Ultimate ALM Course for Project Managers and Scrum Masters

Recognize the vital role of application life cycle management in software development and management, driving success and sustainability of software applications.

Safeguard software integrity by ensuring reliability and functionality and preventing defects and breakdowns. Learn how testing and code review identify and fix mistakes before release to keep software running smoothly.

Apply ALM as a guiding framework to consistently deliver high quality, reliable software by adopting best practices, optimizing performance, resolving bugs, and introducing new features to enhance user satisfaction.

Cost efficiency in software means smart planning, testing, and updates that optimize resource allocation, reduce development and maintenance costs, and improve the product across its life cycle.

Understand how user satisfaction drives software success by meeting user expectations and delivering a positive experience. See how games and apps delight users with fun and a reliable experience.

Identify, address, and resolve problems quickly using tools and methodologies that form a superhero team to fix what's wrong and keep the game running smoothly.

Alm guards software applications by ensuring longevity, reliability, and adaptability, providing a structured approach to development, maintenance, and enhancement that helps organizations maximize value.

Explore the key components of ALM and application lifecycle management to improve software quality, enhance cross-functional collaboration, and enable cost-effective development from inception to retirement.

Master requirement management in application lifecycle management by gathering and defining requirements and establishing traceability to track how each requirement connects to software components and affected areas during changes.

Explore the development process in application lifecycle management, from writing code to version control, ensuring requirements translate into a functional software product through structured steps.

Learn the testing process in application lifecycle management, focusing on quality assurance and automated testing to ensure software meets defined requirements and is free from defects.

Describe the deployment phase in application lifecycle management, moving software from development and testing into production. Use staging and other environments to validate readiness and enable a smooth end-user release.

Monitor the production application's performance, availability, and health to maintain reliability. Use monitoring tools to track response time, throughput, resource usage, and logs, with alerts for proactive issue resolution.

Learn how maintenance and support drive life cycle management after deployment, planning fixes and feature updates to keep the deployed application secure and up to date.

See software development as a planned journey from design to care. Let the Eillam roadmap guide design, build, test, and care through the life cycle.

Explore the Elm aspects diagram from the birth of a business need through portfolio rationalization, SDLC, development, testing, deployment, handover to operations, production value, retirement, and recurring change requests.

Roles collaborate across projects to deliver business value through team-based software development. This course emphasizes cross-role collaboration to optimize the ALM process and maximize system value.

Identify and engage stakeholders, including those who pay for the project and end users, to align needs and concerns with project goals through effective communication and management.

Analyze business needs and initiate development projects delivering value, with the business manager guiding approvals, portfolio rationalization, and coordinating IT staff involvement for deployment into the infrastructure.

Assign suitable individuals to the project manager, product owner, or scrum master roles based on the project budget, and have them lead after the go ahead decision to ensure continuity.

PMO decision makers drive project choices, prioritize projects, allocate resources, manage risk, and ensure governance standards, performance monitoring, and accountability align with organizational objectives.

Lead requirements collection and portfolio rationalisation to analyze stakeholders' business needs and present viable solutions within the systems development life cycle, serving as a bridge between business and service providers.

Sketch the initial concept of the solution and create a blueprint that guides system design. Evaluate scalability, hardware requirements, and user interfaces to ensure the architecture is effective and adaptable.

UX design is a fundamental deliverable requiring close collaboration between the team and development, ideally with a dedicated UX expert embedded, since strong business logic cannot compensate for poor UX.

DBAs optimize database performance and ensure high uptime, while developers increasingly handle database work and should broaden their skills to include database management.

Developers design, create, and maintain software solutions, writing, testing, and debugging code to tailor software to business needs and end users across front-end, back-end, full-stack, mobile, and web roles.

learn how testers integrate testing across the entire development life cycle, from requirement documentation to build and version-controlled commits, through tdd (test driven development) and proactive quality assurance.

Explore the essentials of application lifecycle management and the pivotal roles that drive successful software development, and learn how rules intervene in the process.

Explore four distinct application lifecycle management perspectives—sdlc, service operations, APM, and a unified approach—and learn how CIOs can harmonize them to optimize ALM.

Explore the software development life cycle from business need to operations. See how ALM harmonizes activities, artifacts, and progress reporting across design, development, and testing.

Adopt a service management view that covers deployment, operations, support, and optimization to meet defined service levels in production, with development and operations teams collaborating from the start.

Treats an application as a product within a broader portfolio, aligning with PMI principles and illustrating the life cycle from concept to operation within project portfolio management.

Unify earlier views with business objectives by adopting a chief information officer–level focus on the full life cycle of an application to enhance project agility from inception to completion.

