Kubernetes vs OpenShift
A simple comparison to help you understand when to use what.
🤔 What Are They?
| Kubernetes | OpenShift | |
|---|---|---|
| What | Open-source container orchestration platform | Enterprise Kubernetes platform by Red Hat |
| Developer | Google (donated to CNCF in 2015) | Red Hat (now part of IBM) |
| First Release | 2014 | 2011 (OpenShift v3+ uses K8s since 2015) |
| Governance | CNCF (Cloud Native Computing Foundation) | Red Hat (IBM subsidiary) |
| Analogy | Linux kernel | Red Hat Enterprise Linux (RHEL) |
| Cost | Free (Open Source) | Paid (with support) |
| License | Apache 2.0 | Apache 2.0 (core) + Proprietary features |
Simple way to think about it: Kubernetes is the engine, OpenShift is the car with the engine + dashboard + GPS + airbags.
Who Developed Them?
Kubernetes (K8s):
- 🔷 Created by: Google engineers (based on internal Borg/Omega systems)
- 🔷 Key Contributors: Joe Beda, Brendan Burns, Craig McLuckie
- 🔷 Donated to: CNCF (Cloud Native Computing Foundation) in 2015
- 🔷 Maintained by: Open-source community (1000s of contributors worldwide)
- 🔷 Backed by: Google, Microsoft, Red Hat, AWS, and many others
OpenShift:
- 🔴 Developed by: Red Hat (acquired by IBM in 2019)
- 🔴 Built on: Kubernetes core + Red Hat enhancements
- 🔴 Community Version: OKD (OpenShift Kubernetes Distribution)
- 🔴 Enterprise Support: Red Hat
- 🔴 Strategy: Add enterprise features on top of K8s
Stakeholders
Kubernetes Stakeholders:
- CNCF - Neutral governance body
- Cloud Providers - AWS (EKS), Google (GKE), Azure (AKS), etc.
- Tech Giants - Google, Microsoft, Red Hat, IBM, VMware
- End Users - Fortune 500 companies, startups, government
- Contributors - Thousands of developers worldwide (70,000+ as of 2026)
- Vendors - Tool makers (Helm, Rancher, Istio, etc.)
OpenShift Stakeholders:
- Red Hat/IBM - Primary developer and supporter
- Enterprise Customers - Banks, healthcare, government, Fortune 500
- Partners - Microsoft (Azure Red Hat OpenShift), AWS (ROSA)
- OKD Community - Open-source contributors
- Certified Partners - ISVs with certified operators
- System Integrators - Consulting firms implementing OpenShift
🖥️ Containers vs Virtual Machines
Before diving into Kubernetes and OpenShift, let's understand how containers differ from traditional Virtual Machines.
What's the Difference?
| Virtual Machines (VMs) | Containers (K8s/OpenShift) | |
|---|---|---|
| What | Full computer virtualization | Application-level virtualization |
| OS | Each VM has its own full OS | Shares host OS kernel |
| Size | GBs (2-20 GB typical)* | MBs (50-200 MB typical)* |
*Sizes vary based on application and OS requirements | Startup | Minutes | Seconds | | Isolation | Hardware-level (hypervisor) | Process-level (namespaces, cgroups) |
🏢 Analogy:
- Virtual Machines = Individual houses on a street - each has its own foundation, walls, plumbing, and electrical system
- Containers = Apartments in a building - share foundation, plumbing, and electrical, but each has private living space
Architecture Comparison
Virtual Machines Architecture:
┌─────────────────────────────────────┐
│ Application Layer │
├─────────────────────────────────────┤
│ Guest OS | Guest OS | Guest OS │ ← Each VM has full OS
├─────────────────────────────────────┤
│ Hypervisor (VMware, etc) │
├─────────────────────────────────────┤
│ Host Operating System │
├─────────────────────────────────────┤
│ Physical Hardware │
└─────────────────────────────────────┘
Containers Architecture:
┌─────────────────────────────────────┐
│ App | App | App | App | App │ ← Just the app + dependencies
├─────────────────────────────────────┤
│ Container Runtime (Docker/CRI-O) │
├─────────────────────────────────────┤
│ Orchestrator (K8s/OpenShift) │ ← Manages containers
├─────────────────────────────────────┤
│ Host Operating System │ ← Shared OS kernel
├─────────────────────────────────────┤
│ Physical Hardware │
└─────────────────────────────────────┘
Detailed Comparison
