\u00a0<\/span><\/h3>\nT<\/span>he annual release frequency in Waterfall<\/span>\u00a0<\/span>is<\/span>\u00a0reduced to quarterly\/monthly releases with Agile. With DevOps, the release frequency has shortened to weeks, days, and hours. The segregated, siloed Dev, Ops, and Test\u00a0<\/span>teams\u00a0<\/span>work collaboratively, together, simultaneously under\u00a0<\/span>the\u00a0<\/span>DevOps framework. From long, phase-wise testing at the end of a long development cycle, we have moved on to in-sprint testing strategies and unattended automation aligned with build frequency in the CI\/CD pipeline. DevOps methodology allow<\/span>s<\/span>\u00a0organizations to focus on in-sprint end-to-end testing, non-functional engineering, continuous integration & testing, test data engineering, build readiness for operation and release, UX engineering & assurance, & automated test enabling functions such as test data & environment engineering.<\/span>\u00a0<\/span><\/p>\nThe transition, rather<\/span>,<\/span>\u00a0evolution from Waterfall to Agile & DevOps is not only technical \u2013\u00a0<\/span>it is behavioral.<\/span><\/i>\u00a0<\/span>It is about instilling end-to-end visibility across the SDLC. It is about\u00a0<\/span>exposing<\/span>\u00a0a failure and\u00a0<\/span>making it transparent<\/span>\u00a0to learn from it and avoid it in the future.<\/span>\u00a0It is about\u00a0<\/span>emphasizing<\/span>\u00a0Q<\/span>uality Assurance to\u00a0<\/span>lower risks, allow incremental changes, and conquer change resistance.<\/span>\u00a0<\/span><\/p>\nTransitioning from Quality Assurance to Quality Engineering<\/span><\/b>\u00a0<\/span><\/h3>\nCloud computing & serverless architectures are in vogue. Organizations are formulating container-first strategies. They are adopting DevSecOps and dual-shift quality automation approach for making quality inherent in the SDLC. This shift from traditional to built-in quality approach is mainly because of the rising cost\u00a0<\/span>of defects in production. Extreme automation with integrated quality engineering techniques\u00a0<\/span>is becoming<\/span>\u00a0a cornerstone\u00a0<\/span>of<\/span>\u00a0daily deployments. A paradigm shift<\/span>\u00a0is being observed<\/span>\u00a0towards BDD with TDD delivery practices<\/span>\u00a0while\u00a0<\/span>the role of quality<\/span>\u00a0is getting extended<\/span>\u00a0to Ops and post-production.\u00a0<\/span>\u00a0<\/span><\/p>\nNavigating your DevOps<\/span><\/b>\u00a0implementation<\/span><\/b>\u00a0journey<\/span><\/b>\u00a0<\/span><\/h3>\nFor a successful implementation<\/span>, organization<\/span>s<\/span>\u00a0need to take an all-rounded<\/span>\u00a0DevOps<\/span>\u00a0approach that includes automation, data engineering, non-functional engineering, continuous monitoring, governance, and infrastructure automation.\u00a0<\/span>\u00a0<\/span><\/p>\n\u00a0 \u00a0 1. Automation:<\/span><\/b>\u00a0<\/span><\/p>\n\n- Unit, services, and UI automation<\/span>\u00a0<\/span><\/li>\n
- CI\/CD pipeline integration<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
\u00a0 \u00a0 2.Data\u00a0<\/span><\/b>engineering<\/span><\/b>:<\/span><\/b>\u00a0<\/span><\/p>\n\n- Centralized test data management<\/span>\u00a0<\/span><\/li>\n
- Data creation from production<\/span>\u00a0<\/span><\/li>\n
- Synthetic data creation<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
\u00a0 \u00a0 3. Continuous monitoring:<\/span><\/b>\u00a0<\/span><\/p>\n\n- Infra & App monitoring<\/span>\u00a0<\/span><\/li>\n
- Threshold enablement<\/span>\u00a0<\/span><\/li>\n
- Root cause analysis<\/span>\u00a0<\/span><\/li>\n
- Auto alert configuration<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
\u00a0 \u00a0 4. Non-functional engineering:<\/span><\/b>\u00a0<\/span><\/p>\n\n- Performance engineering<\/span>\u00a0<\/span><\/li>\n
- Proactive performance management<\/span>\u00a0<\/span><\/li>\n
- DevSecOps \u2013 security assurance program<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
\u00a0 \u00a0 5. Governance:<\/span><\/b>\u00a0<\/span><\/p>\n\n- Metrics and KPI monitoring \u2013 Dev, Test, and Ops<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
\u00a0 \u00a06. Infrastructure automation:<\/span><\/b>\u00a0<\/span><\/p>\n\n- Automated test environments management \u2013 provisioning, troubleshoot, and self-healing<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
Steps involved in the DevOps implementation process<\/span><\/b>\u00a0<\/span><\/h3>\nFor DevOps to be successful,\u00a0<\/span>the Dev, Ops, and Test teams must<\/span>\u00a0work in complete tandem with one another. The key steps involved in the DevOps implementation are:<\/span>\u00a0<\/span><\/p>\n\n- Assessment:\u00a0<\/strong>
\nBefore starting the implementation process, organizations need to take a step back, analyze, assess, and understand their culture, governance policies, and team dynamics. This assessment will help them chart an effective change management plan.<\/span>\u00a0<\/span><\/li>\n- Align with Agile methodology<\/span><\/b>:<\/span><\/b>
\nDevOps being an extension of Agile<\/span>\u00a0<\/span>mandates alignment of the software development practices with the Agile methodology. Quality Engineering techniques such as container-first strategies, dual-shift quality automation, DevSecOps, pipeline automation, and\u00a0<\/span>service-less architecture should be implemented. It is essential that in-sprint testing is facilitated, and\u00a0<\/span>the\u00a0<\/span>acceptance criteria\u00a0<\/span>are<\/span>\u00a0defined.<\/span><\/li>\n- Tools orchestration<\/span><\/b>:<\/span><\/b>\u00a0\u00a0<\/span>