01
Engineering Workflow
Start with source and change control.
- Git model and collaboration
- Branching strategies
- Pull / merge workflows
- Artifact lifecycle
- Release thinking
All training programs
SOURCE → AUTOMATE → PACKAGE → DEPLOY → OPERATE
DevOps & Platform Engineering
Connect source control, CI/CD, infrastructure automation, containers, Kubernetes and observability into a coherent engineering delivery system.
Outcomes
Design reliable delivery workflows
Automate repeatable infrastructure and configuration tasks
Package and run applications using containers
Operate Kubernetes with observability and troubleshooting practices
Audience & prerequisites
Who it is for— DevOps engineers— Platform engineers— System administrators moving into automation— Application teams working with cloud-native delivery
Prerequisites— Basic Linux and networking— Git fundamentals are helpful but can be included
Representative curriculum
Training topics, organized as engineering modules.
The exact sequence is adjusted to the audience. Foundation topics can be compressed for experienced teams; architecture and troubleshooting can be expanded for advanced programs.
02
CI/CD
Turn change into a controlled delivery pipeline.
- Pipeline stages
- Build and test automation
- Secrets and credentials
- Quality / security gates
- Promotion and rollback
03
Infrastructure Automation
Make infrastructure changes repeatable.
- Ansible fundamentals
- Roles and variables
- Idempotency
- Templates and handlers
- Automation controller concepts
04
Containers
Understand images, runtime and isolation.
- Container architecture
- Dockerfiles and image design
- Networking and storage
- Security
- Troubleshooting
05
Kubernetes & Platforms
Operate applications on a distributed orchestration platform.
- Cluster architecture
- Workloads and services
- Configuration and secrets
- Storage and networking
- Scheduling, scaling and troubleshooting
06
Observability & Reliability
Measure the platform and understand failure.
- Metrics, logs and traces
- Prometheus
- Grafana
- Alert design
- SLO / incident concepts
Hands-on work
Labs are part of the learning path.
Exercises emphasize observation, implementation, failure and diagnosis rather than command copying.
01
Build a CI pipeline
02
Automate configuration with Ansible
03
Containerize a service
04
Deploy and troubleshoot a Kubernetes workload
05
Create Prometheus alerts and a Grafana dashboard
Customization
Align the program to your engineering environment.
Tooling can be adapted around GitHub Actions, GitLab, Jenkins, AAP, Kubernetes distributions and the customer's current platform stack.
GitCI/CDAnsibleDockerKubernetesHelmPrometheusGrafanaInfrastructure automation