At a glance
What is this page?
A practical use case guide for teams choosing between virtual machines (VMs), containers, and orchestration—with plain-language explanations, deeper technical context where helpful, examples, pitfalls to avoid, and three server recommendations you can deploy today.
Written in a straightforward, dependable, infrastructure-first voice so your team can stay in control without surprises.
TL;DR - Quick Decision Guide
- Use VMs for legacy systems, security boundaries, mixed OS stacks
- Use containers for microservices, CI/CD, cloud-native apps
- Use orchestration (K8s) for auto-scaling and multi-team environments
- Pin NUMA for performance-critical VMs; use NVMe storage
- Plan overhead: VMs (10-15%), containers (2-5%), orchestration (+20%)
- Start simple; add complexity only when needed
Pick your virtualisation approach
Choose the right level of abstraction based on workload isolation and operational needs.
VMs (Type 1)
Best for
Legacy apps, compliance, mixed OS
Resource Overhead
10-15% CPU overhead
Next step
Pin vCPU, tune NUMA
Containers (Docker)
Best For
Microservices, dev/test, CI/CD
Resource Overhead
2-5% resource overhead
Next Step
Add container registry
Orchestration (K8s)
Best For
Auto-scaling, multi-team ops
Resource Overhead
+20% for control plane
Next Step
Service mesh + monitoring
What is virtualisation?
Virtualisation splits one physical server into multiple virtual machines. Each VM behaves like a dedicated server with its own OS, CPU/RAM allocation, storage, and network interfaces—ideal for compliance-grade isolation, mixed OS stacks, or per-tenant boundaries.
A bit deeper:
Hypervisors:
Type 1 hypervisors (bare-metal) such as KVM, Hyper-V, or ESXi allocate CPU time, memory, and I/O to each VM and enforce strict boundaries.
NUMA & CPU pinning:
For performance-sensitive apps (databases, low-latency trading, transcoding), you can pin vCPUs to cores and align RAM to the right NUMA node to avoid cross-socket penalties.
Storage & network virtualisation:
VM disks sit on block devices or shared datastores (RAID/NVMe/SSD). Virtual switches and VLANs let you segment traffic per tenant or environment.
Choose VMs when isolation, legacy OS support, or clear tenancy lines matter most.
Virtualisation at Scale
600+ VM Hosts
Battle-tested hypervisor performance
Enterprise-Grade Storage
NVMe/RAID for any workload
Multi-Tenant Security
Compliant isolation boundaries
24/7 Infrastructure Team
In-house hypervisor expertise
What is containerisation?
Containerisation packages an application with just the libraries and settings it needs on a shared host OS. Containers start fast, use fewer resources than VMs, and are portable across environments—great for microservices, APIs, workers, and frequent releases.
A bit deeper:
Namespaces & cgroups:
Linux namespaces isolate processes, filesystems, network, and users; cgroups limit CPU/memory/IO to keep one container from starving others.
Image layers:
Container images are layered; shared layers are cached across containers, which makes pulls faster and saves space.
Networking & storage:
Containers join bridges or overlays; state lives on volumes or external databases/queues.
Security hardening:
Add Pod/Container security profiles (seccomp, AppArmor/SELinux), drop capabilities, run as non-root, and scan/sign images to reduce supply-chain risk.
Use containers to standardise builds and speed up CI/CD.
What is orchestration and when do you need it?
Orchestration (e.g., Kubernetes) places, scales, heals, and updates containers across multiple servers. It automates rollouts (blue/green, canary), autoscaling, health checks, discovery, and secrets/config management.
A bit deeper:
Control plane & scheduler:
Assigns pods to nodes based on CPU/RAM requests/limits, node labels, and affinity/anti-affinity rules.
Self-healing:
Probes restart unhealthy containers; replica sets replace missing instances automatically.
Ingress & service mesh:
Ingress exposes services; meshes (e.g., Istio/Linkerd) add mTLS, retries, and traffic shaping.
Policies & RBAC:
Enforce who can deploy what, where it can run, and how it talks on the network—vital for multi-team platforms.
Adopt orchestration when you have variable demand, many services/teams, or zero-downtime requirements.
When should I use virtualisation, containers, or both?
Use VMs for hard isolation, mixed OS needs, or strict compliance. Use containers for speed, density, and portability. Combine both when you want VM-grade separation plus container agility (e.g., run K8s worker nodes inside VMs to isolate teams or environments).
VM snapshots/replication help with conservative change control. Containers excel with weekly/daily releases and scalable backends.
Which workloads fit each approach?
VM-friendly workloads
- Databases needing consistent IOPS and kernel stability (Postgres, MySQL, SQL Server)
- ERP/monoliths and Windows services with longer lifecycles
- Strictly isolated multi-tenant hosting with VM boundaries
- Security-sensitive systems with regulated isolation needs
Container-friendly workloads
- Microservices and public APIs with frequent releases
- Event/queue workers and scheduled jobs
- Real-time backends (chat, notifications, IoT ingestion)
- CPU/GPU batch pipelines (transcode, inference, analytics)
Orchestration-friendly scenarios
- Variable demand benefiting from autoscaling
- Large engineering teams needing standardised rollouts, secrets, policies, and observability
- Zero-downtime requirements (canary/blue-green)
What does a minimal architecture look like?