Explore four viewpoints of application lifecycle management to understand the complexities of the entire life cycle and apply informed decisions and strategies across development operations, portfolio management, and strategy.

Traceability serves as a pillar of application lifecycle management, providing visibility from requirements inception to delivered code, supporting FDA regulated applications, compliant change management, and cost control.

Automate core processes in application lifecycle management, including approval workflows across analysis, design, build, deployment, and testing, to streamline the software life cycle, reduce errors, and accelerate delivery.

Enhance transparency into development progress with real-time dashboards and metrics for bugs, test results, and status. Heirloom tools help teams track milestones, identify bottlenecks, and stay on track for quality.

Compare manual tracking with tool-enabled requirements in ALM, highlighting the interconnected pillars of traceability, visibility, and process automation to reduce effort and improve software quality.

Explore metrics in application lifecycle management to drive efficiency, monitor progress, and support decisions across project management, architecture, analysis and design, developer practices, testing, and release management.

Explore agile project-management metrics to gauge project effectiveness, including backlog, sprint burndown, velocity report, release burndown, and cumulative flow diagrams.

Explore the backlog overview report, a prioritized, dynamic list of features, user stories, tasks, bugs, and improvements that serves as the central source of truth for agile sprint planning.

Track sprint progress with a burndown chart, comparing actual and ideal lines in Jira, updated daily to reveal delays and guide improvements.

Discover how the velocity report tracks estimated, committed, and completed work across sprints to forecast backlog delivery, guide sprint planning, and drive data-driven improvement.

Track release progress with the release burndown in JIRA to see backlog moving toward a version. Use estimation data to forecast sprints and adjust scope with stakeholders for tracking.

Explore how a cumulative flow diagram in Jira visualizes work items across to do, in progress, and done to identify bottlenecks and optimize lead time, cycle time, flow efficiency.

Identify release management key performance indicators, including production defects, upgrade success rate, untested releases, urgent releases, and average cost, and learn how measurement, analysis, and action drive high-quality releases.

Leverage metrics and key performance indicators to assess progress and maintain quality standards in application life cycle management, choosing metrics that best fit your organization’s goals.

Explore metrics borrowed from the development domain to evaluate architecture and design key performance indicators, including lines of code, class coupling, depth of inheritance, cyclomatic complexity, and maintainability index.

Explore lines of code (LOC) as a size metric for software, useful for rough estimates, but it doesn't reflect quality; use VSCode counter for quick tracking alongside other metrics.

Examine class coupling as interdependence between modules and how low coupling with high cohesion enhances modularity. Learn abstraction, encapsulation, dependency injection, and design patterns to reduce coupling.

Explore depth of inheritance as a metric of hierarchy complexity, using a CEO to employees analogy, and learn how code reviews and documentation guide refactoring toward maintainable hierarchies.

Explore cyclomatic complexity as a software metric that counts independent paths to identify trouble spots and refactor high-complexity functions, improving readability and test coverage within a ten or lower threshold.

Discover how the maintainability index measures how easily software can be maintained, highlighting readable, well-documented, modular code, unit tests, code reviews, and version control.

Explore essential metrics for developer practices, focusing on code coverage, compiler warnings, and code analysis warnings, to guide your team toward higher quality, reliable software within the scrum framework.

Define code coverage targets, measure lines, branches, and statements executed by automated tests, and use continuous integration reports to improve software quality.

Address compiler warnings to improve code correctness and maintainability. Use linters, refactor unclear code, treat warnings as errors, run unit tests, track changes in version control, and conduct code reviews.

Identify code analysis warnings from static analyzers, targeting security, performance, and maintainability. Learn to configure tools like Sonarqube and integrate warnings into CI and testing.

Explore metrics for software testing, including bugs per state, reactivated bugs, test run results, and percent requirements covered, to drive ongoing, KPI-based quality in development.

Track bugs by state—active, resolved, and closed—to monitor backlog, definitions, and defect triage practices; implement real-time dashboards and conduct root cause analysis for closed bugs to improve quality.

Monitor reactivated bugs to reveal incomplete fixes, conduct root cause analysis, perform regression testing, document resolutions, and use automated testing frameworks to improve software quality and user experience.

Explore how test run results reveal pass rate, fail rate, incomplete or blocked cases, and execution time to assess software quality and inform test automation and regression testing.

Assess the percent of requirements covered by test cases using a traceability matrix and stakeholder reviews to reach 100% coverage.

Measure the percentage of requirements covered by testing and pursue 100% coverage. Collaborate with stakeholders to validate requirements, update test cases as they change, and communicate risk from unverified requirements.