Kubernetes (K8s) is an open-source system for deploying, scaling, automating, and managing containerized applications. This automation helps in improving productivity, efficiency, and reduction of operational downtime for enterprises.
Kubernetes (K8s) is an open-source system for deploying, scaling, automating, and managing containerized applications. This automation helps in improving productivity, efficiency, and reduction of operational downtime for enterprises.
This training course helps you develop your skills and knowledge in Kubernetes. In addition, you can also explore basic to advanced concepts of Kubernetes such as Pods, Nodes, Schedulers, Replication Controller & Replica Sets, etc.
The course is designed for Cloud and DevOps professionals working as cloud administrators, and Kubernetes administrators managing Kubernetes instances.
Exam Prep CKA: Certified Kubernetes Administrator course contains 7+ hours of Training content. Learners could find a combination of Video Lectures. Reading material and quizzes in the training course with comprehensive coverage of all topics regarding automating and managing containerized applications. These lectures are divided into 6 Modules and each module is further split into Lessons. The entire course includes Assessments (both Graded and Non-Graded) to validate learners' knowledge.
Module 1: Kubernetes: Core Concepts
Module 2: Kubernetes: Storage and Networking
Module 3: Kubernetes: Scaling Workloads
Module 4: Kubernetes: Pods and Schedulers
Module 5: Kubernetes: Cluster Architecture, Installation & Configuration
Module 6: Kubernetes: Troubleshooting
Candidate should have hands-on knowledge of Docker, and Kubernetes (K8s). One should have experience with Linux shells, Git, GitHub and virtual machines in cloud environments. By the end of this course, a learner will be able to:
- Implement Kubernetes cluster and evaluate its basic components.
- Explore Networking and Storage concepts in Kubernetes.
- Analyze and Implement application scaling in Kubernetes.
- Explore Pods and Schedulers concepts in Kubernetes.
- Troubleshoot Kubernetes cluster using monitoring and logging techniques.
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