.
Read on to learn more about:
- What is containerization
- The difference between VMs (Virtual Machines) and containers
- How containers help DevOps teams be more productive
- The security of containerized applications
- The best containerization tools for DevOps teams
What is containerization?
Most of the applications we use today rely on microservices. This means that they are actually made up of smaller, discrete applications that communicate with each other but are not dependent on one another. This makes it easy for developers to quickly change one small part without affecting the whole application.
To help them do just that, developers use containers. Containers bring together all of the small parts together into one highly portable package. Critically, containers are abstracted from the actual operating system, taking just what it needs from the system in order to run the application. Instead of running directly from the operating system, containers are a kind of virtualization. The application runs as a container image in an isolated user space.
You can think of containers as packing together smaller applications in a more space efficient way. The same way a shipping container consolidates thousands of small items into a neat package for effective storage and transport, the containers we are talking about are an efficient way of consolidating thousands of smaller applications. This makes the application easy to “transport” around, which in this case means to run on different operating environments.
A container includes all of the binaries, libraries, and configurations that an application needs to run. It does not include virtualized hardware or kernel resources. The reason for this is that containers share the same basic kernel — or core — of an operating system. The reason it is still able to run without being configured to a specific operating system is because it only takes what it needs from the kernel, and abstracts the resources that it takes. The container is not dependent on the operating system or underlying infrastructure, because it only needs a small part in order to run.
Containers only take what they need from the system and only include the basic components and dependencies of the application. This allows containers to be incredibly lightweight in terms of storage space, and faster than other abstraction tools in terms of the amount of computing power it requires to run containerized workloads.
What came before: Virtual machines vs containers
Containers are a powerful tool that help drive efficiencies in DevOps teams throughout the product lifecycle. To understand just how critical containers are to smooth management and deployment of applications, it’s useful to look back at what developers used before containers.
A large problem for DevOps teams has always been how to manage configurations for different operating systems and development environments. Before containers, DevOps teams deployed, configured, and managed applications on bare-metal servers. Bare-metal servers are actual, physical servers, unlike cloud providers or virtual machines.
Because everything was done on bare-metal, DevOps teams needed to configure applications for each and every operating system separately. Once an operating system was updated — which happens quite frequently — the DevOps team would need to reconfigure and update the application. Then, anytime the application itself received an update, the team would have to reconfigure the updated application for all the operating systems again.
This process was too clunky and time consuming, so DevOps teams sought a solution. One solution that people still use today is another kind of virtualization: A virtual machine. A virtual machine is an abstraction of an operating system that is layered onto a host operating system. An example of a virtual machine is Ubuntu for Windows. Ubuntu allows Windows users to run the Linux operating system when needed, without having to completely uninstall Windows and rely on Linux alone.
While virtual machines are separate from the host operating system, containers share the host operating system’s kernel. Virtual machines abstract the operating system as a whole, while containers only abstract the application itself.
The problem with virtual machines is that because they are an entire operating system, they provide a lot more computing power than necessary to actually run the application. Virtual machines are notoriously slow, and still represent just one operating system. In contrast, containers allow for a faster runtime, are resource efficient, and allow the application to run on multiple operating systems.
How do containers boost DevOps productivity?
A common challenge that DevOps teams face is getting an application to work across multiple environments. A developer will run the application in one specific environment and it will work great, but will suddenly be full of bugs in another environment.
The reality is that very little in software development or operating systems is standardized. Each company produces their own computing environments that require special configurations. Containerization eliminates this problem by abstracting the resources needed to run the application, so it can run anywhere.
Common use cases for containers include:
- Microservices Architecture: Microservices are network of small, independent applications that communicate with each other to create one application for the user. Containers easily facilitate microservices because they can easily deploy isolated units of code.
- CI/CD (Continuous Integration/Deployment): Containers facilitate automation, which is crucial to continuous integration and deployment. Containers help reduce dependency issues because each container is independent of the other. Containers are also used for continuous integration and deployment because they minimize resource consumption, making it easier to quickly deploy new features.
- Modernizing legacy apps: Modernizing legacy apps so they can run on the cloud is not a simple process. Because containers abstract out the application, DevOps teams can use them to run a legacy application on the cloud without changing the application itself.
The benefits of containerization go beyond these use cases. Using containers can immediately boost DevOps productivity as well as reduce costs in any application.
Because containers use the operating system’s kernel, they are lightweight and take up very little server space. Using containers can drastically reduce server and licensing costs. Unlike a virtual machine that can take minutes to start up, a containerized application takes only a few seconds. Containers optimize disk space, making it simple for DevOps teams to share the application and deploy on any device.
Containerized applications have a high level of portability because they can run on any operating system, saving DevOps teams thousands of hours configuring and reconfiguring applications for different operating systems. Containers are typically less expensive than virtual machines because they do not require their own operating system kernel.
Containers are resource efficient. Containers automatically maximize cloud resources, which can drastically cut down on cloud-based costs. When one container isn’t maximally utilizing computing resources, those resources are automatically given to the next container. This not only cuts down on resource usage, but also delivers a smooth experience for the end user.
Another way that containerization helps DevOps team save time is that rollbacks and fault isolation are quicker than in traditionally deployed applications. Because containers are independent from each other, when one container fails, it doesn’t create a domino effect that brings the other containers down as well. Therefore, DevOps teams can simply address the fault in the specific failed container, instead of debugging the whole system.
