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.

Typical duration3–10 days depending on depth and platform scope

DeliveryOnline · On-site · Hybrid · Architecture lab

Practical work5 representative labs

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.

Engineering Workflow

Start with source and change control.

Git model and collaboration
Branching strategies
Pull / merge workflows
Artifact lifecycle
Release thinking

CI/CD

Turn change into a controlled delivery pipeline.

Pipeline stages
Build and test automation
Secrets and credentials
Quality / security gates
Promotion and rollback

Infrastructure Automation

Make infrastructure changes repeatable.

Ansible fundamentals
Roles and variables
Idempotency
Templates and handlers
Automation controller concepts

Containers

Understand images, runtime and isolation.

Container architecture
Dockerfiles and image design
Networking and storage
Security
Troubleshooting

Kubernetes & Platforms

Operate applications on a distributed orchestration platform.

Cluster architecture
Workloads and services
Configuration and secrets
Storage and networking
Scheduling, scaling and troubleshooting

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.

Build a CI pipeline

Automate configuration with Ansible

Containerize a service

Deploy and troubleshoot a Kubernetes workload

Create Prometheus alerts and a Grafana dashboard

CONNECTED PATHS

Turn the learning path into production context.

Explore Knowledge Hub

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Architecture and modernization guidance for cloud infrastructure, platform services, networking, observability and workload migration.

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Independent engineering guidance for organizations making architecture, platform, modernization or technology-selection decisions across connected systems.

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ConsultingLinux & Open Source