| Aspect | Virtual Machines | Containers |
|---|---|---|
| Boot Time | 1-5 minutes | 1-5 seconds |
| Resource Efficiency | Lower (overhead for each OS) | Higher (shared kernel) |
| Density | 10-20 VMs per server | 100-1000 containers per server |
| Portability | Moderate (image size issues) | High (lightweight images) |
| Security Isolation | Strong (hardware-level) | Good (process-level, improving) |
| Performance | Near-native | Near-native (minimal overhead) |
| Management | Manual or VM managers | Orchestrators (K8s/OpenShift) |
| Use Case | Full OS needed, legacy apps | Microservices, cloud-native apps |
Visual Analogy
Shipping Analogy:
| Virtual Machines | Containers |
|---|---|
| 🚢 Shipping individual cars, each with its own engine, wheels, and everything | 📦 Shipping standardized containers that fit on any ship |
| Each VM needs its own "vehicle" (full OS) | All containers share the "ship" (host OS) |
| Slow to load/unload | Fast to load/unload |
| Expensive per unit | Cost-effective at scale |
Pros and Cons
Virtual Machines
✅ Pros:
- Strong Isolation - Complete separation between VMs
- Run Any OS - Windows VM on Linux host, or vice versa
- Legacy Apps - Works with apps not designed for containers
- Mature Technology - 20+ years of tooling and best practices
- Security - Hardware-level isolation, better for multi-tenancy
- Full Control - Complete OS customization
❌ Cons:
- Resource Heavy - Each VM needs full OS (RAM, CPU, storage)
- Slow Startup - Minutes to boot a VM
- Poor Density - Fewer VMs per physical server
- Large Images - VM images are GBs in size
- Slower Deployment - Provisioning takes time
- Update Overhead - Must patch each VM's OS separately
Containers (Kubernetes/OpenShift)
✅ Pros:
- Lightweight - Shares OS kernel, minimal overhead
- Fast Startup - Seconds to start a container
- High Density - 100s of containers per server
- Portable - "Write once, run anywhere" (Linux/Cloud)
- Easy Scaling - Spin up 100 instances in seconds
- DevOps-Friendly - CI/CD integration, microservices
- Version Control - Images are like Git for infrastructure
- Efficient Updates - Layer-based, only update what changed
❌ Cons:
- OS Limitation - Linux containers need Linux host (Windows containers available for Windows hosts)
- Security Trade-off - Shared kernel = potential attack vector
- Complexity - Learning curve for orchestration (K8s)
- Not for Everything - Legacy monoliths may struggle
- Networking - More complex than VMs
- State Management - Stateful apps need extra work
When to Use What?
| Scenario | Recommendation | Why |
|---|---|---|
| Microservices Architecture | Containers (K8s/OpenShift) | Fast deployment, scaling, cloud-native |
| Legacy Monolithic Apps | Virtual Machines | Easier to lift-and-shift, no refactoring |
| Multi-OS Requirements | Virtual Machines | Need Windows + Linux + others |
| Highly Regulated Industries | VMs or OpenShift | Stronger isolation, compliance needs |
| Development/Testing | Containers | Faster setup, tear down, iteration |
| Running Windows Apps | Virtual Machines | (or Windows Containers on Windows host) |
| Database Workloads | VMs (traditionally) or Containers (cloud-native) | VMs for legacy, Containers for cloud-native DBs |
| Stateless Applications | Containers | Perfect use case, scales easily |
| Stateful Applications | Both (careful design) | VMs easier, Containers need StatefulSets |
| Maximum Isolation Needed | Virtual Machines | Hardware-level security |
Hybrid Approach: The Best of Both Worlds
Many organizations use both:
Modern Architecture:
├── Virtual Machines
│ ├── Legacy ERP systems
│ ├── Windows applications
│ └── Databases (sometimes)
│
└── Containers (Kubernetes/OpenShift)
├── Microservices
├── APIs
├── Web applications
└── Batch processing
Bonus: OpenShift Virtualization runs VMs inside OpenShift!
💡 Pro Tip: You don't have to choose one or the other. Use VMs for what they're good at, and containers for what they excel at.
