Let’s talk about containers and data centers for a moment. If you need a more agile DevOps team, it’s time to take a closer look at them.
Containers provide virtualization at the operating system level. They are a lightweight approach to virtualization that provides the bare minimum for an application to run and function as intended. You can think of containers as similar to a virtual machine, one not running on a hypervisor, which typically includes applications and libraries.
The Advantage of Using Containers
Containers are large and usually measured in tens of megabytes, and it only takes 1 to 2 seconds to provision one. As the load increases, new containers can easily be created. When the load declines, containers can easily be deleted. If you need to update a container, all you have to do is modify the configuration file and then create a new container.
Even though virtual machines and containers share some characteristics, containers are not virtual machines. Here are some significant differences setting them apart.
- Virtual machines contain a complete operating system and applications.
- Hypervisor-based virtualization is resource intensive, with a VM potentially taking up several GBs in storage.
- Virtual machines use hypervisors to share and manage hardware while containers share the kernel of the host OS to access the hardware.
- Virtual machines have their own kernel and they don’t use and share the kernel of the host OS, which means they are isolated from each other.
- Virtual machines residing on the same server can run different operating systems. One VM can run Windows while the VM next door might be running Linux.
- Containers are bound by the host operating system; for example, containers on the same server use the same OS.
- Containers are virtualizing the underlying operating system while virtual machines are virtualizing the underlying hardware.
7 Reasons to Use Containers versus VMs
- As mentioned above in the preceding list, the average container size is within the range of tens of MBs while VMs can take up several gigabytes. This means a server can host significantly more containers than virtual machines. Running containers is less resource intensive then running VMs so you can add more computing workload onto the same server.
- Provisioning containers only take a few seconds or less, which means your data center can respond quickly to spikes in usage.
- Containers are easily packaged, lightweight and designed to run anywhere—giving you the ability to easily allocate resources to processes and run your application in various environments.
- Containers let you embrace agile development, by decreasing the time needed for development, testing, and deployment of applications and services.
- Testing and bug tracking are also easier because there is no difference between running your application locally, on a test server, or in production.
- Containers are cost-effective. They can potentially help you to decrease your operating cost (less servers, less staff) and your development cost (because your team needs to develop for one consistent runtime environment).
- Container-based virtualization is a great option for microservices and continuous deployment.
- You can run multiple containers in a single VM.
There are many types of containers—stateless, stateful, data applications, and enterprise applications—but all require access to data storage. The challenge is maintaining persistent data, managing different workloads, and accelerating application and microservice performance.
Try to Contain Your Excitement
To complete this two-part series, stay tuned till next week to learn about automated access to data storage for container pods, Kubernetes for containers and how DataCore’s storage management software relates to container management.
For now, schedule a live demo to discover first-hand how new features in PSP7, SANsymphony and Hyperconverged Virtual SAN can accelerate your development and deployment for greater agility and application performance!