containers_vs_vms - dwilson2547/wiki_demo GitHub Wiki

• 1. What is Containerization?
  • Key Components of Containerization
  • 1.1. How Containerization Works
  • 1.2. Popular Containerization Tools
• 2. What is KVM?
  • Key Components of KVM
  • 2.1. How KVM Works
• 3. Key Differences Between Containerization and KVM
• 4. When to Use Containerization vs. KVM
  • 4.1. Use Containerization When:
  • 4.2. Use KVM When:
• 5. Performance Comparison
  • 5.1. Startup Time
  • 5.2. Resource Overhead
  • 5.3. Disk Usage
• 6. Security Comparison
  • 6.1. Isolation
  • 6.2. Attack Surface
  • 6.3. Best Practices for Security
• 7. Networking Comparison
  • 7.1. Containers
  • 7.2. KVM VMs
• 8. Storage Comparison
  • 8.1. Containers
  • 8.2. KVM VMs
• 9. Orchestration and Management
  • 9.1. Containers
  • 9.2. KVM VMs
• 10. Use Case Scenarios
  • 10.1. Containerization
  • 10.2. KVM
• 11. Hybrid Approaches
  • 11.1. KVM + Containers (LXC)
  • 11.2. Kata Containers
  • 11.3. Firecracker (AWS)
• 12. Example Workflows
  • 12.1. Containerization Workflow (Docker)
  • 12.2. KVM Workflow (virsh)
• 13. Performance Benchmarks
• 14. When to Combine Both
• 15. Summary: Containerization vs. KVM
• 16. Final Recommendations
• 17. Further Learning

Containerization is a lightweight virtualization method that packages an application and its dependencies into a container. Containers share the host OS kernel but run in isolated user spaces, making them portable, efficient, and fast to deploy. Unlike traditional virtual machines (VMs), containers do not require a full OS; they only need the application and its libraries.

1. Container Engine:
   • Software that manages containers (e.g., Docker, containerd, Podman).
2. Container Image:
   • A read-only template with the application and its dependencies (e.g., a Docker image).
3. Container Runtime:
   • Executes containers from images (e.g., runc, crun).
4. Orchestration Tools:
   • Manage multiple containers across hosts (e.g., Kubernetes, Docker Swarm).

• Containers share the host OS kernel but run in isolated user spaces (namespaces) with their own:
  • Filesystem (via overlayFS or other storage drivers).
  • Process tree (PID namespace).
  • Network stack (network namespace).
  • User IDs (user namespace).
  • IPC (Inter-Process Communication).
• Resource limits (cgroups) prevent one container from consuming all host resources.

Example:

docker run -it ubuntu bash

• Downloads the ubuntu image (if not cached) and starts a container running bash.

KVM (Kernel-based Virtual Machine) is a Type-1 hypervisor built into the Linux kernel. It enables running multiple virtual machines (VMs) with their own full operating systems (guests) on a single physical host. KVM provides hardware-assisted virtualization (Intel VT-x/AMD-V) for near-native performance.

1. KVM Kernel Module:
   • Loadable module (kvm.ko) that enables virtualization.
2. QEMU:
   • Emulates hardware (CPU, NIC, storage) for VMs.
3. libvirt:
   • Manages VMs and provides tools like virsh and virt-manager.

• KVM turns the Linux kernel into a hypervisor, allowing multiple VMs to run with:
  • Full OS isolation (each VM has its own kernel).
  • Hardware virtualization (Intel VT-x/AMD-V).
  • Device emulation (via QEMU) for NICs, disks, and GPUs.
• Performance: Near-native due to direct hardware access.

Example:

virt-install --name ubuntu-vm --ram 2048 --vcpus 2 --disk path=/var/lib/libvirt/images/ubuntu.qcow2,size=20 --os-type linux --os-variant ubuntu20.04 --network bridge=virbr0 --graphics spice --cdrom /path/to/ubuntu.iso

• Creates a VM with 2GB RAM, 2 vCPUs, and a 20GB disk.

• You need lightweight, fast, and scalable deployments (e.g., microservices, cloud-native apps).
• You want to maximize resource efficiency (e.g., running hundreds of containers on a single host).
• You are deploying stateless applications (e.g., web servers, APIs).
• You need portability (e.g., Docker images run anywhere with Docker installed).
• You are using orchestration tools like Kubernetes or Docker Swarm.

Example Use Cases:

• Microservices: Deploying individual services in containers.
• CI/CD Pipelines: Running tests in ephemeral containers.
• Serverless: Containers as the backbone for serverless platforms (e.g., AWS Fargate).

• You need full OS isolation (e.g., running Windows on Linux or vice versa).
• You are running legacy applications that require a full OS.
• You need hardware passthrough (e.g., GPU, PCI devices).
• You require high security (e.g., multi-tenant environments where kernel isolation is critical).
• You are using high-performance computing (HPC) or workloads that need direct hardware access.

Example Use Cases:

• Enterprise Virtualization: Running multiple OS environments (e.g., Windows VMs on Linux hosts).
• Development/Testing: Testing software on different OS versions.
• GPU-Intensive Workloads: Machine learning, 3D rendering, or gaming VMs.

Example:

time docker run -it ubuntu echo "Hello"
# ~0.5 seconds

time virsh start myvm && virsh console myvm
# ~30-60 seconds (depends on OS)

Example:

• A container might use 50MB of additional memory.
• A VM might use 512MB–2GB for the guest OS alone.