Real-World Examples
Companies Using VMs:
- Traditional enterprises running SAP, Oracle
- Banks with mainframe integrations
- Healthcare with certified legacy systems
Companies Using Containers:
- Netflix → Microservices architecture
- Uber → Dynamic scaling for rides
- Airbnb → Fast deployment cycles
- Spotify → Thousands of services
Companies Using Both:
- Most large enterprises (hybrid approach)
- Cloud providers (offer both services)
- Banks modernizing incrementally
Technology Evolution
1960s: Mainframes
↓
1990s: Physical Servers
↓
2000s: Virtual Machines (VMware, Hyper-V)
↓
2013: Containers (Docker)
↓
2014: Kubernetes (Container Orchestration)
↓
2015: OpenShift (Enterprise Kubernetes)
↓
2020s: Hybrid (VMs + Containers + Serverless)
The Future: Serverless computing, WebAssembly, and edge computing are emerging, but VMs and containers will coexist for the foreseeable future.
🔄 Key Differences
1. Installation & Setup
| Kubernetes | OpenShift |
|---|---|
| DIY - you configure everything | Batteries included - pre-configured |
| Multiple distributions (EKS, GKE, AKS, k3s) | Single consistent platform |
| Steep learning curve | Easier to get started |
🏠 Analogy: Kubernetes is like buying land and building your house from scratch. OpenShift is buying a fully furnished apartment - move in and start living.
2. Security
| Kubernetes | OpenShift |
|---|---|
| Basic RBAC, you add the rest | Strict security by default |
| Containers run as root by default | Containers run as non-root by default |
| You manage security policies | Built-in Security Context Constraints (SCC) |
🔐 Analogy: Kubernetes gives you a door with a basic lock - add cameras and alarms yourself. OpenShift comes with a full security system, fingerprint scanner, and 24/7 monitoring.
3. Developer Experience
| Kubernetes | OpenShift |
|---|---|
| CLI only (kubectl) | Web Console + CLI (oc) |
| No built-in CI/CD | Built-in CI/CD pipelines |
| Bring your own image registry | Integrated image registry |
| Manual app deployment | Source-to-Image (S2I) builds |
🍳 Analogy: Kubernetes is like cooking from raw ingredients - you control everything. OpenShift is a meal kit delivery - ingredients are prepped, just follow the recipe.
4. Networking & Routing
| Kubernetes | OpenShift |
|---|---|
| Ingress (you choose controller) | Routes (built-in, simpler) |
| Configure your own load balancer | HAProxy router included |
| Service mesh: install Istio yourself | OpenShift Service Mesh included |
🛣️ Analogy: Kubernetes gives you a map and compass - find your own route. OpenShift gives you GPS navigation with traffic updates built-in.
✅ When to Use Kubernetes
- Budget constraints - Free and open source
- Maximum flexibility - Build your own platform
- Cloud-native apps - Using managed K8s (EKS, GKE, AKS)
- Learning - Understand container orchestration fundamentals
- Small teams - Simple workloads, less complexity needed
Good for: Startups, learning, cloud-managed environments, custom setups
✅ When to Use OpenShift
- Enterprise requirements - Need support and SLAs
- Strict security - Regulated industries (banking, healthcare)
- Developer productivity - Built-in CI/CD, web console
- Hybrid/Multi-cloud - Consistent platform across environments
- Large teams - Need governance and standardization
Good for: Enterprises, regulated industries, hybrid cloud, large teams
🛠️ Command Comparison
| Task | Kubernetes | OpenShift |
|---|---|---|
| CLI tool | kubectl | oc (also supports kubectl) |
| Get pods | kubectl get pods | oc get pods |
| Create app | kubectl create deployment | oc new-app |
| Expose service | kubectl expose + Ingress | oc expose svc (creates Route) |
| Login | kubectl config | oc login |
| Build from source | ❌ (need external CI) | oc new-app https://github.com/... |
📊 Quick Decision Matrix
| If you need... | Choose |
|---|---|
| Free solution | Kubernetes |
| Enterprise support | OpenShift |
| Maximum control | Kubernetes |
| Quick setup | OpenShift |
| Cloud-managed K8s | Kubernetes (EKS/GKE/AKS) |
| On-premise enterprise | OpenShift |
| Built-in CI/CD | OpenShift |
| Learning K8s concepts | Kubernetes |
🎯 Summary
Kubernetes = Foundation (flexible, DIY, free)
OpenShift = Enterprise Platform (opinionated, secure, paid)
Bottom line:
- Start with Kubernetes if you want to learn or need flexibility
- Choose OpenShift if you need enterprise features and don't want to build everything yourself
🏛️ Architecture & Design Philosophy
Kubernetes Philosophy
- Minimal & Extensible - Core provides basics, extend with plugins/operators
- Unopinionated - Multiple ways to solve the same problem
- Flexibility First - Choose your own tools, patterns, and practices
- Community-Driven - CNCF governance, vendor-neutral
Think: LEGO blocks - build whatever you want, however you want
