Understand the delivery lifecycle
Learn how code, infrastructure, testing, deployment, and operations connect.
DevOps · Continuous delivery and operations
DevOps
Combine development and operations through Git, Linux, CI/CD, containers, Kubernetes, infrastructure as code, cloud deployment, monitoring, security, and automation.
Learn how teams move code from commit to production through repeatable workflows while improving delivery speed, reliability, visibility, and recovery.
Course overview
DevOps combines development, operations, automation, quality, security, and collaboration to improve the way software is delivered and operated.
This course begins with DevOps culture, version control, Linux, scripting, and repeatable environments. It then progresses through CI/CD, Docker, Kubernetes, cloud deployment, infrastructure as code, observability, security, and incident response.
The proposed capstone is a CI/CD pipeline that builds, tests, packages, scans, deploys, and verifies a sample application in a controlled environment.
DevOps is not just a collection of tools. It is a way to improve the flow of valuable changes while maintaining reliability, security, feedback, collaboration, and responsible operations.
Prerequisites
The course is designed for learners with basic computer knowledge who want to explore software delivery and infrastructure workflows.
- Basic computer and file-management knowledge.
- Basic understanding of applications and web services.
- Basic terminal familiarity is helpful.
- Basic Git knowledge is recommended.
- Basic networking concepts are useful.
- Prior cloud or Kubernetes experience is not required.
Readiness activity
Draw a simple workflow from a developer commit to a deployed application. Include source control, automated tests, a build artifact, deployment, monitoring, and rollback.
Who can explore this course?
Improve release workflows
Explore automation, testing, packaging, environments, observability, and recovery.
Automate infrastructure tasks
Connect Linux, containers, networking, cloud, configuration, and operational practices.
Prepare for cloud-native delivery
Explore Kubernetes, infrastructure as code, CI/CD, monitoring, and security.
What you will learn
- Explain DevOps culture, collaboration, and delivery principles.
- Use Git workflows for branching, review, and release history.
- Work with Linux commands, processes, services, and logs.
- Automate repeatable tasks with scripts and configuration.
- Build CI pipelines with tests and quality checks.
- Package applications with Docker containers.
- Deploy and manage workloads with Kubernetes concepts.
- Provision infrastructure using infrastructure-as-code concepts.
- Deploy workloads to cloud environments.
- Monitor logs, metrics, traces, health, and deployment outcomes.
- Apply security checks throughout the delivery lifecycle.
- Build and document a complete CI/CD capstone project.
Curriculum outline
The ten-module outline moves from DevOps foundations to a complete delivery pipeline. Tools may vary by delivery environment, but the underlying workflow remains the main learning focus.
01
DevOps fundamentals and delivery culture
Understand the goals, responsibilities, and feedback loops that connect development and operations.
- DevOps compared with isolated development and operations.
- Collaboration, shared ownership, and feedback.
- Continuous integration, delivery, and deployment.
- Automation and reduction of manual handoffs.
- Small changes, fast feedback, and safe recovery.
- Quality, security, and operations as shared concerns.
- Delivery flow, bottlenecks, and value-stream thinking.
Practice: Map a fictional software-delivery process and identify manual delays, quality risks, and opportunities for automation.
02
Git, collaboration, and release workflows
Use version control as a source of truth for application code, configuration, and delivery history.
- Repositories, commits, branches, and tags.
- Feature branches and pull-request workflows.
- Merge conflicts and code-review habits.
- Commit messages and traceable changes.
- Release tags and rollback references.
- Repository permissions and protected branches.
- Configuration files and secret exclusions.
Practice: Create a repository, use a feature branch, open a review, resolve a conflict, and tag a release.
03
Linux, scripting, and environment management
Build the command-line and system skills needed to inspect, configure, automate, and troubleshoot environments.
- Files, directories, permissions, and users.
- Processes, services, ports, and logs.
- Environment variables and configuration.
- Shell pipelines, redirection, and exit codes.
- Basic shell scripting and repeatable tasks.
- SSH and remote-administration concepts.
- Development, test, and production differences.
Practice: Write a script that checks service status, records logs, exits with useful status codes, and reports failures clearly.
