Kubernetes Fundamentals

Duration: 3 days | Level: Beginner to intermediate | Max participants: 16

Prerequisites: Basic Linux command line, familiarity with web application deployment concepts. No prior container or Kubernetes experience required.

What's included: Slide decks, lab environment access (72 hours post-training), exercise repository, and a reference cheat sheet.

• Container fundamentals and Docker best practices
• Kubernetes architecture: pods, services, deployments, namespaces
• Configuration: ConfigMaps, Secrets, environment variables
• Storage: PersistentVolumes, StatefulSets
• Networking: Services, Ingress, DNS, network policies
• Troubleshooting: logs, events, exec, resource debugging
• Lab: Deploy a multi-tier application on a real cluster

Kubernetes Advanced Operations

Duration: 2 days | Level: Intermediate to advanced | Max participants: 12

Prerequisites: Working knowledge of Kubernetes (pods, deployments, services). Completion of Kubernetes Fundamentals or equivalent experience operating clusters.

What's included: Slide decks, lab environment with multi-node cluster access (72 hours post-training), Helm chart starter templates, and GitOps repository scaffold.

• Cluster administration: upgrades, backup, disaster recovery
• Security: RBAC, Pod Security Standards, OPA/Gatekeeper
• Observability: Prometheus, Grafana, log aggregation
• Autoscaling: HPA, VPA, cluster autoscaler, KEDA
• Helm chart development and management
• GitOps with Argo CD or Flux
• Lab: Set up a full observability stack and GitOps pipeline

CI/CD Pipeline Engineering

Duration: 2 days | Level: Intermediate | Max participants: 16

Prerequisites: Experience with Git (branching, pull requests). Basic understanding of Docker and containerization. Familiarity with at least one CI platform (GitHub Actions, GitLab CI, or Jenkins).

What's included: Slide decks, reusable workflow templates for GitHub Actions and GitLab CI, pipeline architecture decision guide, and example repository.

• Pipeline design patterns and anti-patterns
• GitHub Actions: workflows, reusable actions, matrix builds
• GitLab CI: pipelines, includes, child pipelines
• Container image building: multi-stage builds, caching, security scanning
• Deployment strategies: blue-green, canary, rolling updates
• Self-hosted runners: setup, autoscaling, security
• Lab: Build a complete CI/CD pipeline from commit to production

Infrastructure as Code with Terraform

Duration: 2 days | Level: Beginner to intermediate | Max participants: 16

Prerequisites: Basic understanding of cloud services (AWS, GCP, or Azure). Comfort with the command line. No prior Terraform experience required.

What's included: Slide decks, lab environment with cloud sandbox account, starter module library, and CI pipeline template for Terraform.

• Terraform fundamentals: providers, resources, state
• Module design: reusable, composable infrastructure
• State management: remote backends, locking, workspaces
• Testing: plan validation, Terratest, policy-as-code
• Multi-environment patterns: dev/staging/production
• Team workflows: code review, CI for infrastructure
• Lab: Build and deploy a multi-tier cloud environment

Cloud Operations & SRE

Duration: 2 days | Level: Intermediate | Max participants: 16

Prerequisites: Experience operating production systems. Familiarity with monitoring concepts (metrics, logs). Understanding of basic cloud infrastructure (compute, networking, storage).

What's included: Slide decks, SLO worksheet and calculator, incident response template kit, runbook templates, and monitoring dashboard examples.

• SRE principles: SLIs, SLOs, error budgets
• Incident management: detection, response, postmortems
• Monitoring strategy: metrics, logs, traces, dashboards
• Cost management: tagging, budgets, optimization
• Security operations: hardening, compliance, audit prep
• On-call practices: runbooks, escalation, rotation
• Lab: Set up SLO-based monitoring and incident response workflow

Docker & Container Security

Duration: 1 day | Level: Beginner to intermediate | Max participants: 16

Prerequisites: Basic Docker experience (building and running containers). Familiarity with Linux file system and process concepts.

What's included: Slide decks, hardened Dockerfile templates, scanning pipeline configuration, and container security checklist.

• Container image best practices: minimal base images, layer optimization
• Image scanning and vulnerability management
• Runtime security: read-only filesystems, capability dropping
• Secrets management in containerized environments
• Supply chain security: signing, SBOM, provenance
• Lab: Harden a container image and set up a scanning pipeline

We build custom training programs tailored to your team:

• Stack-specific — Training on your actual cloud provider, CI/CD system, and tools
• Project-based — Learn by working on a real project from your backlog
• Skill assessment — Pre-training evaluation to calibrate content to your team's level
• Follow-up coaching — Post-training embedded support as your team applies what they learned

Our training content aligns with industry certifications:

• CKA — Certified Kubernetes Administrator
• CKAD — Certified Kubernetes Application Developer
• CKS — Certified Kubernetes Security Specialist
• HashiCorp Terraform Associate
• AWS Solutions Architect

• Immediate productivity — Hands-on labs mean engineers apply skills the next day
• Reduced external dependency — Your team handles more, you need less outside help
• Consistent skill baseline — Everyone on the same page with shared practices
• Retention signal — Engineers value employers who invest in their growth

• DevOps as a Service
• Technology Consulting
• Kubernetes Support