DevOps Trainings
Hands-on training programs for Kubernetes, CI/CD, IaC, and cloud operations
Bridge the gap between your team's current skills and where you need to be. Our training programs cover the full DevOps toolchain—from containers and orchestration to CI/CD pipelines and infrastructure as code.
Training formats#
| Format | Duration | Best for |
|---|---|---|
| On-site workshop | 1-5 days | Teams who learn best together with dedicated lab time |
| Remote live | Half-day sessions over 2-4 weeks | Distributed teams, minimal disruption to sprints |
| Self-paced | Flexible | Individual engineers, onboarding new hires |
| Embedded coaching | 2-8 weeks | Teams adopting new tools who need guidance on real work |
Curriculum overview#
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
Custom training#
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
Certification preparation#
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
Key benefits#
- 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
Getting started#
Want to upskill your team? Tell us about your stack, team size, and goals—we'll propose a training program.
Book a Training →