OpenShift Philosophy
- Opinionated & Integrated - Best practices baked in
- Enterprise-Ready - Security, compliance, support out-of-the-box
- Developer-Centric - Simplify common workflows
- Red Hat Way - Curated, tested, supported stack
Think: Pre-built house - move in ready, everything works together
Technical Architecture Differences
| Layer | Kubernetes | OpenShift |
|---|---|---|
| Container Runtime | Multiple choices (containerd, CRI-O) | CRI-O (optimized for K8s) |
| API Server | Standard K8s API | Extended with OpenShift resources |
| Scheduler | Basic scheduler | Enhanced with priority/preemption |
| Networking | CNI plugins (Calico, Flannel, etc.) | OVN-Kubernetes (SDN) |
| Storage | CSI drivers | CSI + Red Hat Data Foundation |
| Registry | External (Docker Hub, etc.) | Built-in + integrated |
| Operators | Manual installation | Operator Hub built-in |
🌍 Ecosystem & Community
Kubernetes Ecosystem
Community:
- 💪 70,000+ contributors worldwide
- 🎯 CNCF (Cloud Native Computing Foundation) governed
- 🌟 Most active open-source project on GitHub
- 🔄 Quarterly releases (v1.28, v1.29, etc.)
Cloud Adoption:
| Provider | Offering | Market Share |
|---|---|---|
| AWS | EKS (Elastic Kubernetes Service) | ~35% |
| Azure | AKS (Azure Kubernetes Service) | ~20% |
| Google Cloud | GKE (Google Kubernetes Engine) | ~10% |
| Others | Self-managed, DigitalOcean, Linode | ~35% |
Popular Tools:
Helm → Package manager
Istio → Service mesh
ArgoCD → GitOps deployment
Prometheus → Monitoring
Grafana → Visualization
Velero → Backup/restore
OpenShift Ecosystem
Community:
- 🔴 Red Hat backed with enterprise support
- 🤝 OKD (OpenShift Kubernetes Distribution) - community version
- 📦 Certified operators - pre-validated by Red Hat
- 🔄 Major releases every ~6 months
Deployment Options:
| Type | Description | Use Case |
|---|---|---|
| OpenShift Container Platform | Self-managed | On-premise data centers |
| Red Hat OpenShift Dedicated | Red Hat-managed | AWS, GCP, Azure |
| Azure Red Hat OpenShift (ARO) | Microsoft + Red Hat managed | Azure-native |
| Red Hat OpenShift on IBM Cloud | IBM-managed | IBM Cloud |
Integrated Tools (Built-in):
Tekton → CI/CD pipelines
OpenShift Service Mesh → Based on Istio
OpenShift Logging → Elasticsearch, Fluentd, Kibana
OpenShift Monitoring → Prometheus + Grafana
OpenShift Virtualization → Run VMs alongside containers
CodeReady Workspaces → Cloud IDE
🏢 Enterprise Adoption & Use Cases
Kubernetes Success Stories
Best For:
- ✅ Startups - Fast iteration, cost-conscious
- ✅ Cloud-native apps - Born in the cloud
- ✅ DevOps teams - High technical capability
- ✅ Microservices - Container-first architecture
Real-World Examples:
🎵 Spotify → 200+ clusters, thousands of services
📱 Airbnb → Dynamic scaling for global traffic
🛒 Shopify → Black Friday traffic handling
🎮 Pokemon Go → Massive scale-up (50x in days)
💰 Capital One → Cloud-native transformation
OpenShift Success Stories
Best For:
- ✅ Banks & Financial - Strict compliance, security
- ✅ Healthcare - HIPAA compliance needs
- ✅ Government - Certified security standards
- ✅ Large Enterprises - 1000+ developers, multiple teams
Real-World Examples:
🏦 Deutsche Bank → Mission-critical banking apps
🏥 Novartis → Healthcare data processing
📺 BBC → Content delivery platform
🚗 BMW → Connected car platform
✈️ American Airlines → Customer-facing applications
⚡ Performance & Scalability
Kubernetes Performance
| Metric | Scale | Notes |
|---|---|---|
| Max Nodes | 5,000 | Per cluster (upstream K8s) |
| Max Pods | 150,000 | Across cluster |
| Pods per Node | 110 | Default limit (configurable) |
| API Response | <1s | For most operations |
| Startup Time | Seconds | For lightweight pods |
Performance Tuning:
# You control every knob and dial
- Custom scheduler tweaks
- Network plugin optimization
- Storage driver selection
- Resource quotas and limits
- Horizontal/Vertical pod autoscaling
OpenShift Performance
| Metric | Scale | Notes |
|---|---|---|
| Max Nodes | 2,000 | Per cluster (supported limit) |
| Max Pods | ~150,000 | With proper hardware |
| Pods per Node | 250 | OpenShift default |
| API Response | <1s | Additional OpenShift APIs |
| Build Time | Minutes | Source-to-Image builds |
Built-in Optimization:
# Pre-tuned for enterprise workloads
- Optimized default settings
- CRI-O performance improvements
- OVN-Kubernetes networking optimization
- Auto-tuning based on cluster size
- Built-in monitoring for bottlenecks
Reality Check:
Kubernetes → Can scale bigger, but you manage it
OpenShift → Scales to most enterprise needs, tuned for you
💰 Total Cost of Ownership (TCO)
Kubernetes Cost Breakdown
Software: FREE ✅
✅ Kubernetes itself
✅ kubectl CLI
✅ Community support
Hidden Costs: 💸💸💸
❗ DevOps/SRE team salaries (critical!)
