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Agile Methodology in DevOps

Agile Methodology in DevOps

$248.00
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Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
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What does the Agile Methodology in DevOps course cover?

Agile Methodology in DevOps is covered here in 8 modules: Integrating Agile Frameworks with DevOps Pipelines, Continuous Integration and Agile Development Rhythms, Continuous Delivery and Release Management Alignment and 5 more. The outline lists 48 specific topics, opening with selecting between Scrum, Kanban, or SAFe based on team size, release frequency, and organizational maturity when aligning with CI/CD workflows.

How do you approach Agile Methodology in DevOps step by step?

The work is sequenced in 8 stages. It starts with Integrating Agile Frameworks with DevOps Pipelines, moves through Continuous Integration and Agile Development Rhythms and Continuous Delivery and Release Management Alignment, and ends at Measuring and Optimizing Agile DevOps Performance. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the Agile Methodology in DevOps course?

Module 1 is Integrating Agile Frameworks with DevOps Pipelines. It works through selecting between Scrum, Kanban, or SAFe based on team size, release frequency, and organizational maturity when aligning with CI/CD workflows., mapping sprint planning cycles to deployment windows to avoid conflicts during production releases., configuring backlog prioritization to reflect technical debt reduction alongside feature development, ensuring pipeline stability. and 3 more.

How is the Agile Methodology in DevOps course delivered?

The Agile Methodology in DevOps course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Agile Methodology in DevOps course cost?

The Agile Methodology in DevOps course is $250 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Agile Methodologies in DevOps, DevOps and Agile Methodologies Kit, Agile Methodology and Agile Methodologies Kit, Agile DevOps Toolkit.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the equivalent of a multi-workshop program, addressing the integration of Agile practices with DevOps workflows across planning, development, deployment, and operations, as seen in enterprise-scale advisory engagements.

Module 1: Integrating Agile Frameworks with DevOps Pipelines

  • Selecting between Scrum, Kanban, or SAFe based on team size, release frequency, and organizational maturity when aligning with CI/CD workflows.
  • Mapping sprint planning cycles to deployment windows to avoid conflicts during production releases.
  • Configuring backlog prioritization to reflect technical debt reduction alongside feature development, ensuring pipeline stability.
  • Defining Definition of Done (DoD) criteria to include automated testing, security scanning, and infrastructure-as-code validation.
  • Aligning Agile team roles (e.g., Product Owner, Scrum Master) with DevOps responsibilities such as on-call rotations and incident response.
  • Implementing sprint retrospectives that include metrics from deployment frequency, lead time, and change failure rate.

Module 2: Continuous Integration and Agile Development Rhythms

  • Establishing branch strategies (e.g., trunk-based development vs. feature branching) that support daily Agile commits without breaking the build.
  • Enforcing pre-merge quality gates such as static code analysis, unit test coverage thresholds, and dependency checks in pull requests.
  • Scheduling automated builds to trigger on every commit while balancing pipeline speed with test comprehensiveness.
  • Coordinating CI pipeline execution with Agile stand-ups by surfacing build health in team dashboards.
  • Managing flaky tests in CI by isolating, quarantining, or disabling them while assigning ownership for resolution within the sprint.
  • Integrating CI feedback into Agile task tracking tools to reflect build status directly on user stories and defects.

Module 3: Continuous Delivery and Release Management Alignment

  • Designing deployment pipelines with stage gates that align with sprint review and approval workflows.
  • Implementing feature toggles to decouple deployment from release, allowing Agile teams to merge completed work without immediate exposure.
  • Coordinating release train schedules with Agile release planning, especially in multi-team environments using PI planning.
  • Managing rollback procedures and versioned artifacts to support Agile teams during failed production deployments.
  • Defining release criteria that include non-functional requirements like performance, security, and compliance checks.
  • Using dark launching and canary releases to validate features incrementally without disrupting Agile delivery commitments.

Module 4: Infrastructure as Code and Agile Environment Provisioning

  • Versioning infrastructure code in the same repository as application code to maintain traceability with Agile user stories.
  • Automating environment creation for QA, staging, and UAT to support sprint-based testing cycles.
  • Enforcing IaC peer reviews as part of the Agile pull request process to prevent configuration drift.
  • Managing stateful services (e.g., databases) in IaC while supporting Agile teams' need for rapid iteration and data seeding.
  • Scaling cloud resources dynamically to match Agile testing load without exceeding budget guardrails.
  • Integrating drift detection tools to alert teams when manual changes conflict with IaC definitions.

Module 5: Monitoring, Feedback Loops, and Agile Iteration

  • Instrumenting production systems to capture metrics that inform backlog refinement, such as error rates and user drop-off points.
  • Routing production alerts to the Agile team responsible for the related user story or feature.
  • Configuring observability dashboards to align with sprint goals and feature KPIs.
  • Using customer feedback from monitoring tools (e.g., session replay, logs) to generate new backlog items during backlog grooming.
  • Establishing feedback latency targets so that operational data influences the next sprint planning cycle.
  • Integrating post-deployment health checks into the Definition of Done for user stories involving backend services.

Module 6: Security and Compliance in Agile DevOps Workflows

  • Embedding security scanning tools (SAST, DAST, SCA) into CI pipelines without introducing unacceptable delays to Agile delivery.
  • Assigning vulnerability remediation tasks to specific sprints based on risk severity and exploitability.
  • Coordinating compliance audits with sprint reviews to demonstrate control adherence incrementally.
  • Managing secrets and credentials in CI/CD environments while maintaining developer access needs per Agile team structure.
  • Implementing policy-as-code checks that block deployments violating regulatory requirements (e.g., GDPR, HIPAA).
  • Training Agile teams on secure coding practices during sprint planning and refinement sessions.

Module 7: Scaling Agile DevOps Across Teams and Domains

  • Designing cross-team API contracts and versioning strategies that support independent Agile delivery without integration bottlenecks.
  • Establishing shared DevOps platforms (e.g., internal developer portals) while preserving team autonomy in Agile execution.
  • Resolving dependency conflicts between Agile teams through synchronized planning events and integration milestones.
  • Implementing centralized logging and monitoring that aggregates data across Agile teams for enterprise visibility.
  • Balancing standardization of tooling with flexibility for team-specific Agile practices in large-scale transformations.
  • Managing technical portfolio alignment by mapping Agile epics to enterprise architecture roadmaps and infrastructure upgrades.

Module 8: Measuring and Optimizing Agile DevOps Performance

  • Selecting DORA metrics (deployment frequency, lead time, change failure rate, time to restore) as KPIs for Agile team health.
  • Correlating sprint velocity with operational outcomes like incident volume and rollback frequency.
  • Using value stream mapping to identify bottlenecks between Agile planning and deployment execution.
  • Setting baseline performance targets for pipelines and adjusting Agile goals based on historical throughput.
  • Conducting blameless post-mortems that link production incidents to specific Agile decisions or backlog items.
  • Iterating on toolchain configuration based on team feedback collected during sprint retrospectives.
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