Scalability is a concern for every company, from startup to corporation. Containers make it simple for DevOps teams to quickly scale applications with little disruptions to the user. To scale a containerized application, all you need to do is copy the container. Container orchestration tools like Kubernetes can scale containerized applications automatically.
Using containers means that DevOps teams are able to develop, deploy, and package applications more quickly. Containerization eliminates the need for DevOps to consider different production environments. Instead, there is only one computing environment — the container, and everything the development team needs is in that container. Once an application scales, however, the number of containers needed increases exponentially. Container orchestration platforms help manage and scale the container ecosystem.
Orchestration automates the creation of new containers and removes existing containers. DevOps teams can set predefined rules regarding resource utilization, and the orchestration tool will then balance CPU and RAM usage automatically. Container orchestration also performs load balancing across all containers to ensure the most efficient performance. Container management is important because as an application scales it becomes harder to manage every single container.
Container orchestration platforms are the ultimate productivity tool for DevOps, because it automates the management of all the different containers. It can automate the process of continuous integration/deployment, and restart failed containers. Not only does this save time, but it also reduces the potential for human error and lengthy downtime.
Are containerized applications secure?
Security is a central concern at every level of the organization. Not only do development teams need to worry about the security of their code and other company assets, but they need to take into account the security of user data.
Although containers are isolated, they are not automatically secure. A containerized application can contain vulnerabilities that expose the system to malware attacks just like any other application. When software development first started using containers, the leading wisdom was that virtual machines were more secure. That’s because with virtual machines, a hypervisor is isolating the machine from the entire operating system, which keeps the host operating system safe. Containers, however, share an operating system with its host, leaving the operating system exposed to attacks.
There are two advances in container technology that make containers more secure than ever. Recent improvements in Linux have made the kind of isolation that containers provide as efficient as virtual machines, isolating them almost completely from the host operating system.
Container orchestrators also provide security tools by allowing for faster software patching and automatic isolation and recovery of faulty containers.
The best containerization tools for DevOps teams
Using containers to develop applications is a great way for DevOps teams to be more efficient and more productive. Luckily, containers have been around for a while, and the technology has improved significantly in the past few years as a result of cloud services. Many containerization tools are cloud-native and open-source. These developer tools were chosen because they have powerful features and integrations.
We’ve put together a list of some of the best containerization tools for DevOps teams. First we’ll provide a list of container engine software, and then some popular container orchestration tools. Finally, we’ll provide a list of container networking software.
The best container engine software:
Container engines are what create the containers themselves.
- Docker: Docker is perhaps the most widely used and known container software. It’s easy to download and free to use if you don’t mind storing your container images on a public repository. That may be fine for playing around, but DevOps teams will want the paid version that provides more security.
- Oracle Cloud Infrastructure Compute: As the name suggests, Oracle doesn’t strictly provide container software options. Instead, their cloud infrastructure includes bare-metal, virtual machine, and cloud options in addition to containers.
- IBM WebSphere Hybrid: This is a great tool for any DevOps team that wants to use containers to modernize legacy Java applications. They offer container solutions for on-premises and public cloud environments.
The best container orchestration software:
Container orchestration software manages multiple containers for automatic continuous integration/deployment, debugging, and keeps everything secure.
- Docker Swarm: Swarm is run directly on the Docker engine, and can only be used with a docker container. It doesn’t provide full automation, so it may not be the best tool for driving efficiency for large teams, but it can be useful for startups who are just starting out with containerization.
- Kubernetes: Kubernetes has been doing container orchestration the longest. It was originally designed by Google, but is now maintained by the Cloud Native Computing Foundation. Because they’ve been doing it for the longest, Kubernetes has a lot of support and user generated content. The Kubernetes API is extensive, to enable multiple integrations.
- Google Kubernetes Engine (GKE): GKE is an enterprise-grade version of Kubernetes. The main benefit of GKE is that it is secure by default, so you never have to worry about the security of your containerized applications.
- Red Hat OpenShift: OpenShift is a kubernetes tool specifically designed for hybrid cloud deployment. It provides smooth application delivery to hybrid cloud, multi-cloud, and edge deployments.
- AWS Fargate: AWS Fargate by Amazon is a tool for Amazon’s other containerization platforms ECS and EKS. Fargate allows users to run containers without worrying about servers or clusters.
The best container networking software
Container networking software helps to manage IP addresses and create isolated networks for containers. This software is all about connecting your isolated containers to a larger network.
- Codefresh: Provides continuous delivery for cloud-native applications. Some of the biggest DevOps teams at Monday.com, GoodRx and more use this tool.
- VMware NSX Data Center: NSX enables entire networks to be embedded in a hypervisor layer, which further abstracts the container from the operating system.
- NGINX: NGINX is a completely open-source platform used by Netflix, Starbucks, McDonalds, and others to connect containerized applications.
Building applications in containers is a great way to increase productivity in DevOps teams and create more efficient workflows. Containerized applications use little computing resources, are small in disk size, and can be deployed on any computing environment without the need for time-intensive configurations. With the advances in container technology, it’s easier and more secure than ever to develop applications using containers.
Using the right technology is important for DevOps productivity, but time management tools can be equally as important in making sure that everyone is as productive as possible. Clockwise provides smart scheduling features to automate your whole team’s calendar. Uninterrupted Focus Time is protected from meetings and other distractions, so your team can get the work done. Flexible Meetings automatically schedule themselves to address conflicts and optimize for your meeting preferences.