VM-only
- Per-app VMs behind a load balancer
- Snapshots & backups
- Strong isolation; ideal for legacy apps/Windows
- VLANs for tenant segmentation
- Choose NVMe for hot data; RAID10 for DBs
Containers without orchestration
- 1–3 VMs with Docker and docker-compose
- Reverse proxy (Nginx/Traefik)
- Centralised logs/metrics
- Simple backups
- Clear path to Kubernetes if growth continues
Full orchestration
- 3+ nodes (HA control plane optional)
- Registry, Ingress, metrics/logging/alerts
- Secrets and policy controls
- Git-driven deployments (Argo/Flux)
- Requests/limits and network policies from day one
Three Worldstream server recommendations
These are solid baselines. We tailor CPU, RAM, storage tiers, and networking to your workloads—our focus is infrastructure, and we do it exceptionally well.
Where is this use case common?
SaaS & Marketplaces
- Many services, per-tenant isolation
- Frequent deploys and rapid iteration
Fintech & Payments
- Defense-in-depth and auditability
- Smooth, low-risk updates under regulation
Media & Gaming
- Bursty traffic and edge distribution
- Low latency; GPU/CPU pipelines
Healthcare & Public Sector
- Isolation and policy control
- Data residency in trusted locations
Retail & E-commerce
- Seasonal scaling
- Experimentation and feature flags
Industrial / IoT
- Edge clusters across many sites
- Predictable, remote-friendly updates
Worldstream’s infrastructure is locally built, globally trusted, with own data centers in the Netherlands, 15,000+ active servers, and support that sits close to the metal—useful for the regulated and latency-sensitive scenarios above.
What pain points does this solve?
- Unpredictable traffic → orchestration autoscaling adds replicas before users feel slowdown.
- Slow, risky releases → containers standardize builds; orchestrators automate rollouts and rollbacks.
- “Works on my machine” → container images pin dependencies so environments match.
- Noisy neighbors / compliance → VM boundaries provide clear separation.
- Upgrade downtime → blue/green or canary strategies shift traffic gradually.
- Resource waste → container density packs more work per server and scales with real demand.
What are the benefits and drawbacks?
Virtualisation (VM's)
Heavier than containers (more OS overhead per workload)
Strong isolation; predictable performance per tenant
Slower boot times; fewer instances per host
Full OS control (kernels, drivers, licensing)
More OS maintenance across many VMs
Clear tenancy boundaries for compliance and cost attribution
Containerisation
Weaker default isolation vs. VMs (must be hardened)
Fast start, high density → efficient hardware use
Image sprawl and supply-chain risk without governance
Portable images → consistent dev→prod
Stateful apps need careful storage/network patterns
CI/CD-native, automation-friendly
Orchestration
Operational complexity and learning curve
Automated scheduling, scaling, and self-healing
Platform overhead (backups, upgrades, observability)
Built-in rollouts, secrets, RBAC, and policies
Overkill for small, static apps
Standardised operations across many teams/services
How do I choose?
Simple decision guide
Rule of thumb: Start with the simplest architecture that meets today’s requirements, and design a clear upgrade path as complexity grows.
Do you need strict isolation or mixed OSes?
Choose VMs. You can still run containers inside those VMs for faster deploys.
Are you shipping weekly/daily across multiple services?
Choose containers for standardized packaging and CI/CD
Do you face variable demand or complex rollouts?
Add orchestration (Kubernetes/Nomad) for autoscaling, self-healing, and safe deployments.
How big is your platform team and ops footprint?
If small, start with VMs + docker-compose and keep the surface area modest. Add Kubernetes when services or teams outgrow manual coordination.
What are your data and compliance constraints for stateful systems?
Keep stateful systems on VMs or well-supported operators with strong backup/restore; use private networks/VLANs for tenancy boundaries and auditability.
Do you need strict isolation or mixed OSes?
Choose VMs. You can still run containers inside those VMs for faster deploys.
Do you face variable demand or complex rollouts?
Add orchestration (Kubernetes/Nomad) for autoscaling, self-healing, and safe deployments.
What are your data and compliance constraints for stateful systems?
Keep stateful systems on VMs or well-supported operators with strong backup/restore; use private networks/VLANs for tenancy boundaries and auditability.
Are you shipping weekly/daily across multiple services?
Choose containers for standardized packaging and CI/CD
How big is your platform team and ops footprint?
If small, start with VMs + docker-compose and keep the surface area modest. Add Kubernetes when services or teams outgrow manual coordination.
How do I run Kubernetes on Worldstream dedicated servers?
