Cloud DevOps
Engineering.
Learn how applications move from source code to reliable cloud environments through Linux, containers, automation, infrastructure as code, orchestration, monitoring and practical production operations.
Duration
8 weeks
Learning format
Physical or remote
Core tools
Docker, Kubernetes, Terraform and GitHub Actions
Course outcome
Automated deployment and observability project
Learn what happens
after the code is written.
The programme connects development, infrastructure and operations. You will work through the practices used to build repeatable environments, automate delivery and understand the health of running services.
From Git commit to deployed service
Learn how source control, automated tests, image builds, artefact storage, environment configuration and deployment stages combine into a controlled delivery pipeline.
Operate what you deploy
Deployment is only the beginning. The course also covers health checks, logs, metrics, dashboards, alerts, troubleshooting, recovery and practical incident response.
A practical
DevOps toolchain.
Tools are taught as parts of a delivery system rather than as isolated commands. The emphasis remains on the engineering problem each tool helps solve.
Linux and Git
Command-line work, files, processes, permissions, networking, repositories, branches and collaborative version control.
Docker
Images, containers, Dockerfiles, build contexts, volumes, networking, Compose and smaller production images.
Kubernetes
Pods, Deployments, Services, namespaces, configuration, secrets, scaling, rollouts and workload health.
GitHub Actions
Automated tests, builds, environment controls, secrets, artefacts and deployment workflows.
Terraform
Infrastructure definitions, plans, state, reusable modules, variables and controlled resource changes.
Prometheus and Grafana
Metrics, service health, dashboards, alerts and operational visibility.
Logs and tracing
Structured logs, centralised inspection, correlation and introductory distributed tracing concepts.
Security tooling
Secret handling, image scanning, dependency checks, permissions and infrastructure security controls.
What you will
build.
The capstone connects the full delivery lifecycle around a sample application so that each tool contributes to one coherent system.
Containerised application
Package an application with repeatable dependencies, configuration, networking and local multi-service orchestration.
Automated pipeline
Run validation, tests, builds and deployment stages from a version-controlled workflow.
Provisioned infrastructure
Define and create the required cloud or lab infrastructure using reusable Terraform configuration.
Orchestrated deployment
Deploy the application with configuration, service discovery, controlled rollouts and workload-health checks.
Monitoring dashboard
Collect relevant metrics and build dashboards that show application and infrastructure health.
Operational documentation
Document deployment, configuration, rollback, troubleshooting and handover procedures.
Eight-week
curriculum.
Each week adds another layer to the delivery platform, ending with an integrated capstone and operational handover.
01
Linux, networking and development environments
Terminal workflow, files, permissions, processes, services, ports, DNS, HTTP, SSH, Git and environment setup.
02
Containers and Docker
Dockerfiles, layers, images, containers, volumes, networks, Compose, multi-stage builds and container troubleshooting.
03
Kubernetes fundamentals
Pods, Deployments, Services, namespaces, ConfigMaps, Secrets, probes, scaling and rollout management.
04
Continuous integration and delivery
GitHub Actions workflows, jobs, runners, tests, artefacts, environment secrets, approvals and deployment stages.
05
Infrastructure as code
Terraform configuration, providers, variables, plans, state, modules, outputs and controlled infrastructure changes.
06
Monitoring, logging and observability
Metrics, dashboards, alerts, structured logs, tracing concepts, service-level signals and operational investigation.
07
Security, access and resilience
Secrets, RBAC, image and dependency scanning, network controls, backups, recovery, least privilege and safer pipeline design.
08
Capstone, failure simulation and handover
End-to-end deployment, monitored operation, troubleshooting, rollback, incident simulation and delivery documentation.
Who this course is
for.
The programme is suitable for people who understand basic technical concepts and want practical experience with deployment, infrastructure and operations.
Aspiring DevOps engineers
Learners seeking a structured introduction to deployment automation, cloud infrastructure and operational tooling.
Software developers
Developers who want to understand containers, pipelines, environments and how applications behave after release.
IT and infrastructure professionals
Technical professionals moving from manual system administration toward automation, cloud operations and infrastructure as code.
What you should know
before starting.
Deep cloud experience is not required, but learners should be ready to work regularly with terminals, configuration files and technical troubleshooting.
Recommended foundation
- Basic computer and operating-system knowledge.
- Comfort installing and configuring software.
- Introductory command-line experience.
- Basic understanding of applications and databases.
- Basic Git familiarity is helpful.
- Programming experience is helpful but not mandatory.
What you will need
- A computer capable of running containers and development tools.
- Reliable internet access for remote participation.
- Administrator access to your learning computer.
- A GitHub account and modern web browser.
- Access to the approved cloud or lab environment.
- Time for practical exercises and the capstone project.
Learn to automate, deploy and operate modern applications.
Complete the training application to select your preferred learning format. Current fees, cohort dates, availability, equipment requirements and payment instructions are confirmed during registration.