❗ Security tools (Falco, Aqua, Twistlock)
❗ Monitoring/Logging setup (Prometheus, ELK)
❗ CI/CD pipeline setup (Jenkins, GitLab)
❗ Registry hosting (Artifact storage)
❗ Training & certifications (CKA, CKAD)
❗ Downtime costs (if self-managed)
❗ Upgrade management overhead
Typical Annual Cost (100-node cluster):
💵 Small Team (5 SREs): $500K - $800K
💵 Medium Team (15 SREs): $1.5M - $2.5M
💵 Large Team (30+ SREs): $3M - $5M+
⚠️ Mostly personnel costs!
OpenShift Cost Breakdown
Software: PAID 💰
💵 Licensing: $50-100 per core/year
💵 100-core cluster: ~$50K-100K/year in licenses
What's Included: 🎁
✅ 24/7 Red Hat support
✅ Security updates & patches
✅ Certified operators & integrations
✅ Built-in CI/CD, monitoring, logging
✅ Web console & CLI
✅ Training materials
✅ Compliance certifications (FedRAMP, PCI-DSS)
✅ Upgrade automation
Typical Annual Cost (100-node cluster):
💵 Software Licenses: $50K - $100K
💵 Small Team (2-3 SREs): $200K - $400K
💵 Total TCO: $250K - $500K
✅ Significantly lower personnel costs
Cost Comparison Summary
| Scenario | Kubernetes | OpenShift | Winner |
|---|---|---|---|
| Startup (10 nodes) | $100K-150K/year | $80K-120K/year | OpenShift |
| Mid-size (50 nodes) | $400K-800K/year | $200K-400K/year | OpenShift |
| Large (200+ nodes) | $1.5M-3M/year | $800K-1.5M/year | OpenShift |
| Cloud-managed K8s | EKS/GKE fees + team | N/A | Depends |
Key Insight:
💡 If you have < 10 experienced K8s engineers:
→ OpenShift often costs LESS due to reduced personnel needs
💡 If you have a large, experienced DevOps team:
→ Kubernetes can be cheaper for massive scale
🔄 Migration & Interoperability
Migrating Between Platforms
Kubernetes → OpenShift
Compatibility: ✅ HIGH
✅ Standard K8s resources work (90%+ compatible)
✅ Use `oc` CLI (supports kubectl commands)
✅ Existing Helm charts mostly work
✅ YAML manifests need minimal changes
Changes Needed:
# Security: OpenShift runs containers as non-root
❗ Update SecurityContext in deployments
❗ Use Routes instead of Ingress (or both)
❗ Add OpenShift-specific labels/annotations
❗ Adjust for Security Context Constraints (SCC)
Migration Effort: 🟢 LOW to MEDIUM
- 1-2 weeks for small apps
- 1-2 months for complex applications
- Use
odoors2ifor simplified deployments
OpenShift → Kubernetes
Compatibility: ⚠️ MEDIUM
✅ Core resources (Pods, Services) work
⚠️ Routes → need Ingress conversion
⚠️ BuildConfigs → need external CI/CD
⚠️ ImageStreams → need external registry
⚠️ DeploymentConfigs → convert to Deployments
❗ Lose OpenShift-specific features
Changes Needed:
# Replace OpenShift objects with K8s equivalents
❗ Convert Routes → Ingress
❗ Set up external image registry
❗ Implement CI/CD pipelines (Jenkins, Tekton)
❗ Relax security (containers may need root)
❗ Add monitoring/logging stack
Migration Effort: 🟡 MEDIUM to HIGH
- 1-3 months for most applications
- Need to replicate OpenShift's built-in features
- Possible architecture redesign
Multi-Cluster & Hybrid Strategies
Option 1: Pure Kubernetes
├── AWS (EKS)
├── Azure (AKS)
└── GCP (GKE)
Tools: Rancher, Anthos, Crossplane
Option 2: Pure OpenShift
├── On-premise (OCP)
├── AWS (ROSA)
└── Azure (ARO)
