About the Course
The modern engineering landscape requires a shift from manual hand-offs to automated, observable, and secure workflows. Organizations today demand results they can prove through measurable data, yet many teams struggle with technical debt, fragmented toolchains, and security bottlenecks. This course provides a structured system to transform these challenges into a competitive advantage by focusing on the core pillars of modern SDLC management: automation, security, and feedback loops. You will gain the ability to demonstrate mastery in GitOps, Infrastructure as Code (IaC), container orchestration, and automated testing. By the end of the program, you will have practiced building a full-stack delivery pipeline that integrates security scanning and performance monitoring as native components of the development process.
The modern software development lifecycle involves the integration of development, security, and operations into a single, continuous flow. Professionals use it to reduce lead time for changes and improve service reliability. This course is specifically designed for practitioners who must deliver under the pressure of rapid release cycles and complex regulatory environments. You will be introduced to advanced concepts like Site Reliability Engineering (SRE) and AI-augmented coding while spending the majority of your time applying these frameworks to real-world architectural challenges. This approach ensures that you do not just learn about the tools but understand how to orchestrate them into a cohesive strategy that aligns with global best practices and organizational goals.
Target Audience
This program is tailored for experienced technical professionals who are responsible for the design, execution, and optimization of software delivery processes within their organizations.
This course is designed for:
- Senior Software Engineers responsible for architectural SDLC decisions
- DevOps Engineers implementing CI/CD and GitOps automation
- Software Engineering Managers overseeing cross-functional delivery teams
- Release Managers coordinating complex cloud-native deployments
- Cloud Architects designing scalable SDLC infrastructure environments
- Quality Assurance Leads managing automated testing frameworks
- DevSecOps Specialists integrating security into the delivery pipeline
- Product Owners aligning technical roadmaps with SDLC velocity
- Systems Reliability Engineers focused on deployment stability metrics
- IT Governance Officers auditing software development compliance standards
Course Objectives
This course equips you to design, execute, and measure modern software initiatives that accelerate time-to-market, ensure regulatory compliance, and support strategic business growth.
By the end of this course, you'll be able to:
- Assess current delivery maturity using the DORA metrics framework
- Apply ISO/IEC/IEEE 12207:2017 standards to modern engineering workflows
- Construct a multi-stage CI/CD pipeline using GitOps principles
- Implement automated security scanning within the DevSecOps lifecycle
- Design containerized deployment strategies using Docker and Kubernetes
- Evaluate infrastructure requirements using Terraform and Ansible tools
- Set measurable performance targets using Site Reliability Engineering objectives
- Synthesize engineering data into executive-level delivery health reports
Requirements & Prerequisites
Participants should have at least 3 years of experience in software development, systems administration, or technical project management. Familiarity with Git version control and basic Linux command-line operations is required. No advanced coding skills are necessary, but a working knowledge of at least one programming language (e.g., Python, Java, JavaScript) will enhance the learning experience.
Local Application and Business Return
How participants can apply the training in local operating conditions, and the return their organisation can plan for.
How participants apply this
Expected ROI
Training Methodology
This is a practical, outcome-driven course designed to turn SDLC aspirations into measurable action and credible reporting through hands-on technical application.
Methodology includes:
- Hands-on CI/CD pipeline construction using a live Jenkins environment
- Scenario simulation requiring recovery from a failed production deployment
- SDLC maturity assessment using a customized DORA metrics checklist
- Stakeholder mapping exercise for aligning engineering and business goals
- Case study analysis of SDLC failures in Fintech and Healthcare
- Group workshop designing a secure GitOps workflow for Kubernetes
- Reflection exercise benchmarking current team velocity against industry standards
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Modern Software Development Lifecycle Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Effective Learning & Skill Development
- Build expertise with structured, outcome-driven learning.
- Equip individuals and teams with skills that grow with industry needs.
- Reinforce learning through real-world scenarios, case studies and practical exercises.
Career Growth & Professional Advancement
- Apply what you learn with a proven methodology that ensures lasting impact.
- Develop immediately usable skills that translate directly into workplace success.
- Gain the expertise needed for career advancement and leadership roles.
Training Optimization & Learning Excellence
- Tailor training to industry-specific challenges and organizational goals.
- Use data-driven insights and automation to enhance training effectiveness.
- Evaluate progress and ensure long-term learning success.
Tools and platforms relevant to this field
Examples local teams may encounter, and that may be featured in training where they support the confirmed course scope.
These are field-relevant examples, not a promise that every tool will be covered. Exact coverage depends on the confirmed course scope, participant needs, and delivery format.
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GitHub Copilot GitHubUsed by development teams to speed up code drafting, refactoring, and test creation inside modern IDE workflows.
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Jenkins Jenkins projectUsed to automate build, test, and deployment pipelines for continuous integration and continuous delivery.
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GitLab GitLab Inc.Used to manage source control, merge requests, CI/CD pipelines, and release workflows in one platform.
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Azure DevOps MicrosoftUsed to plan work, run pipelines, and coordinate releases across engineering and operations teams.
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AWS CodePipeline Amazon Web ServicesUsed to orchestrate automated software delivery stages in cloud-native environments.
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SonarQube SonarSourceUsed to enforce code quality gates and detect maintainability and security issues early in the lifecycle.