1. Choose 3+ nodes
– One control plane (or three for HA) + two or more workers
2. Install your distro
– kubeadm or k3s for simplicity
– Connect your private container registry
3. Add essentials
– Ingress for routing, CSI for storage, CNI for networking
– Prometheus/Grafana for SLOs; Loki/ELK for logs
– Backups with Velero (test restores regularly)
4. Deploy via Git
– GitOps with Argo CD/Flux or pipelines so every change is auditable
5. Harden early
– Network policies and Pod Security
– Image signing/scanning; RBAC; regular kernel/OS patching
6. Segment environments
– Separate namespaces or even separate VM node pools for Dev/Test/Prod
Worldstream’s Worldstream Elastic Network (WEN)—our platform for deploying, connecting, and scaling resources via a single gateway—helps stitch clusters and services together without unnecessary complexity, aligned with our promise of fewer buttons, more control.
Performance Targets & Resource Guidelines
VM Performance:
- CPU overhead: <15%
- Memory balloon: <10%
- Disk I/O: <50μs latency
Container Efficiency:
- Start time: <2s
- Resource overhead: <5%
- Image layers: <10
K8s Control Plane:
- API response: <100ms
- Pod start: <30s
- Node ready: <2min
VM Deployment Checklist
Resource Allocation
✓ CPU pinning configured
✓ NUMA topology aligned
✓ Memory ballooning disabled
✓ Storage path optimized
Security & Backup
✓ VM templates hardened
✓ Snapshot schedule set
✓ Network isolation tested
✓ Backup restoration verified
Container Performance Issues Runbook
High Memory/CPU (0-3 min)
- Check container resource limits
- Scale horizontally if possible
- Identify memory leaks in apps
- Review recent deployment changes
Slow Pod Starts (3-10 min)
- Pre-pull critical images
- Optimize image layers and size
- Check node resource availability
- Review init container dependencies
Operations, Performance & Risk Management
Costs:
Containers often increase density; VMs simplify tenancy and compliance. With Worldstream's straightforward contracts and pricing, you know what to expect—no surprise
Performance:
Use NVMe for hot data; SSD RAID10 for databases; consider 25GbE for heavy east-west traffic. For CPU-bound services, favor higher base clocks; for parallel workloads, more cores pay off.
Monitoring:
Observe p95 latency and queue depth as leading indicators of stress.
Scaling:
Start small (VMs or a 3-node cluster). Scale vertically (more RAM/CPU) or horizontally (more nodes). Orchestration automates placement and growth; capacity plans should follow real usage.
Costs:
Containers often increase density; VMs simplify tenancy and compliance. With Worldstream's straightforward contracts and pricing, you know what to expect—no surprise
Monitoring:
Observe p95 latency and queue depth as leading indicators of stress.
Performance:
Use NVMe for hot data; SSD RAID10 for databases; consider 25GbE for heavy east-west traffic. For CPU-bound services, favor higher base clocks; for parallel workloads, more cores pay off.
Scaling:
Start small (VMs or a 3-node cluster). Scale vertically (more RAM/CPU) or horizontally (more nodes). Orchestration automates placement and growth; capacity plans should follow real usage.
Risks & Mitigations
Operational complexity:
Assign a platform owner; keep runbooks for upgrades, backups, and incident response; implement change windows and rollbacks.
Supply-chain security:
Use a private registry, sign images, scan dependencies, and pin base images; routinely audit third-party charts/operators.
Stateful services in Kubernetes:
Prefer mature operators (Postgres, Kafka, Redis) or keep databases on VMs with managed backup/replication.
Over/under-sizing:
Size from observability data (CPU, memory, disk IOPS, saturation) rather than static requests; run periodic load tests.
Networking surprises:
Enforce network policies; isolate tenants via VLANs; document layer-3/4/7 traffic flows.
Operational complexity:
Assign a platform owner; keep runbooks for upgrades, backups, and incident response; implement change windows and rollbacks.
Stateful services in Kubernetes:
Prefer mature operators (Postgres, Kafka, Redis) or keep databases on VMs with managed backup/replication.
Networking surprises:
Enforce network policies; isolate tenants via VLANs; document layer-3/4/7 traffic flows.
Supply-chain security:
Use a private registry, sign images, scan dependencies, and pin base images; routinely audit third-party charts/operators.
Over/under-sizing:
Size from observability data (CPU, memory, disk IOPS, saturation) rather than static requests; run periodic load tests.
Next steps with Worldstream
You’ll work with in-house engineers who sit next to the infrastructure in our own data centers. We’re a partner for teams who value freedom of choice, dependable support, and transparent agreements.
Worldstream focuses solely on infrastructure—and we do it exceptionally well. Clear, down-to-earth guidance and predictable agreements give you control without complexity.
Solid IT. No Surprises.
Frequently Asked Questions
Not entirely. Containers optimise packaging and deployment; VMs provide stronger default isolation and OS flexibility. Many teams combine both: VMs for boundaries, containers for speed.
Glossary
Key terms explained briefly for quick reference.