QA Automation Engineers and SDETs constantly face requests to automate various tests. Deciding which tests to automate is a core daily task, and being able to prioritize the right tests helps to deliver quick results to other teams and demonstrates sound decision making. 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮 𝗳𝗼𝗿 𝗖𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝗧𝗲𝘀𝘁𝘀 𝘁𝗼 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 🔁 𝗥𝗲𝗽𝗲𝗮𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 Tests that run frequently, like regression and sanity tests, are ideal automation candidates. Daily smoke tests that check basic functionality should be automated to provide quick feedback on application stability. 🔥 𝗛𝗶𝗴𝗵 𝗥𝗶𝘀𝗸 𝗔𝗿𝗲𝗮𝘀 Critical functionalities like authentication, security, data integrity, and financial transactions should be automated. These features must work flawlessly under all circumstances. 🔒 𝗦𝘁𝗮𝗯𝗹𝗲 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 Features that rarely change require minimal test maintenance, making them valuable long term automation investments. Main user scenarios that have remained stable across several releases are perfect candidates. ⏰ 𝗧𝗶𝗺𝗲 𝗖𝗼𝗻𝘀𝘂𝗺𝗶𝗻𝗴 𝗧𝗮𝘀𝗸𝘀 Multi step tests or large test suites with hundreds of cases consume significant manual effort. Scenarios requiring repeated user interactions (like multiple login/logout cycles) are tedious and error prone when done manually but execute in seconds when automated. 🍒 𝗟𝗼𝘄 𝗛𝗮𝗻𝗴𝗶𝗻𝗴 𝗙𝗿𝘂𝗶𝘁 Tests that can be automated easily and quickly offer immediate returns. Basic login/logout functionality can be automated fast and shows immediate value by reducing manual testing time. 📊 𝗗𝗮𝘁𝗮 𝗗𝗿𝗶𝘃𝗲𝗻 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 Tests involving multiple datasets or input combinations benefit significantly from automation. Form validation with various input combinations ensures all edge cases are handled efficiently. 𝗧𝗵𝗲 𝗖𝗼𝘀𝘁 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Balance the effort required to automate against the time it will save. Prioritize automation where long term benefits justify the initial investment. Automating complex but frequently executed tests saves significant time. However, a manual test that takes 10 minutes and runs once a month isn't worth 40 hours of automation effort.

Part of every Engineering Team's job is to communicate their progress and impact to upper management using clear, meaningful metrics. This applies to all engineering department, including QA Automation and SDETs. Tracking the right metrics helps teams identify bottlenecks, make informed decisions and show concrete results. 𝗪𝗵𝘆 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗠𝗮𝘁𝘁𝗲𝗿 𝗳𝗼𝗿 𝗤𝗔 𝗧𝗲𝗮𝗺𝘀 Stakeholders need the answers to questions like: - How much of the application is covered by tests? - How fast can releases be validated? - Are bugs being caught before production? - Is automation saving time? 𝗧𝗵𝗲 𝟱 𝗘𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗤𝗔 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 📊 𝟭. 𝗧𝗲𝘀𝘁 𝗖𝗼𝘃𝗲𝗿𝗮𝗴𝗲 The percentage of user scenarios and critical features covered by test cases. High coverage demonstrates confidence that releases won't break for customers. ➤ Target 80%+ coverage of critical user flows, with clear documentation of what's tested and what's intentionally excluded. 🤖 𝟮. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘃𝗲𝗿𝗮𝗴𝗲 The ratio of manual test cases converted to automated tests. This shows testing efficiency improvements and ROI. Every automated test saves time on every future release. ➤ Target at least 60% to 70% for regression tests, focusing on repetitive and stable scenarios. ⚡ 𝟯. 𝗧𝗲𝘀𝘁 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗧𝗶𝗺𝗲 How long it takes to run your automated test suite. Faster tests mean faster feedback to developers. A 6 hour test suite delays every code change by 6 hours. A 15 minute suite enables rapid iteration. ➤ Keep full regression under ~30 minutes and smoke tests under ~10 minutes. Use parallel runs if needed. ⏱️ 𝟰. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗘𝗳𝗳𝗼𝗿𝘁 𝗧𝗶𝗺𝗲 Time spent on different testing activities like test creation, execution, bug verification, and regression testing. This reveals bottlenecks and helps justify automation investments. If 80% of effort goes to manual regression instead of exploratory testing, that's a clear process problem. ✅ 𝟱. 𝗣𝗮𝘀𝘀 𝗥𝗮𝘁𝗲 𝗮𝗻𝗱 𝗕𝘂𝗴 𝗧𝗿𝗲𝗻𝗱𝘀 The percentage of passing tests and the number of new bugs per deployment. Pass rate shows application stability. Bug trends reveal whether development practices are improving or degrading.

If you're an SDET or QA Automation Engineer still manually running tests or waiting for DevOps teams to set up your testing environments, you're opportunities on the table. DevOps skills have shifted from "nice to have" to essential for modern QA. So... 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗗𝗲𝘃𝗢𝗽𝘀? DevOps is a methodology that combines software development and IT operations to build and deliver software faster and more reliably. DevOps Engineers manage the infrastructure, tools, and automation that make continuous delivery possible. Their responsibilities include: • Managing servers and cloud infrastructure • Building CI/CD pipelines for automated deployments • Implementing monitoring and logging solutions • Ensuring system stability and reliability • Enabling seamless collaboration between development and operations teams 𝗧𝗵𝗲 𝗢𝘃𝗲𝗿𝗹𝗮𝗽: 𝗪𝗵𝘆 𝗤𝗔 𝗮𝗻𝗱 𝗗𝗲𝘃𝗢𝗽𝘀 𝗚𝗼 𝗛𝗮𝗻𝗱 𝗶𝗻 𝗛𝗮𝗻𝗱 Test Automation and DevOps are part of the same infrastructure. Both roles require knowledge of: ✅ CI/CD Pipelines (Jenkins, GitLab CI, GitHub Actions) ✅ Containerization (Docker, Kubernetes) ✅ Cloud Platforms (AWS, Azure, GCP) ✅ Linux/Command Line Operations ✅ Version Control (Git) ✅ Databases (SQL, NoSQL) The difference is DevOps Engineers focus on production deployments. Test Automation Engineers focus on quality gates. But the technical foundation is nearly identical. 𝗧𝗵𝗲 𝗖𝗮𝗿𝗲𝗲𝗿 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 Learning DevOps isn't just about technical growth. It's about career advancement and compensation. 💰 Higher Salaries: ▶ DevOps skills are among the highest paid in tech. SDETs and QA Automation Engineers with DevOps expertise often get paid significantly higher salaries than those without. 🚀 More Job Opportunities: ▶ Job descriptions increasingly require "SDET with DevOps experience" or "QA Engineer with CI/CD knowledge." Companies want engineers who can own the entire testing pipeline. 🏆 Greater Independence: ▶ Stop waiting for DevOps teams to configure environments or fix pipeline issues. Manage your own infrastructure and move faster.