04
Continuous integration and automated testing
Build a pipeline that checks changes automatically before they are accepted or released.
- Pipeline stages, jobs, steps, and runners.
- Build triggers and pull-request checks.
- Unit, integration, and smoke-test concepts.
- Linting, formatting, and static analysis.
- Build artifacts and dependency caching.
- Test reports and failure visibility.
- Pipeline permissions and secret handling.
Practice: Create a CI workflow that installs dependencies, runs tests, performs a quality check, and stores a build artifact.
05
Continuous delivery and deployment strategies
Explore how validated artifacts move through development, testing, staging, and production.
- Continuous delivery compared with deployment.
- Environment promotion and approval gates.
- Deployment packages and immutable artifacts.
- Rolling, blue-green, and canary strategies.
- Configuration and environment variables.
- Rollback planning and release verification.
- Post-deployment smoke tests.
Practice: Design a pipeline with development, staging, and production stages including a manual approval and rollback step.
06
Docker and containerized applications
Package applications consistently and understand how images, containers, networks, and volumes work.
- Images, containers, registries, and tags.
- Dockerfiles and image layers.
- Build context and dependency installation.
- Ports, networks, volumes, and environment variables.
- Multi-stage builds and smaller images.
- Container logs and health checks.
- Compose-based local development concepts.
Practice: Containerize a sample application, run it locally, configure environment values, and inspect its logs and health.
07
Kubernetes and cloud-native workloads
Understand how containerized applications are deployed, scaled, exposed, and managed in a cluster.
- Clusters, nodes, namespaces, and workloads.
- Pods, Deployments, ReplicaSets, and Services.
- Configuration, secrets, and environment values.
- Readiness and liveness probes.
- Scaling and rolling-update concepts.
- Ingress and external traffic concepts.
- Logs, events, resource limits, and troubleshooting.
Practice: Deploy a sample container to a local Kubernetes environment, expose it through a service, and inspect status, events, and logs.
08
Infrastructure as code and cloud integration
Define infrastructure and environment configuration in version-controlled, reviewable files.
- Infrastructure-as-code principles.
- Desired state and repeatable provisioning.
- Variables, modules, outputs, and state concepts.
- Plan, review, apply, and destroy workflows.
- Remote state and collaboration considerations.
- Cloud networking, compute, and managed services.
- Drift, access control, and infrastructure security.
Practice: Define a small development environment, review its planned changes, apply it in a lab, and remove it safely afterward.
09
Observability, security, and incident response
Operate services with visibility into health, performance, security, errors, and deployment impact.
- Metrics, logs, traces, and service health.
- Latency, traffic, errors, and saturation signals.
- Dashboards, alerts, and alert ownership.
- Secrets, dependencies, image scanning, and access control.
- Incident triage and operational runbooks.
- Rollback, recovery, and post-incident review.
- Security checks throughout the pipeline.
Practice: Create a monitoring and incident runbook for a service that experiences high error rates after a deployment.
10
GitOps, metrics, and capstone delivery
Bring the workflow together and measure both delivery speed and operational stability.
- Git as a source of truth for desired configuration.
- Pull-based deployment and reconciliation concepts.
- Infrastructure and application review.
- Deployment frequency and change lead time.
- Change failure rate and time to restore service.
- Continuous improvement and team feedback.
- Capstone presentation and documentation.
Practice: Complete the CI/CD pipeline, measure delivery outcomes, document a failed deployment, and demonstrate recovery.
Practical exercise ideas
These exercises prepare you for the complete DevOps pipeline project.
Release workflow
Use branches, pull requests, code review, tags, and release notes for a sample application.
Review focus: traceability, collaboration, and rollback references.
Service health script
Check processes, ports, logs, disk space, and service status with useful exit codes.
Review focus: automation, evidence, and operational troubleshooting.
Automated test pipeline
Build a workflow that installs dependencies, runs tests, checks quality, and saves an artifact.
Review focus: stages, failures, artifacts, and secure variables.
Containerized application
Build a container image, configure it, run it locally, and verify its health.
Review focus: image size, ports, logs, configuration, and reproducibility.
