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Containerization And Virtualization in DevOps

Containerization And Virtualization in DevOps

$298.00
When you get access:
Course access is prepared after purchase and delivered via email
How you learn:
Self-paced • Lifetime updates
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Toolkit Included:
Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
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What does the Containerization And Virtualization in DevOps course cover?

Containerization And Virtualization in DevOps is covered here in 9 modules: Foundations of Virtualization in Enterprise Infrastructure, Container Architecture and Runtime Design, Image Management and Registry Operations and 6 more. The outline lists 72 specific topics, opening with selecting between full virtualization, paravirtualization, and hardware-assisted virtualization based on guest OS compatibility and performance requirements.

How do you approach Containerization And Virtualization in DevOps step by step?

The work is sequenced in 9 stages. It starts with Foundations of Virtualization in Enterprise Infrastructure, moves through Container Architecture and Runtime Design and Image Management and Registry Operations, and ends at Hybrid and Multi-Cloud Deployment Strategies. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the Containerization And Virtualization in DevOps course?

Module 1 is Foundations of Virtualization in Enterprise Infrastructure. It works through selecting between full virtualization, paravirtualization, and hardware-assisted virtualization based on guest OS compatibility and performance requirements., configuring CPU and memory overcommit ratios in hypervisors while maintaining SLA compliance for critical workloads., implementing NUMA-aware VM placement to avoid remote memory access penalties in multi-socket hosts. and 5 more.

How is the Containerization And Virtualization in DevOps course delivered?

The Containerization And Virtualization in DevOps course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Containerization And Virtualization in DevOps course cost?

The Containerization And Virtualization in DevOps course is $296 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Containerization And Virtualization in Virtualization, Virtualization Tools in DevOps, DevOps Fundamentals CI CD and Containerization Mastery.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the technical depth and operational breadth of a multi-workshop program focused on enterprise containerization and virtualization, comparable to an internal capability build-out for standardizing cloud-native infrastructure across hybrid environments.

Module 1: Foundations of Virtualization in Enterprise Infrastructure

  • Selecting between full virtualization, paravirtualization, and hardware-assisted virtualization based on guest OS compatibility and performance requirements.
  • Configuring CPU and memory overcommit ratios in hypervisors while maintaining SLA compliance for critical workloads.
  • Implementing NUMA-aware VM placement to avoid remote memory access penalties in multi-socket hosts.
  • Designing storage backends for VMs using thin vs. thick provisioning based on IOPS, capacity planning, and snapshot needs.
  • Integrating VMs with existing identity providers for console access and audit logging.
  • Establishing VM lifecycle policies for patching, decommissioning, and image version control.
  • Evaluating Type 1 vs. Type 2 hypervisors in regulated environments with strict isolation requirements.
  • Managing VM sprawl through automated tagging, resource quotas, and chargeback mechanisms.

Module 2: Container Architecture and Runtime Design

  • Choosing between container runtimes (runc, gVisor, Kata Containers) based on security, performance, and compatibility needs.
  • Defining resource limits and requests for CPU and memory in container manifests to prevent noisy neighbor issues.
  • Implementing init containers for pre-start dependency checks and configuration validation.
  • Configuring container health checks using liveness, readiness, and startup probes with appropriate thresholds.
  • Designing multi-stage Dockerfiles to minimize image size and reduce attack surface.
  • Managing container UID/GID mappings to prevent privilege escalation on host systems.
  • Enforcing seccomp, AppArmor, and SELinux profiles at runtime for defense-in-depth.
  • Handling PID and orphaned process management in long-running containerized services.

Module 3: Image Management and Registry Operations

  • Designing a multi-tenant container registry hierarchy with project-based access controls and retention policies.
  • Implementing image signing using Cosign or Notary to enforce supply chain integrity.
  • Automating vulnerability scanning in CI pipelines with tools like Trivy or Clair and defining severity thresholds for blocking.
  • Syncing images across geographically distributed registries to reduce pull latency and improve resiliency.
  • Creating base image governance policies that mandate patching cadence and owner accountability.
  • Managing image metadata through annotations for compliance, ownership, and deployment constraints.
  • Configuring registry garbage collection and storage cleanup to avoid disk exhaustion.
  • Integrating image promotion workflows with GitOps pipelines using semantic versioning.

