Containers vs Virtual Machines (VMs): What’s the Difference?

In cloud computing, a prevailing topic is the distinction between “virtual machines” and “containers.” A Virtual Machine is a software-based emulation of a computer, running an operating system and applications as if they were on physical hardware. Containers, on the other hand, encapsulate an application and its dependencies in a consistent environment that can run across various computing environments. For effective cloud infrastructure management, grasping this differentiation is crucial.

What are Virtual Machines (VMs)?

Virtual Machines (VMs) are computer systems emulated on physical servers, each operating its OS and designated resources. Managed by hypervisors, VMs operate with complete OS isolation, suitable for applications with specific OS requirements. For example, a VM could run a Linux environment on a host machine that’s using Windows, ensuring compatibility for Linux-specific software. VMs have an extensive history, and their infrastructure is supported by established tools like VMware, Hyper-V, and Oracle VirtualBox.

What are Containers?

Containers are units that package an application and its dependencies. Unlike VMs, they utilize the host system’s OS. Containers are designed for efficient resource use, fast startup, and scalability across environments. If you’re developing a Node.js application with certain library dependencies, you can use a Docker container to encapsulate and run the application consistently across multiple stages of development and deployment, irrespective of discrepancies in the local environment. Docker, Kubernetes, and OpenShift are prominent tools in the container ecosystem, streamlining deployment and orchestration.

Distinguishing Virtual Machines vs. Containers:

So what is the difference between virtual machines and containers? At the architectural level, VMs run their OS, leading to full isolation but higher resource consumption. Containers share the host OS, packaging only the application and necessary libraries, resulting in minimal overhead.

A major difference between the two is that their security perspectives vary. VMs offer hardware-level isolation, whereas containers have process-level isolation, posing unique security considerations. VMs have longer boot-up times due to the need to initiate an OS, while containers start almost instantly.

In terms of portability, VMs can have challenges in diverse environments because of OS dependencies. Containers offer consistent performance across settings due to the shared OS model. Management tools for VMs include solutions like VMware, while Docker and Kubernetes cater to containers.

VMs consume more resources compared to the streamlined containers. While VMs provide comprehensive isolation, containers depend on the host OS, which might introduce vulnerabilities. Regarding scalability, containers are compatible with microservices for rapid scaling, while VMs are optimal for larger applications.

Similarities Between Virtual Machines and Containers

Both Virtual Machines (VMs) and containers are technologies designed to isolate applications, ensuring that they run in a consistent environment. They serve as tools to replicate environments across various stages of the development and deployment lifecycle, minimizing the “it works on my machine” problem.

1. Isolation: At their core, both VMs and containers provide isolated environments for applications. This isolation ensures that each application receives the resources and runtime environment it requires without interference from other applications.
2. Snapshot and Cloning Abilities: VMs, managed by hypervisors, and containers, usually managed by orchestration tools like Kubernetes, offer snapshot capabilities. These snapshots capture the state of the VM or container at a particular point in time and can be used to clone or restore the environment.
3. Portability: Both VMs and containers encapsulate the application and its dependencies. This encapsulation makes it possible to move applications across different stages of the development pipeline (from a developer’s local machine to production environments) or across different cloud providers or on-premises servers.
4. Version Control: VMs and containers support versioning. VMs can be versioned by creating different virtual machine disk files, while container images can be versioned and stored in container registries. This version control is essential for rollback, audit, and replication purposes.
5. Automation and Scripting: VMs and containers can be automated and managed using scripts and APIs. For VMs, hypervisor APIs can be utilized, while for containers, tools like Docker provide command-line interfaces and APIs.

In essence, while VMs and containers have distinct architectures and use cases, they share several common functionalities centered on application isolation, management, and deployment.

Optimal Use Cases for VMs and Containers

Even though both are effective software layers, there are situations in which they are best used.

• VMs: Traditionally, large enterprises and companies with legacy applications find VMs particularly beneficial. Firms like financial institutions or government agencies, which prioritize robust security and isolation and have systems that rely on specific OS environments, lean towards VMs. Additionally, VMs are suitable for scenarios where complete resource isolation, hardware utilization, and OS-specific applications are required. For instance, a multinational corporation may use VMs for resource-intensive ERP systems that need isolated environments.
• Containers: Start-ups, tech companies, and modern enterprises that focus on agility and scalability prefer containers. For instance, a tech startup aiming for rapid iterative deployments or a Software as a Service (SaaS) company looking to ensure consistency across multiple deployment environments will find containers more aligned to their needs. Containers are ideal for microservices architectures, where different services can be developed, scaled, and deployed independently.
• Combining VMs and Containers: Hybrid approaches, where VMs and containers coexist, are gaining traction, especially in complex IT environments. For example, a large e-commerce company might use VMs for its database systems, ensuring resource isolation and stability, while leveraging containers for its front-end and microservices to ensure quick updates and scalability during peak sales periods.

The Gigamon Perspective on Containers vs Virtual Machines:

From an observability standpoint, understanding both VMs and containers is essential to achieve complete network visibility. In hybrid cloud infrastructure, integrating VMs and containers can establish a resilient system, optimizing resource allocation and performance.

Why Choose Gigamon?

Gigamon, a renowned name in the field of network visibility and analytics, holds a significant position when it comes to VMs and containers within hybrid cloud infrastructure.

One of the core strengths of the Gigamon Deep Observability Pipeline lies in its ability to provide deep observability across different environments. As enterprises adopt a mix of VMs and containers, achieving comprehensive visibility becomes a challenge. Gigamon addresses this by enabling organizations to monitor traffic traversing both VMs and containerized applications. This is crucial for performance optimization, security monitoring, and troubleshooting.

In the world of VMs, Gigamon integrates with hypervisors to extract, mirror, and analyze the inter-VM traffic. Such insights are paramount, especially when VMs host critical applications. By understanding this traffic, IT teams can identify inefficiencies, potential security threats, or operational issues.

Containers introduce a different set of challenges. With containers often being short-lived and dynamically scheduled, tracking the communication between them is non-trivial. Gigamon facilitates the capture of inter-container traffic, ensuring that no blind spots exist, irrespective of the container’s lifespan.

Moreover, Gigamon provides a unified platform for both VM and container traffic. This means that organizations don’t have to juggle between disparate monitoring tools when dealing with hybrid deployments. Such a consolidated approach not only simplifies the operational overhead but also ensures that there’s a single source of truth when analyzing network traffic.

Gigamon is pivotal in ensuring that enterprises, regardless of their reliance on VMs, containers, or a blend of both, have the requisite tools to maintain visibility, security, and performance across their network landscapes.

Conclusion

Understanding the technical differences between virtual machines and containers is fundamental for effective hybrid cloud infrastructure management. As technology evolves, it’s essential to remain updated and make data-driven decisions in the realm of cloud computing.

Learn more about how to Solidify Your Security Posture with Visibility into Virtual Machines and Containers with Gigamon.

**Written by Gigamon utilizing AI research