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Course Outline
Advanced GNS3 Architecture
- Overview of GNS3 architecture for distributed deployments.
- Performance optimization for GNS3 server and GNS3 VM.
- Managing multiple projects and collaborative workflows.
Network Automation with Python and Ansible
- Introduction to automation in network engineering.
- Creating and deploying automation scripts in GNS3.
- Automating router and switch configuration with Ansible playbooks.
- Testing network state and compliance with automated checks.
Docker Integration in GNS3
- Installing and configuring Docker containers within GNS3.
- Utilizing prebuilt Docker appliances (e.g., web servers, DNS, Linux services).
- Building custom Docker containers for network testing.
- Simulating microservices and service chaining in GNS3 topologies.
Cloud and Hybrid Lab Integration
- Designing hybrid environments using GNS3 and public clouds.
- Connecting GNS3 to AWS, Azure, or GCP via VPN and tunneling.
- Deploying cloud-based endpoints and integrating with simulated networks.
- Security and access considerations for hybrid topologies.
Multi-Vendor Testing and Simulation
- Running and managing multiple vendor VMs (e.g., Cisco, Juniper, Palo Alto).
- Using QEMU, IOU/IOL, and VirtualBox appliances together.
- Traffic generation and application emulation for interoperability testing.
CI/CD and Advanced Lab Automation
- Integrating GNS3 with Git and CI pipelines for version control and testing.
- Automating topology deployment and rollback.
- Using REST APIs to control GNS3 from external scripts.
Use Cases and Best Practices
- Lab design for pre-deployment validation.
- Documenting network behavior and configurations.
- Reusable lab templates and team workflows.
Summary and Next Steps
Requirements
- Proficiency in creating GNS3 topologies and configuring devices.
- Working knowledge of Python or Ansible.
- Familiarity with containerization and cloud fundamentals.
Audience
- Senior network engineers and DevNet professionals.
- Engineers integrating GNS3 with automation frameworks (e.g., Ansible, Python).
- Professionals experimenting with Dockerized services in virtual labs.
- Advanced users working on hybrid cloud labs or simulating multi-vendor environments.
21 Hours
Testimonials (1)
communication, knowledge from experience, solve problems,
