Kubernetes Cloud Deployment and Operations Training Course

Course overview

Kubernetes teams are expected to release services reliably while controlling cloud spend, maintaining secure configurations and resolving incidents before customers are affected. Many administrators can deploy a container, yet lack a repeatable operating model for namespaces, workload health, ingress, secrets, upgrades, observability and recovery. This course addresses that gap by connecting Kubernetes configuration choices to day-to-day operational outcomes: availability, deployment safety, access control, capacity use and incident response.

Participants build and operate a Kubernetes application environment using declarative YAML manifests, kubectl, Helm and Terraform. They learn to configure Pods, Deployments, Services, ConfigMaps, Secrets, Ingress, resource requests and limits, probes, autoscaling and persistent storage. The course also covers role-based access control, network segmentation, release strategies, cluster monitoring with Prometheus, log and event investigation, backup considerations, and practical runbooks for common production failures.

Instructor-led demonstrations are followed by guided cloud-style lab scenarios in which participants deploy a multi-tier application, expose it securely, monitor its health and remediate deliberately introduced faults. Teams work through operational decisions such as choosing rollout controls, diagnosing CrashLoopBackOff errors, responding to resource pressure and rolling back an unsuccessful release. Each participant leaves with a documented Kubernetes deployment and operations pack: manifests, Helm values, Terraform configuration, monitoring queries, an operational checklist and an incident runbook that can be adapted for their workplace.

Course objectives

By the end of this course, participants will be able to:

• Create declarative Kubernetes manifests for Deployments, Services, ConfigMaps, Secrets and Ingress resources
• Deploy and upgrade packaged applications using Helm charts, values files and release rollback commands
• Provision repeatable Kubernetes infrastructure and supporting cloud resources with Terraform modules
• Configure resource requests, limits, liveness probes, readiness probes and Horizontal Pod Autoscalers
• Apply namespace isolation, Role-Based Access Control policies and NetworkPolicy rules for workload access
• Diagnose failed workloads using kubectl logs, describe output, events and container status conditions
• Build Prometheus-based monitoring queries and alert conditions for application and cluster health
• Produce a Kubernetes operations runbook covering deployment, rollback, incident triage and recovery actions

Benefits of attending

Target competencies

Who should attend

• Cloud Engineers — who need to deploy and support containerised services on Kubernetes
• Systems Administrators — who are moving from server administration to cluster-based operations
• DevOps Engineers — who need consistent release, rollback and observability practices for Kubernetes workloads
• Platform Engineers — who establish reusable deployment patterns, access controls and operational guardrails
• Software Engineers — who package applications for reliable deployment and troubleshooting in Kubernetes
• Technical Team Leads — who must assess Kubernetes operating risks, responsibilities and support readiness

Requirements and prerequisites

Participants should be comfortable using a command line, navigating files, editing text-based configuration files and reading basic application logs. Familiarity with Linux processes, TCP/IP concepts, DNS, HTTP and either AWS, Azure or Google Cloud terminology is helpful. Participants should understand what containers are and have seen Docker images or Dockerfiles, although they do not need prior Kubernetes administration experience. Basic YAML awareness is useful because manifests are edited throughout the course. No programming background, prior Helm or Terraform use, production cluster access or cloud certification is required.

Training methodology

The course combines short instructor-led technical briefings with live configuration demonstrations and progressive hands-on labs. Participants work in a Kubernetes lab environment, using kubectl to inspect cluster state and edit manifests that are then deployed, tested and deliberately stressed. Case scenarios introduce failed releases, unavailable services, access-control issues and resource contention; teams diagnose evidence and agree remediation steps. Daily exercises produce working artefacts, culminating in an application deployment and operations plan reviewed against practical reliability, security and support criteria.

Course outline

Day 1: Kubernetes foundations and workload deployment

• Kubernetes control plane, worker node and cluster component responsibilities
• Namespaces, labels, annotations and Kubernetes object metadata
• Pod lifecycle, container image references and restart policies
• Deployment controllers, ReplicaSets and declarative desired state
• kubectl context management, resource inspection and manifest application
• YAML manifest structure, selectors and label matching
• Service types, internal DNS and basic service discovery

Workshop: Deploy a two-tier application from YAML manifests and produce a resource map showing its Pods, Deployments and Services.

Day 2: Application configuration, exposure and releases

• ConfigMaps and Secrets for externalised application configuration
• Volume mounts, environment variables and secret consumption patterns
• Ingress resources, ingress controllers and HTTP routing rules
• PersistentVolume, PersistentVolumeClaim and storage class concepts
• Helm chart structure, templates, values files and release metadata
• Helm install, upgrade, history and rollback workflows
• Rolling updates, revision history and controlled deployment strategies

Workshop: Package and release an application with Helm, configure ingress routing and demonstrate a controlled rollback from a failed version.

Day 3: Cloud infrastructure, resilience and scaling

• Terraform providers, state files, variables and outputs for Kubernetes environments
• Terraform modules for repeatable cloud and cluster-supporting resources
• CPU and memory requests, limits and quality-of-service classes
• Liveness, readiness and startup probes for workload health management
• Horizontal Pod Autoscaler metrics and scaling behaviour
• PodDisruptionBudgets and availability during voluntary disruptions
• Node scheduling, taints, tolerations and affinity rules

Workshop: Use Terraform configuration and Kubernetes resource controls to deploy a scalable service, then produce a capacity and resilience configuration sheet.

Day 4: Security, observability and incident diagnosis

• Role-Based Access Control roles, bindings, service accounts and least privilege
• NetworkPolicy rules for namespace and workload traffic segmentation
• Image provenance, registry access and secret-handling practices
• Prometheus metric types, labels and PromQL query fundamentals
• Application and cluster health dashboards and alert thresholds
• kubectl logs, describe, events and exec for fault investigation
• Failure patterns including ImagePullBackOff, CrashLoopBackOff and pending Pods

Workshop: Investigate a simulated production incident using kubectl and Prometheus, then produce an evidence-based incident timeline and remediation plan.

Day 5: Operational readiness and production practices

• Deployment checklists, change controls and release approval evidence
• Backup and recovery considerations for persistent application data
• Cluster upgrade planning, version compatibility and workload validation
• Resource quota, limit range and namespace governance controls
• Cost-aware capacity management and unused resource identification
• Operational runbooks, escalation paths and service ownership models
• Post-incident reviews and improvement actions for Kubernetes services

Workshop: Complete an operational readiness workshop and produce a deployable application pack containing manifests, monitoring checks, rollback steps and an incident runbook.

Tools & standards covered

kubectl, Helm, Terraform, Prometheus

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions