Kubernetes and Cloud Native Associate (KCNA) - Mock Exams
Description
Kubernetes and Cloud Native Associate (KCNA)
Prepare thoroughly for the Kubernetes and Cloud Native Associate (KCNA) certification with this professionally developed mock exam course. Designed for aspiring cloud-native professionals, DevOps practitioners, system administrators, and developers, this course offers six full-length mock exams that closely simulate the structure, content, and difficulty level of the official KCNA certification exam.
Each mock exam is meticulously curated to cover the core domains of the KCNA exam blueprint, including Kubernetes architecture and fundamentals, container orchestration, cloud-native observability, networking, security, and the broader cloud-native ecosystem. The questions are crafted to test your conceptual understanding as well as your practical knowledge of modern cloud-native technologies.
Every question includes a comprehensive explanation of the correct answer. These explanations not only reinforce key concepts but also clarify nuanced topics, helping you identify and address any knowledge gaps. Whether you are reviewing foundational Kubernetes concepts or diving deeper into CNCF projects and best practices, this course provides the structured practice and expert insight needed for effective exam readiness.
By the end of this course, you will have enhanced your confidence, sharpened your problem-solving skills, and strengthened your understanding of the cloud-native landscape—positioning yourself for success in the KCNA certification and beyond.
Can I retake the practice tests?
Yes, you can attempt each practice test as many times as you like. After completing a test, you'll see your final score. Each time you retake the test, the questions and answer choices will be shuffled for a fresh experience.
Is there a time limit for the practice tests?
Yes, each test includes a time limit of 120 seconds per question.
What score do I need to pass?
You need to score at least 70% on each practice test to pass.
Are explanations provided for the questions?
Yes, every question comes with a detailed explanation.
Can I review my answers after the test?
Absolutely. You’ll be able to review all your submitted answers and see which ones were correct or incorrect.
Are the questions updated frequently?
Yes, the questions are regularly updated to provide the best and most relevant learning experience.
Additional Note: It’s highly recommended that you take the practice exams multiple times until you're consistently scoring 90% or higher. Don’t hesitate—start your preparation today. Good luck!
Who this course is for:
- Aspiring Cloud-Native Professionals
- DevOps Engineers
- Site Reliability Engineers (SREs)
- Software Developers and Application Engineers
- System Administrators and Infrastructure Engineers
- Platform Engineers and Cloud Engineers
- IT Students and Recent Graduates
- Technical Project Managers and Product Owners
- Security and Compliance Analysts
- Technology Consultants and Solutions Architects
Instructor
- 4.3 Instructor Rating
- 11,181 Reviews
- 431,711 Students
- 164 Courses
EN
Python Developer/AI Enthusiast/Data Scientist/Stockbroker
Enthusiast of new technologies, particularly in the areas of artificial intelligence, the Python language, big data and cloud solutions. Graduate of postgraduate studies at the Polish-Japanese Academy of Information Technology in the field of Computer Science and Big Data specialization. Master's degree graduate in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science at the University of Lodz. Former PhD student at the faculty of mathematics. Since 2015, a licensed Securities Broker with the right to provide investment advisory services (license number 3073). Lecturer at the GPW Foundation, conducting training for investors in the field of technical analysis, behavioral finance, and principles of managing a portfolio of financial instruments.
Founder at e-smartdata
PL
Data Scientist, Securities Broker
Jestem miłośnikiem nowych technologii, szczególnie w obszarze sztucznej inteligencji, języka Python big data oraz rozwiązań chmurowych. Posiadam stopień absolwenta podyplomowych studiów na kierunku Informatyka, specjalizacja Big Data w Polsko-Japońskiej Akademii Technik Komputerowych oraz magistra z Matematyki Finansowej i Aktuarialnej na wydziale Matematyki i Informatyki Uniwersytetu Łódzkiego. Od 2015 roku posiadam licencję Maklera Papierów Wartościowych z uprawnieniami do czynności doradztwa inwestycyjnego (nr 3073). Jestem również wykładowcą w Fundacji GPW prowadzącym szkolenia dla inwestorów z zakresu analizy technicznej, finansów behawioralnych i zasad zarządzania portfelem instrumentów finansowych. Mam doświadczenie w prowadzeniu zajęć dydaktycznych na wyższej uczelni z przedmiotów związanych z rachunkiem prawdopodobieństwa i statystyką. Moje główne obszary zainteresowań to język Python, sztuczna inteligencja, web development oraz rynki finansowe.
Założyciel platformy e-smartdata