Corso Cisco AUTOCOR – Designing, Deploying and Managing Network Automation Systems

Network Automation Toolkits

• Overview of modern network automation tools and frameworks
• Comparison of automation approaches for enterprise network environments
• Evaluation of tool selection based on scalability, maintainability, and operational needs
• Role of scripting, APIs, IaC, CI/CD, and validation tools in automated networks
• Integration of automation toolchains into network operations

Network Task Automation with Python

• Use of Python to automate common network administration tasks
• CLI-based automation for device interaction and configuration workflows
• Script structure, error handling, and reusable automation logic
• Management of network data, variables, and configuration inputs
• Automation of repetitive operational tasks across network devices

REST APIs in Network Automation

• Core concepts of REST APIs in network automation
• Use of API documentation to understand endpoints, methods, and payloads
• Authentication and secure interaction with network device APIs
• Automation of API calls using Python libraries such as requests
• Integration of REST APIs into network management workflows

Network Automation with Ansible

• Use of Ansible for network configuration automation
• Creation and execution of Ansible playbooks for network devices
• Management of inventories, variables, and reusable automation tasks
• Automation of configuration changes across multiple devices
• Application of Ansible in repeatable and controlled network workflows

Network Automation with Terraform

• Use of Terraform for network Infrastructure as Code
• Definition and management of network resources through declarative configuration
• Automation of infrastructure changes using Terraform workflows
• Management of router interfaces and network parameters as code
• Evaluation of Terraform for scalable and consistent network provisioning

Infrastructure as Code Implementation

• Principles of Infrastructure as Code (IaC) for network management
• Translation of network configurations into version-controlled code
• Automation of configuration deployment and infrastructure changes
• Management of consistency, repeatability, and rollback strategies
• Application of IaC practices to modern automated network environments

Network Change Tracking with Git

• Use of Git for tracking network configuration changes
• Version control concepts applied to network automation projects
• Management of repositories, commits, branches, and change history
• Collaboration and auditability in network automation workflows
• Integration of Git with CI/CD pipelines and automation processes

Configuration Change Deployment with CI Pipelines

• Design of GitLab CI/CD pipelines for network automation
• Automated validation and deployment of network configuration changes
• Pipeline stages for testing, approval, and controlled execution
• Integration of automation scripts, IaC tools, and validation checks
• Reduction of operational risk through repeatable deployment workflows

Cisco Modeling Labs Integration for Test Network Environments

• Use of Cisco Modeling Labs (CML) to create test network environments
• Design and deployment of virtual network topologies for automation testing
• Integration of CML topologies into automated workflows
• Use of simulated environments before production deployment
• Automation of test topology creation and lifecycle management

Network State Validation with pyATS

• Use of pyATS for network state validation and automated testing
• Creation of validation scripts for configuration and operational checks
• Comparison of expected and actual network state
• Integration of pyATS testing into CI/CD automation pipelines
• Support for pre-deployment and post-deployment network validation

Model-Driven Telemetry for Network Monitoring

• Concepts of Model-Driven Telemetry (MDT) for real-time network monitoring
• Use of telemetry streams to collect operational data from Cisco devices
• Configuration of telemetry using model-driven approaches
• Analysis of network state, performance, and operational behavior
• Integration of telemetry data into automated operations workflows

Network Automation Solution Troubleshooting

• Diagnosis of common failures in network automation workflows
• Use of structured logs from Python, Ansible, and RESTCONF integrations
• Identification of errors related to connectivity, authentication, data models, and payloads
• Troubleshooting of CI/CD pipelines and automated deployment processes
• Improvement of automation reliability through logging and validation

Secure Coding Practices for Network Automation

• Application of secure coding practices in automation scripts
• Input validation, credential protection, and output sanitization
• Management of sensitive data and secrets in automation workflows
• Reduction of risks related to insecure scripts and exposed credentials
• Security hardening of Python, API, and automation tool integrations

Network Automation Environment Containerization with Docker Compose

• Use of Docker Compose to build multi-service automation environments
• Containerization of automation components and supporting services
• Management of local development and testing environments
• Deployment of repeatable environments for automation workflows
• Integration of containers into network automation toolchains

Trusted TLS Certificates Deployment for Secure Communication

• Role of TLS certificates in securing web interfaces and APIs
• Generation, signing, and installation of trusted certificates
• Protection of communications between automation tools and services
• Certificate management for secure network automation environments
• Security considerations for API-driven and web-based automation systems

Generative AI for Network Automation

• Role of Generative AI in network automation script creation
• Use of AI tools to support automation design, code generation, and troubleshooting
• Evaluation of benefits and risks of AI-assisted network operations
• Review and validation of AI-generated automation outputs
• Practical use of AI to accelerate network automation workflows

AI Agents for Network Automation

• Concepts of AI agents applied to network operations
• Design of agents capable of interacting with tools, APIs, and network data
• Use of AI agents to support multi-step network automation tasks
• Evaluation of control, safety, and validation in agentic workflows
• Application of AI agents in operational and automation scenarios

LLM and MCP Server Integration

• Integration of Large Language Models (LLMs) with external automation capabilities
• Use of MCP servers to connect LLMs with tools and network workflows
• Deployment of local LLM environments using tools such as Ollama
• Development of AI-enhanced network automation tools
• Design of secure and controlled LLM-powered automation architectures

Attività Laboratoriali

• Use Python to Automate Common Network Tasks
• Explore REST API Documentation
• Automate API Calls with Python Requests
• Construct and Send RESTCONF Requests
• Automate the Device Configuration with RESTCONF
• Create a Network Automation Solution with Ansible
• Automate Network Infrastructure with Terraform
• Manage Router Interfaces as Code
• Start Tracking Your Network State with GitLab
• Build a GitLab CI Pipeline for Network Configuration
• Create a Testing Network Environment with Cisco Modeling Labs
• Build a Python Script to Launch Test Topologies in Cisco Modeling Labs
• Integrate Cisco Modeling Labs Topologies into CI Pipeline
• Create a Configuration Validation Tool with pyATS
• Integrate pyATS Testing into Automated Pipelines
• Set Up MDT on a Cisco Router Using YANG Suite
• Troubleshoot an Automation Script
• Harden an Automation Script
• Containerize Automation Components
• Set Up Local LLM with Ollama
• Build a Network Automation Tool with Python and Ollama
• Build and Launch a FastMCP Server