Cluster deployment
Deploy a container, expose it with a service, and inspect events, status, and logs.
Review focus: workload state, health checks, scaling, and troubleshooting.
Incident response drill
Investigate a failed release, decide whether to roll back, and record lessons learned.
Review focus: alerts, runbooks, recovery, and communication.
Suggested twelve-week learning plan
This is an illustrative sequence. Confirm the academy's official timetable, cloud access, lab tools, and delivery requirements before publishing it as a schedule.
| Week | Focus | Suggested milestone |
|---|---|---|
| 01 | DevOps foundations | Map a software-delivery workflow and bottlenecks. |
| 02 | Git and collaboration | Complete a reviewed branch and tagged release. |
| 03 | Linux and scripting | Automate service checks and collect operational evidence. |
| 04 | Continuous integration | Build a test and quality-check pipeline. |
| 05 | Continuous delivery | Design environment promotion and rollback stages. |
| 06 | Docker | Build and verify a containerized application. |
| 07 | Kubernetes | Deploy and troubleshoot a workload in a lab cluster. |
| 08 | Infrastructure as code | Define and review a repeatable development environment. |
| 09 | Cloud integration | Connect a delivery workflow to an approved cloud environment. |
| 10 | Monitoring and security | Create dashboards, alerts, and pipeline security checks. |
| 11 | Incident response and metrics | Run a failure drill and review delivery measurements. |
| 12 | Capstone presentation | Demonstrate the pipeline, deployment, monitoring, and recovery. |
Automate a reliable delivery workflow
Capstone project
Continuous Integration and Delivery Pipeline
Build a complete CI/CD pipeline for a sample web application or API. The project should show how source changes are tested, packaged, scanned, deployed, monitored, and recovered in a controlled environment.
Core project requirements
- Store application and pipeline files in Git.
- Use a branch and pull-request workflow.
- Run automated tests on every approved change.
- Perform formatting, linting, or static checks.
- Build a versioned application artifact or container image.
- Run a security or dependency check.
- Deploy to a development or staging environment.
- Run a post-deployment smoke test.
- Collect logs, metrics, and deployment status.
- Document rollback and recovery procedures.
Quality requirements
- Keep secrets outside source code and public repositories.
- Use environment-specific configuration safely.
- Make pipeline failures visible and actionable.
- Use reproducible build and deployment steps.
- Record artifact versions and deployment history.
- Test both successful and failed deployment paths.
- Document monitoring, alerts, and ownership.
- Explain known limitations and future improvements.
Optional extensions
Add Kubernetes deployment, Helm packaging, GitOps, infrastructure as code, canary delivery, automated rollback, a cloud deployment, supply-chain scanning, or a dashboard showing delivery and reliability metrics.
A pipeline should improve safety and feedback, not simply deploy faster. Include tests, access control, monitoring, approvals, rollback, and recovery in the design.
Suggested project structure
Keep application source, pipeline definitions, container configuration, deployment manifests, infrastructure files, and operational documentation organized.
devops-cicd-project/
├── app/
│ ├── src/
│ ├── tests/
│ └── README.md
├── .github/
│ └── workflows/
│ └── ci-cd.yml
├── docker/
│ ├── Dockerfile
│ └── compose.yml
├── k8s/
│ ├── deployment.yaml
│ └── service.yaml
├── infrastructure/
│ └── environment.example
├── operations/
│ ├── monitoring.md
│ ├── runbook.md
│ └── rollback.md
├── README.md
└── .gitignore
Do not commit production credentials, private keys, cloud secrets, personal data, or confidential deployment information to a public repository.
Delivery and reliability metrics
Measure outcomes rather than individual busyness. DORA-style metrics examine both delivery velocity and operational stability.
Deployment frequency
How often successful changes are deployed to an environment or production.
Lead time for changes
How long a change takes to move from commit to deployment.
Change failure rate
How often deployments result in incidents, rollbacks, or service degradation.
Time to restore service
How quickly the team recovers after a service failure or deployment problem.
Pipeline visibility
Whether teams can see test failures, deployment state, alerts, and ownership clearly.
Learning from incidents
Whether failures produce corrective actions and improvements rather than blame.
