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Master’s in Software, DevOps and Operations Engineering

Online master's programme of 1,900 hours in software engineering, DevOps and operations, structured in 12 modules covering software architecture, testing, CI/CD, containers and Kubernetes, infrastructure as code, cloud platforms, observability, SRE incident management and DevSecOps, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Apply professional software engineering practices and agile methodologies.

02

Design maintainable and scalable software architectures.

03

Implement automated testing strategies.

04

Build continuous integration and delivery pipelines.

05

Deploy applications with containers and infrastructure as code.

06

Operate services with observability and SRE practices.

07

Develop a complete software system with an integrated DevOps cycle.

Profile

Who it's for

  • DevOps engineers
  • Site reliability engineers (SRE)
  • Platform engineers
  • Software architects
  • Backend software engineers
  • DevSecOps engineers
  • Engineering or science graduates looking to move into technology and software
Standards & tools

What you'll work with

  • ISO/IEC 25010 (software product quality model)
  • ISO/IEC/IEEE 12207 (software life cycle processes)
  • ISO/IEC 27001 (information security management systems)
  • ISO/IEC 20000-1 (IT service management)
  • OWASP ASVS (application security verification standard)
  • SLSA v1.0 (supply-chain levels for software artifacts)
  • ISO/IEC/IEEE 29119 (software testing)
  • ITIL 4 (IT service management framework)
  • GitLab CI
  • Kubernetes
  • Terraform
  • Prometheus
  • Grafana
Syllabus