Module 4: Orchestration with Kubernetes in Production

  • Designing node pools with taints and tolerations to isolate workloads by security level or hardware type.
  • Implementing PodDisruptionBudgets to maintain availability during node maintenance or cluster upgrades.
  • Configuring custom resource definitions (CRDs) with validation schemas and admission controllers.
  • Setting up horizontal and vertical pod autoscaling with metrics from custom Prometheus exporters.
  • Managing stateful applications using StatefulSets with persistent volume claims and storage classes.
  • Implementing network policies to restrict pod-to-pod communication based on zero-trust principles.
  • Using init containers to enforce preconditions before application startup in multi-container pods.
  • Planning for etcd backup and restore procedures with regular snapshot testing.

Module 5: Networking Models and Service Connectivity

  • Selecting CNI plugins (Calico, Cilium, Flannel) based on network policy enforcement and performance needs.
  • Designing service mesh integration using sidecar injection and mTLS for inter-service encryption.
  • Configuring ingress controllers with rate limiting, WAF integration, and TLS termination.
  • Implementing multi-cluster service discovery using federated DNS or service mesh gateways.
  • Managing external access through NodePort, LoadBalancer, or MetalLB in on-prem environments.
  • Resolving DNS latency issues by tuning CoreDNS cache settings and upstream resolvers.
  • Isolating development, staging, and production traffic using namespace-level network policies.
  • Debugging hairpinning and SNAT issues in NAT-heavy environments with custom iptables rules.

Module 6: Persistent Storage and Data Management

  • Selecting storage classes (SSD, HDD, NVMe) based on application I/O patterns and cost constraints.
  • Implementing dynamic provisioning with CSI drivers for cloud and on-prem storage systems.
  • Designing backup and restore workflows for stateful applications using Velero with application consistency hooks.
  • Managing access modes (ReadWriteOnce, ReadWriteMany) for shared filesystems in clustered applications.
  • Handling volume resizing operations with minimal downtime and application impact.
  • Monitoring storage utilization and IOPS to detect misconfigured PVCs or runaway processes.
  • Integrating with enterprise storage solutions (NetApp, Pure Storage) using vendor-specific CSI plugins.
  • Enforcing data retention and encryption policies at the storage layer for compliance.

Module 7: Security, Compliance, and Runtime Enforcement

  • Implementing admission controllers (OPA Gatekeeper, Kyverno) to enforce organizational policies on resource creation.
  • Conducting regular node hardening audits using CIS benchmarks and automated scanning tools.
  • Managing secrets using external vaults (HashiCorp Vault) with short-lived tokens and rotation policies.
  • Enabling audit logging for Kubernetes API server and filtering events based on sensitivity.
  • Configuring pod security standards (restricted, baseline, privileged) across namespaces.
  • Performing runtime threat detection using Falco or Sysdig to monitor for anomalous process execution.
  • Integrating container security into CI/CD with pre-commit hooks and policy-as-code checks.
  • Responding to container breakout incidents with host-level containment and forensic collection.

Module 8: Observability and Day 2 Operations

  • Deploying distributed tracing for microservices using OpenTelemetry and backend collectors.
  • Configuring structured logging pipelines with Fluentd or Vector and enforcing JSON schema compliance.
  • Setting up SLOs and error budgets using Prometheus metrics and alerting via Alertmanager.
  • Managing log retention and indexing costs by filtering low-value logs at the source.
  • Diagnosing performance bottlenecks using container-level CPU, memory, and network profiling.
  • Implementing cluster health dashboards with Grafana for infrastructure and application metrics.
  • Automating routine operations (node rotation, certificate renewal) using operators and CronJobs.
  • Conducting chaos engineering experiments to validate resilience of containerized systems.

Module 9: Hybrid and Multi-Cloud Deployment Strategies

  • Designing cluster federation models for workload portability across AWS, Azure, and on-prem environments.
  • Managing configuration drift using GitOps tools (ArgoCD, Flux) with environment-specific overlays.
  • Implementing hybrid DNS and service discovery to bridge cloud and data center workloads.
  • Optimizing cross-cloud data transfer costs using caching, compression, and scheduling.
  • Enforcing consistent security policies across clusters using centralized policy engines.
  • Handling cloud provider-specific IAM roles and service accounts in multi-cloud Kubernetes.
  • Planning for disaster recovery using active-passive cluster configurations and data replication.
  • Monitoring cloud spending by namespace and team using cost allocation tools like Kubecost.
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