Description

This curriculum spans the design and implementation of DevOps practices across development, security, and operations functions, comparable in scope to a multi-workshop program that guides organizations through the technical and organizational alignment required to automate and govern software delivery at scale.

Module 1: Establishing DevOps Foundations and Organizational Alignment

Decide whether to adopt a centralized platform team or embed DevOps engineers within product squads based on team maturity and system complexity.
Define ownership boundaries between development, operations, and security teams to prevent gaps in incident response and deployment accountability.
Negotiate SLIs and error budget policies with business stakeholders to align deployment velocity with system reliability expectations.
Implement role-based access controls (RBAC) in shared tooling to balance autonomy with compliance and audit requirements.
Select metrics for DevOps performance (e.g., lead time, deployment frequency, change fail rate) that reflect actual business outcomes, not just tool usage.
Establish feedback loops between support teams and developers by routing production incidents directly to feature teams via integrated ticketing and monitoring systems.

Module 2: Source Control and Branching Strategy Design

Choose between trunk-based development and GitFlow based on release cadence, team size, and regulatory constraints for auditability.
Enforce pull request requirements including mandatory code reviews, automated test pass status, and static analysis checks before merge.
Implement branch protection rules to prevent direct commits to mainline and require signed commits for compliance-sensitive applications.
Design repository structure (mono-repo vs. multi-repo) considering code ownership, dependency management, and CI pipeline scalability.
Integrate automated dependency scanning into pull requests to detect vulnerable packages before code is merged.
Manage long-lived feature branches by requiring periodic rebases and automated integration tests to reduce merge conflicts and integration debt.

Module 3: Continuous Integration Pipeline Engineering

Structure CI pipelines with parallelizable stages for unit testing, linting, and artifact building to minimize feedback time.
Cache dependencies and build artifacts across pipeline runs to reduce execution time and external service load.
Isolate test environments using containerization to ensure consistency between local and CI execution.
Enforce test coverage thresholds as quality gates, failing builds when coverage drops below defined levels.
Configure pipeline triggers to avoid unnecessary runs on documentation or asset-only changes.
Rotate and manage CI/CD service account credentials using secret management tools to prevent hardcoded access keys.

Module 4: Artifact Management and Immutable Release Design

Select artifact repository type (e.g., container registry, binary store) based on deployment target and compliance retention policies.
Enforce immutability of released artifacts by disallowing overwrites and using cryptographic checksums for verification.
Tag artifacts with metadata including commit SHA, build number, and author for traceability in production incidents.
Implement retention policies to automatically purge stale artifacts and reduce storage costs and security exposure.
Scan artifacts for vulnerabilities and configuration drift before promoting to higher environments.
Integrate artifact signing into the pipeline to validate provenance and prevent unauthorized deployments.

Module 5: Deployment Automation and Release Orchestration

Choose deployment strategy (blue-green, canary, rolling) based on risk tolerance, rollback requirements, and monitoring capabilities.
Automate rollback procedures by coupling deployment tools with health checks and metrics thresholds.
Coordinate multi-environment promotions using pipeline approvals, manual gates, or automated policy checks.
Manage configuration separately from code using environment-specific config stores or service meshes.
Orchestrate database schema changes alongside application deployments using versioned migration scripts and pre-deployment validations.
Integrate deployment notifications into incident management tools to improve visibility during release windows.

Module 6: Observability and Runtime Feedback Integration

Instrument applications with structured logging, distributed tracing, and custom metrics before deployment to production.
Correlate deployment events with monitoring alerts to identify regression sources during incident triage.
Configure synthetic monitoring to validate critical user journeys post-deployment.
Set up log retention and indexing policies based on regulatory requirements and troubleshooting needs.
Enrich telemetry data with deployment metadata (e.g., release ID) to enable root cause analysis across systems.
Balance observability data volume with cost by sampling high-cardinality traces and logs in non-critical services.

Module 7: Security and Compliance Integration in DevOps Workflows

Shift security testing left by embedding SAST, DAST, and secret detection tools into CI pipelines.
Enforce policy-as-code using tools like OPA to validate infrastructure templates against security baselines.
Automate compliance checks for regulated workloads (e.g., HIPAA, PCI) using configuration auditing tools.
Manage infrastructure provisioning through IaC templates with peer review and drift detection enabled.
Implement just-in-time access for production environments using identity brokers and time-limited credentials.
Conduct regular red team exercises on CI/CD infrastructure to identify privilege escalation paths.

Module 8: Scaling DevOps Across Multiple Teams and Systems

Standardize CI/CD templates across teams while allowing controlled deviations for specialized workloads.
Centralize observability and logging infrastructure to enable cross-team correlation and reduce duplication.
Govern shared platform services (e.g., Kubernetes clusters) with service level objectives and capacity planning.
Resolve inter-team deployment conflicts by implementing release calendars and change advisory boards.
Measure and report on platform team SLAs for pipeline uptime, build duration, and support response times.
Manage technical debt in automation scripts by scheduling refactoring cycles and enforcing code quality standards.