Mobile testing isn't just "web testing on a smaller screen" , it's a completely different beast. Here's what you're really up against. ──────────────────────────────────────── 𝐖𝐡𝐲 𝐌𝐨𝐛𝐢𝐥𝐞 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐈𝐬 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 - 100+ device combinations in the wild - OS fragmentation across Android versions - Performance that varies wildly between devices - Network conditions constantly changing ──────────────────────────────────────── 🔴 𝐓𝐨𝐩 𝟓 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐄𝐯𝐞𝐫𝐲 𝐌𝐨𝐛𝐢𝐥𝐞 𝐓𝐞𝐬𝐭𝐞𝐫 𝐅𝐚𝐜𝐞𝐬 1. Device Fragmentation - The problem: Can't test on every device - The solution: Focus on top devices only. Ask the PMs or the Analytics team about the most common devices used for your app 2. Network Conditions - The problem: WiFi vs 4G vs 3G behavior differs dramatically - The solution: Simulate network throttling in your tests. Use tools such Chrome DevTools, Charles Proxy or Fiddler 3. Touch Gestures - The problem: Swipe, pinch, long-press all behave differently - The solution: Use mobile-specific testing frameworks 4. App State Interruptions - The problem: Calls, notifications, background tasks that kill your app session - The solution: Test interruption scenarios explicitly. Focus on Phone Calls, Low Battery and Notifications 5. Performance on Low-End Devices - The problem: Works on iPhone, crashes on budget Android - The solution: Test on minimum spec devices from the top 5 most popular for your app ──────────────────────────────────────── 💡 𝐓𝐢𝐩: Don't aim for 100% device coverage. Aim for 80% user coverage with smart device selection. Focus your testing budget on devices your actual users have, not every device that exists. ──────────────────────────────────────── 📌 𝗥𝗲𝗮𝗱𝘆 𝘁𝗼 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲 𝗮𝗻𝗱 𝗯𝗲𝗰𝗼𝗺𝗲 𝗮 𝗷𝗼𝗯-𝗿𝗲𝗮𝗱𝘆 𝗦𝗗𝗘𝗧 𝗶𝗻 𝟯–𝟰 𝗺𝗼𝗻𝘁𝗵𝘀? Unlike software engineering or data science, QA Automation has no traditional university degree path. Most people stumble through trial and error for 12-18 months, piecing together knowledge from scattered YouTube tutorials and outdated blog posts.

Looking to break into QA Automation/SDET career in 2026? The market is more competitive than ever, and generic advice won't cut it anymore. This guide breaks down exactly what you need to learn, why it matters, and how to build these skills faster than self-teaching alone. ▶ 𝟭. 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗦𝗸𝗶𝗹𝗹𝘀: 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻, 𝗦𝗰𝗮𝗹𝗲 𝘄𝗶𝘁𝗵 𝗬𝗼𝘂𝗿 𝗝𝗼𝗯 Python is the easiest programming language to learn for QA automation, and it's used by 70% of automation frameworks including Selenium, Playwright, and Pytest. You can write your first working test script in days, not months. Start with Python fundamentals: variables, loops, functions, and OOP basics. Once you're comfortable, learn whatever language your actual job requires. Most companies care more about problem-solving skills than which specific language you know. ▶ 𝟮. 𝗗𝗲𝘃𝗢𝗽𝘀 𝗟𝗶𝗴𝗵𝘁: 𝗖𝗜/𝗖𝗗, 𝗚𝗶𝘁𝗛𝘂𝗯, 𝗮𝗻𝗱 𝗗𝗼𝗰𝗸𝗲𝗿 𝗕𝗮𝘀𝗶𝗰𝘀 You don't need to become a DevOps engineer. But modern SDETs must understand how tests integrate into deployment pipelines. What "DevOps Light" Means: - Set up basic CI/CD pipelines (GitHub Actions or Jenkins) - Use Docker to containerize your test environments - Understand version control with Git/GitHub - Know how to trigger automated tests on code commits Learn how to create simple test pipelines and integrate them into CI/CD workflows. This skill separates entry-level QA from six-figure SDETs. ▶ 𝟯. 𝗕𝘂𝗶𝗹𝗱 𝗦𝗶𝗱𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 Theory alone won't land you interviews. Hands-on projects will. Why Side Projects Work: - They prove you can apply concepts to real problems - They fill your resume when you lack professional experience - They give you talking points in interviews - They show initiative and passion Project Ideas: - Automate testing for a public API - Create an end-to-end test suite for a demo e-commerce site - Contribute to open-source automation frameworks (More Advanced) ▶ 𝟰. 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲: 𝗦𝘁𝗮𝘆 𝗦𝗵𝗮𝗿𝗽, 𝗦𝘁𝗮𝘆 𝗥𝗲𝗮𝗱𝘆 Interview practice is an on-going process. Why Practice Now:

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.