Tools: Red Hat Advanced Cluster Management (ACM)
Option 3: Hybrid (Both)
├── OpenShift (Critical apps, on-prem)
└── Kubernetes (Dev/test, cloud)
Complexity: HIGH
🔮 Future Trends & Evolution
Kubernetes Trajectory
Current Focus (2026):
- 🎯 Simplification - Making K8s easier to use
- 🔐 Security - Pod Security Standards (PSS)
- 🌐 Edge Computing - K3s, MicroK8s for edge
- 🤖 AI/ML Workloads - GPU scheduling, Kubeflow
- 📊 Observability - Better built-in monitoring
Emerging Trends:
→ Serverless on K8s (Knative)
→ WebAssembly (Wasm) support
→ Multi-tenancy improvements
→ Cluster API standardization
→ eBPF networking integration
OpenShift Evolution
Current Focus (2026):
- 🚀 GitOps Native - Deeper ArgoCD integration
- 🤖 AI/ML Platform - Red Hat OpenShift AI
- 🖥️ Virtualization - OpenShift Virtualization (KubeVirt)
- 🔗 Edge & IoT - MicroShift for edge devices
- 🛡️ Zero Trust - Advanced security features
Strategic Direction:
→ Unified platform: VMs + Containers + Serverless
→ Developer experience improvements (IDEs, CLIs)
→ Multi-cluster management enhancements
→ AI/ML workload optimization
→ Sustainability & power efficiency
Industry Predictions
Next 2-3 Years:
📈 Kubernetes adoption: 90%+ of enterprises
📈 OpenShift growth: Strong in regulated industries
📈 Serverless on K8s: Major adoption
📉 Docker Swarm, Nomad: Declining usage
🆕 New patterns: GitOps, Platform Engineering
Converging Features:
Both platforms are becoming more similar:
- K8s adding more built-in features
- OpenShift maintaining upstream compatibility
- Industry standards emerging (Gateway API, etc.)
🎓 Learning Path Recommendations
For Kubernetes
Beginner → Intermediate (3-6 months):
- Learn container basics (Docker)
- Understand K8s architecture
- Practice with Minikube locally
- Study CKA (Certified Kubernetes Administrator) material
- Deploy sample apps
- Learn Helm for package management
Intermediate → Advanced (6-12 months):
- Study CKAD (Certified Kubernetes Application Developer)
- Learn operators and custom resources
- Practice with production-grade clusters
- Study CKS (Certified Kubernetes Security)
- Contribute to K8s ecosystem
For OpenShift
Beginner → Intermediate (2-4 months):
- Learn container basics (Docker/Podman)
- Understand K8s fundamentals
- Use CodeReady Containers locally
- Study EX180 (Red Hat Certified Specialist)
- Practice with oc CLI
- Deploy apps using S2I
Intermediate → Advanced (4-8 months):
- Study EX280 (OpenShift Administration)
- Learn OpenShift operators
- Practice CI/CD with OpenShift Pipelines
- Study EX288 (OpenShift Developer)
- Master security (SCC, network policies)
Pro Tip:
🎯 Learn Kubernetes FIRST, then OpenShift
→ OpenShift = K8s + extras
→ K8s skills transfer 90% to OpenShift
→ OpenShift skills transfer 60% to K8s
📚 Resources
| Resource | Link |
|---|---|
| Kubernetes Docs | kubernetes.io/docs |
| OpenShift Docs | docs.openshift.com |
| Red Hat OpenShift Learning | developers.redhat.com |
| CNCF Kubernetes | cncf.io |
| Kubernetes Training | kubernetes.io/training |
| Red Hat Training | redhat.com/training |
| CNCF Landscape | landscape.cncf.io |
| OpenShift Blog | cloud.redhat.com/blog |
Last updated: February 2026