Virtualization is key to improved scalability for many organizations. Virtual machines and containers are the two most popular visualization approaches. However, deciding between VMs and containers has been a riddle to many. Here is a cyclopedic one-on-one of VMs vs containers for you.
2. Agenda
VMs vs. containers: An overview
Minutes versus milliseconds
Portability across environments
Infrastructure management
Concurrent workload execution
Security & compliance
Risk management
DevOps impact
Learning curve
3. VMs vs. containers: An overview
Virtual Machines Containers
VMs achieve
virtualization at the
hardware level with a
hypervisor that
virtualizes the
processor, RAM,
storage, network, etc.
Containers achieve OS-
level virtualization.
There is a kernel on top
of the hardware, which
helps communicate
hardware with software.
A virtual machine is
isolated from a server or
a machine.
Containers are isolated
forms of processes.
4. Minutes versus milliseconds
As you can observe from the graphical representation below, latency for writer operations of containers
is around 6 ms, and VMs have a latency of 10 ms for 80,000 transactions.
5. Minutes versus milliseconds
With a similar setup, the results for read operations indicated that VMs have a latency of 11 ms and
containers have a latency of 7 ms.
6. Virtual Machines Containers
Provide the virtualization of hardware, and that is
why it has less portability.
Pack microservices and all their dependencies
inside a small package that is portable across
environments.
Have less mobility due to individual OS, apart from
the hardware mobility issues.
Portability across environments
7. Infrastructure management
With VMs, there are several copies of OS which consume a lot of RAM, CPU, and disk space.
The structure of VMs will have a host OS on top of hardware and a hypervisor.
On the other hand, due to the modularity of container architecture and lower memory footprint, scaling either the
Python app or Node.Js app individually is easy.
Another essential benefit of choosing containerization is optimal resource allocation. Even if some containers are not
using the CPU storage, it is automatically allocated among other containers.
9. Concurrent workload execution
When you compare VMs vs. containers for executing concurrent requests, containers have the
advantage of process isolation.
Containers allow you to process concurrent requests simultaneously with the isolation of each
service.
It also has less overhead compared to VMs for concurrent workload execution.
10. Virtual machines have isolated OS environments, so data security is higher.
However, applications running on VMs are susceptible to cyberattacks due to
old packages.
On the other hand, containers share OS, so infections to one container can
affect the entire system.
However, despite having a shared OS, containers have less exposure than
VMs.
This is due to short-lived workloads, which typically last for days or hours, and
frequent security updates.
Security & compliance
11. Risk management
Containers do a better job of leaving a data trail for effective monitoring when comparing VMs vs.
containers for risk management.
Every container engine executes push and pulls of container images from the registry, leaving a
trail that can be logged and monitored for risk assessment.
VMs lack fault tolerance.
Failure of VMs on one server in the cluster triggers restart of OS on a new server affecting the
entire app.
Apart from this, VMs have a single point of failure due to shared OS.
12. DevOps impact
VM virtualization allows teams to maximize gains through parallelism.
For example, teams can test features in real-time while developing them parallelly.
On the other hand, containerization improves test performance for DevOps teams through
simulated environments.
Containers provide process isolation through a lightweight image that contains app binaries.
So, comparing the intensity of impact on DevOps for VMs vs. containers, containerization has the
edge over virtualization.
13. VMs are the primary management unit allowing developers to focus only on managing
virtualization, snapshotting, and migrating to new abstractions.
At the same time, containers completely change the app architecture and developer
practices.
While VMs just virtualize the machines or hardware, containers bring microservice
architecture into action.
Learning curve