The commonly used four DORA measures include deployment frequency, lead time for changes, change failure rate, and time to restore service. [168][170]
Tools and technologies
The exact toolchain may vary. The following technologies represent a common learning toolkit for DevOps workflows.
- Git
- GitHub
- Linux
- Docker
- Kubernetes
- Jenkins concepts
- GitHub Actions concepts
- Terraform concepts
- Ansible concepts
- Cloud platforms
- Prometheus concepts
- Grafana concepts
Supporting concepts
- Shell scripting and command-line workflows.
- HTTP, DNS, ports, services, and network access.
- Containers, images, registries, and health checks.
- Configuration, secrets, environments, and permissions.
- Logs, metrics, traces, alerts, and runbooks.
- Security scanning and software supply-chain awareness.
Learning outcomes
By completing the proposed lessons and exercises, aim to demonstrate the following abilities:
- Explain DevOps principles and software-delivery flow.
- Use Git for collaborative development and releases.
- Automate Linux and application-management tasks.
- Build CI workflows with testing and quality checks.
- Package applications with Docker.
- Deploy and troubleshoot Kubernetes workloads.
- Understand infrastructure-as-code workflows.
- Connect pipelines to cloud environments.
- Design monitoring, alerting, and incident runbooks.
- Apply security checks throughout delivery.
- Measure delivery speed and stability.
- Document and present a CI/CD project.
These are learning objectives, not guarantees of employment, certification, placement, or a specific DevOps role. Progress depends on practical labs, troubleshooting, project quality, and continued learning.
Related career interests
Illustrative directions for continued learning, not job or placement guarantees.
- DevOps Engineer Trainee
- Cloud Operations Associate
- Release Engineer Trainee
- Site Reliability Trainee
- Platform Engineer Trainee
- Infrastructure Engineer
- Automation Engineer
- Associate Engineer
Portfolio presentation ideas
- Explain the application and delivery problem.
- Show the Git workflow and repository structure.
- Walk through the CI pipeline stages.
- Demonstrate a container build and scan.
- Show deployment to a controlled environment.
- Explain monitoring signals and alert responses.
- Demonstrate a failed release and recovery process.
- Discuss security, access, and secret management.
- Present delivery metrics and possible improvements.
Frequently asked questions
Who is this course for?
It is suitable for learners with basic computer knowledge who want to explore software delivery, automation, cloud operations, and infrastructure.
Do I need previous DevOps experience?
No. The course begins with DevOps principles, Git, Linux, and workflow fundamentals. Basic terminal and networking knowledge is helpful.
What tools are covered?
The proposed toolkit includes Git, GitHub, Linux, Docker, Kubernetes, CI/CD concepts, Terraform, Ansible, cloud platforms, monitoring, and alerting.
What is the capstone project?
The proposed capstone is a CI/CD Pipeline that tests, packages, scans, deploys, monitors, and verifies a sample application.
Does the course include Kubernetes?
Yes. The curriculum includes Kubernetes workloads, Deployments, Services, configuration, health checks, scaling, logs, events, and troubleshooting.
Does the course include cloud deployment?
It introduces cloud integration and deployment concepts. Confirm the specific cloud provider, account requirements, lab access, and pricing before publishing enrollment details.
What are DORA metrics?
DORA-style delivery measures examine deployment frequency, lead time for changes, change failure rate, and time to restore service. [168][170]
How long is the course?
The supplied course information proposes a duration of 12 weeks. Confirm the official timetable, lab access, tools, and delivery arrangements.
Can I use production systems for practice?
Do not change or test production systems without authorization, review, backups, and an approved change process. Use a local, classroom, staging, or explicitly authorized environment.
How do I enroll?
This page is a frontend course-information demonstration. Enrollment, payment, scheduling, and admission workflows are not implemented here.
Does this course guarantee a job?
No. The course can support practical learning and portfolio development, but it does not guarantee employment, placement, certification, or salary.
Deliver software with confidence
Build your DevOps delivery workflow
Learn how source control, automation, testing, containers, cloud, monitoring, security, and recovery connect into a reliable software-delivery process.