12 modules · 1900 h

  1. 1.1. Software life cycle and process models
  2. 1.2. Agile methodologies: Scrum and Kanban
  3. 1.3. Requirements engineering and user stories
  4. 1.4. Project estimation and planning
  5. 1.5. Software quality according to ISO/IEC 25010
  6. 1.6. Technical debt and how to manage it
  7. 1.7. Living technical documentation
  8. 1.8. Working in distributed teams
  9. 1.9. DORA performance metrics
  10. 1.10. Case study: maturity assessment of a team
  1. 2.1. SOLID principles and clean design
  2. 2.2. Classic design patterns
  3. 2.3. Hexagonal and layered architecture
  4. 2.4. Microservices versus modular monolith
  5. 2.5. Domain-driven design
  6. 2.6. Architecture based on domain events
  7. 2.7. Architecture decision records
  8. 2.8. Quality attributes and trade-offs
  9. 2.9. Modelling with C4 and UML
  10. 2.10. Workshop: refactoring a monolith into modules
  1. 3.1. Git in depth
  2. 3.2. Trunk-based and GitFlow branching strategies
  3. 3.3. Code review and pull requests
  4. 3.4. Commit conventions and semantic versioning
  5. 3.5. Monorepos and dependency management
  6. 3.6. Conflict management and rebase
  7. 3.7. Hooks and local automation
  8. 3.8. Repository governance
  9. 3.9. GitHub and GitLab platforms
  10. 3.10. Practical exercise: trunk-based workflow with mandatory reviews
  1. 4.1. The testing pyramid
  2. 4.2. Unit tests and test doubles
  3. 4.3. Test-driven development
  4. 4.4. Integration and contract testing
  5. 4.5. End-to-end testing
  6. 4.6. Performance and load testing
  7. 4.7. Property-based testing
  8. 4.8. Coverage and mutation testing
  9. 4.9. Test data management
  10. 4.10. Lab: test suite with pytest and Testcontainers
  1. 5.1. Principles of continuous integration
  2. 5.2. Pipelines with GitHub Actions and GitLab CI
  3. 5.3. Reproducible artefact builds
  4. 5.4. Artefact and container registries
  5. 5.5. Continuous delivery and deployment
  6. 5.6. Blue-green and canary strategies
  7. 5.7. Feature flags and progressive deployment
  8. 5.8. Software supply chain integrity
  9. 5.9. Pipeline time optimisation
  10. 5.10. Practical exercise: complete pipeline for an API
  1. 6.1. Containers with Docker
  2. 6.2. Minimal and multi-stage images
  3. 6.3. Kubernetes: pods, deployments and services
  4. 6.4. Configuration and secrets
  5. 6.5. Persistent storage with volumes
  6. 6.6. Horizontal and vertical autoscaling
  7. 6.7. Helm and Kustomize
  8. 6.8. Service mesh with Istio and Linkerd
  9. 6.9. Kubernetes at the edge
  10. 6.10. Lab: deployment on Kubernetes with Helm
  1. 7.1. Principles of immutable infrastructure
  2. 7.2. Terraform and OpenTofu
  3. 7.3. State management and modules
  4. 7.4. Ansible for configuration
  5. 7.5. GitOps with Argo CD and Flux
  6. 7.6. Infrastructure testing
  7. 7.7. Environment management
  8. 7.8. Policy as code with OPA
  9. 7.9. Cloud cost control
  10. 7.10. Workshop: complete environment with Terraform and Argo CD
  1. 8.1. IaaS, PaaS and serverless models
  2. 8.2. Compute services on AWS, Azure and GCP
  3. 8.3. Virtual networks and perimeter security
  4. 8.4. Managed databases
  5. 8.5. Function-oriented serverless architectures
  6. 8.6. Design for high availability
  7. 8.7. Disaster recovery plans
  8. 8.8. Well-architected framework
  9. 8.9. Internal platform engineering
  10. 8.10. Case study: migrating an application to the cloud
  1. 9.1. Metrics, logs and traces
  2. 9.2. Instrumentation with OpenTelemetry
  3. 9.3. Prometheus and Grafana
  4. 9.4. Distributed tracing across services
  5. 9.5. Service level objectives
  6. 9.6. Error budgets
  7. 9.7. Designing actionable alerts
  8. 9.8. Chaos engineering
  9. 9.9. Capacity and performance
  10. 9.10. Practical exercise: defining SLOs and alerts for a service
  1. 10.1. SRE practices
  2. 10.2. On-call management
  3. 10.3. Incident response
  4. 10.4. Blameless postmortems
  5. 10.5. Change management
  6. 10.6. Runbooks and automation
  7. 10.7. Problem management
  8. 10.8. Communication during incidents
  9. 10.9. ITIL 4 and DevOps
  10. 10.10. Workshop: incident drill and postmortem
  1. 11.1. Security by design
  2. 11.2. SAST static analysis
  3. 11.3. SCA dependency analysis
  4. 11.4. DAST dynamic analysis
  5. 11.5. Container and infrastructure scanning
  6. 11.6. Secrets management with Vault
  7. 11.7. Artefact signing with Sigstore
  8. 11.8. SLSA supply chain framework
  9. 11.9. Automated regulatory compliance
  10. 11.10. Lab: pipeline with integrated security scanning
  1. 12.1. Definition of the software system
  2. 12.2. Architecture and design
  3. 12.3. Implementation and testing
  4. 12.4. Integration and delivery pipeline
  5. 12.5. Infrastructure and deployment
  6. 12.6. Observability and operation
  7. 12.7. Quality assessment and metrics
  8. 12.8. Conclusions on the DevOps cycle
  9. 12.9. Thesis report
  10. 12.10. Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is GitLab CI, Kubernetes, Terraform, Prometheus and Grafana, in free, academic or evaluation versions. Practical work is based on real procedures: building continuous integration and delivery pipelines, deploying applications on Kubernetes clusters, defining service level objectives and running incident drills. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO/IEC 25010, ISO/IEC/IEEE 12207, ISO/IEC 27001, ISO/IEC 20000-1, OWASP ASVS, SLSA v1.0, ISO/IEC/IEEE 29119, ITIL 4.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO/IEC 25010, ISO/IEC/IEEE 12207 and ISO/IEC 27001 applied to real cases, not as a theoretical annex.
Industry software:GitLab CI, Kubernetes, Terraform, Prometheus and Grafana, in free, academic or evaluation versions.
Master's Thesis with defence:A complete software system with an integrated DevOps cycle, from architecture to operation, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Architecture and design
Define the software system and design its architecture.
Implementation and testing
Implement the system with an automated test strategy.
CI/CD pipeline
Build the integration and delivery pipeline with integrated security scanning.
Infrastructure and observability
Deploy with infrastructure as code and define SLOs, alerts and operation.
Master's Thesis
Assess quality and DevOps metrics in the final report, defended before a panel.
Career opportunities

Where this takes you

DevOps engineerSite reliability engineer (SRE)Platform engineerSoftware architectBackend software engineerDevSecOps engineer
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • Internet connection and a computer capable of running the programme's software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with GitLab CI, Kubernetes, Terraform, Prometheus and Grafana, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

Master’s in Software, DevOps and Operations EngineeringEnrol
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