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DevOps with Docker and Kubernetes

The course on DevOps utilizing Docker and Kubernetes offers a thorough exploration of essential containerization and orchestration technologies for contemporary DevOps methodologies.

Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

  1. The course on DevOps utilizing Docker and Kubernetes offers a thorough exploration of essential containerization and orchestration technologies for contemporary DevOps methodologies.

  2. It includes foundational knowledge of Docker, focusing on the creation and management of containers, as well as the deployment of containerized applications.

  3. Participants will gain insights into Kubernetes architecture, cluster management, and the deployment of scalable applications.

  4. This extensive training equips attendees to enhance workflow efficiency and boost application reliability in production settings.

  5. Overall, the course aims to empower professionals with the skills needed for effective DevOps practices.

CERTIFICATION:

  1. Participants are awarded a Certificate of Completion by the training provider.

  2. The course equips learners for certifications like Docker Certified Associate (DCA) and Certified Kubernetes Administrator (CKA).

  3. Completion of the course enhances professional qualifications in container management and orchestration.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

  1. Recognize the significance of Docker and Kubernetes in contemporary DevOps practices.

  2. Acquire skills to create, oversee, and deploy applications in containers with Docker.

  3. Obtain practical knowledge in managing and orchestrating Kubernetes clusters.

  4. Comprehend microservices architecture and the role of containers in its execution.

  5. Develop expertise in scaling, networking, and securing applications within containers.

Course Curriculum

Introduction to DevOps and Containerization
  1. Overview of DevOps practices and CI/CD workflows
  2. Introduction to Docker and Kubernetes
  3. Benefits of containerization
Docker Basics
  1. Installing Docker and understanding its architecture
  2. Building and managing Docker containers and images
  3. Docker Compose for multi-container applications
Kubernetes Fundamentals
  1. Kubernetes architecture: Nodes, pods, and clusters
  2. Understanding YAML files and resource configurations
  3. Deploying applications in Kubernetes
Advanced Docker and Kubernetes Concepts
  1. Docker Networking and Volume Management
  2. Kubernetes services: Load balancers and ingress controllers
  3. Helm charts for application deployment
Scaling and Monitoring
  1. Auto-scaling in Kubernetes using Horizontal Pod Autoscalers (HPA)
  2. Monitoring clusters with Prometheus and Grafana
  3. Logging with Fluentd and Elasticsearch
Security and Best Practices
  1. Securing Docker images and containers
  2. Kubernetes RBAC (Role-Based Access Control)
  3. Managing secrets and configurations securely
CI/CD Integration
  • Integrating Docker and Kubernetes into CI/CD pipelines
  • Tools: Jenkins, GitLab CI/CD, and ArgoCD
  • Deploying updates seamlessly in productio
Certification and Exam Preparation
  1. Exam overview and tips for DCA and CKA certifications
  2. Practice tests and hands-on scenarios
  3. Key documentation and study resources

Training Features

Hands-On Labs and Real-World Projects

Build, deploy, and manage containers and Kubernetes clusters using real-world scenarios.

Expert-Led Video Tutorials

Interactive lessons by certified Docker and Kubernetes professionals.

Mock Exams and Quizzes

Certification-aligned assessments to prepare for DCA and CKA exams.

Comprehensive Learning Materials

Access to Docker and Kubernetes whitepapers, study guides, and cheat sheets.

Community and Mentorship Support

Engage with instructors and peers for troubleshooting and collaborative learning.

24/7 Access and Cloud Lab Environments

Unlimited access to virtual environments for practical exercises and experimentation.

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