• Containers:
  • Share the host kernel, so a kernel exploit can affect all containers and the host.
  • Use namespaces and cgroups for isolation (not as strong as VMs).
• KVM VMs:
  • Full isolation: Each VM runs its own kernel, so a compromise in one VM does not affect others or the host.
  • Supports SELinux/AppArmor for additional security.

• Containers:
  • Smaller attack surface (only the application and its dependencies).
  • Vulnerabilities in the host kernel can impact all containers.
• KVM VMs:
  • Larger attack surface (full OS stack per VM).
  • Hardware virtualization (VT-x/AMD-V) adds a layer of protection.

• Network Models:
  • Bridge: Containers on a virtual bridge (default in Docker).
  • Host: Containers share the host’s network stack.
  • None: No networking.
  • Overlay: Multi-host networking (e.g., Docker Swarm, Kubernetes).
• Performance: Low latency (shared kernel networking).
• Example:

  docker run --network=host nginx

• Network Models:
  • NAT: VMs share the host’s IP (default in libvirt).
  • Bridge: VMs appear as independent devices on the LAN.
  • Direct Attachment: VMs connect directly to a physical NIC (e.g., MacVTAP).
  • Isolated: VMs communicate only with each other.
• Performance: Higher latency (full network stack per VM).
• Example:

  <interface type='bridge'>
    <source bridge='virbr0'/>
    <model type='virtio'/>
  </interface>

• Storage Drivers:
  • OverlayFS: Default in Docker; uses layered filesystems.
  • AUFS: Older layered filesystem.
  • Btrfs/ZFS: Advanced filesystems with snapshot support.
• Example:

  docker pull ubuntu

  • Downloads layers shared across containers.

• Storage Backends:
  • QCOW2: Dynamic disk image (grows as needed).
  • RAW: Fixed-size disk image (better performance).
  • LVM: Logical Volume Manager for block storage.
  • Ceph/GlusterFS: Distributed storage for clouds.
• Example:

  qemu-img create -f qcow2 myvm.qcow2 20G

• Orchestration Tools:
  • Kubernetes: Automates deployment, scaling, and management of containers.
  • Docker Swarm: Docker’s built-in orchestration.
  • Nomad: Lightweight orchestration by HashiCorp.
• Example (Kubernetes):

  kubectl create deployment nginx --image=nginx

• Management Tools:
  • libvirt: Manage VMs with virsh or virt-manager.
  • OpenStack: Cloud platform for managing VMs at scale.
  • oVirt: Enterprise virtualization management.
• Example (libvirt):

  virsh list --all
  virsh start myvm

In some cases, containers and KVM are used together to leverage the strengths of both:

• LXC (Linux Containers) can run inside KVM VMs for lightweight virtualization within VMs.
• Example: Running LXC containers inside a KVM VM for additional isolation.

• Kata Containers combine the security of VMs with the speed of containers.
• Each container runs in a microVM (lightweight VM) for stronger isolation.
• Example:

  docker run --runtime=kata-runtime ubuntu

• Firecracker is a microVM technology by AWS that powers AWS Lambda and Fargate.
• Provides container-like speed with VM-like security.
• Example: AWS Lambda uses Firecracker to run functions in isolated microVMs.

1. Pull an Image:

   docker pull nginx

2. Run a Container:

   docker run -d -p 80:80 --name my-nginx nginx

3. Scale with Kubernetes:

   kubectl create deployment my-nginx --image=nginx --replicas=3

1. Create a VM:

   virt-install --name ubuntu-vm --ram 2048 --vcpus 2 --disk path=/var/lib/libvirt/images/ubuntu.qcow2,size=20 --os-type linux --os-variant ubuntu20.04 --network bridge=virbr0 --graphics spice --cdrom /path/to/ubuntu.iso

2. Start the VM:

   virsh start ubuntu-vm

3. Connect to the VM:

   virt-viewer ubuntu-vm

Use both containers and KVM in scenarios where:

• You need isolation for some workloads (KVM) and speed for others (containers).
• You are running a mixed environment (e.g., legacy apps in VMs and microservices in containers).
• You want to use Kata Containers or Firecracker for secure, lightweight VMs.

Example Architecture:

Host OS (Linux)
├── KVM VMs (Legacy Apps, Windows)
│   ├── VM 1 (Windows Server)
│   └── VM 2 (CentOS 7)
└── Containers (Microservices)
    ├── Container 1 (NGINX)
    ├── Container 2 (Redis)
    └── Container 3 (Node.js App)

• Use Containers for:

  • Microservices, CI/CD, cloud-native apps, and scalable deployments.
  • Stateless applications (e.g., web servers, APIs).
  • Development and testing (e.g., Docker Compose).

• Use KVM for:

  • Legacy applications requiring full OS isolation.
  • Multi-OS environments (e.g., running Windows on Linux).
  • High-security environments (e.g., multi-tenant clouds).
  • GPU-intensive workloads (e.g., machine learning, gaming).

• Combine Both for:

  • Hybrid environments (e.g., Kata Containers, Firecracker).
  • Running containers inside VMs for added security.
  • Mixed workloads (e.g., legacy VMs + modern containers).

• Containerization:
  • Docker Documentation
  • Kubernetes Documentation
  • Podman Documentation
• KVM:
  • KVM Official Site
  • Libvirt Documentation
  • QEMU Documentation
• Hybrid Approaches:
  • Kata Containers
  • Firecracker