Puppet Advanced Training Course

Architecture & Multi-Master Deployment Patterns

• Advanced Puppet topology: responsibilities of master nodes, agent nodes, PuppetDB, and the coordination layer
• Strategies for multi-datacenter and multi-environment classification
• Load balancing architecture, including HAProxy/NGINX configuration and certificate-based routing
• Site-wide node classification, role/profile separation, and centralized control
• Lab: Provision a multi-master cluster, configure the load balancer, establish agent routing, and validate failover behaviour

Advanced Development Environments & Code Management

• Puppet Development Kit (PDK), module scaffolding, and linting/style enforcement
• Version control workflows: Git branching, pull request reviews, and automated provisioning
• Puppetfile/R10k and code management servers for environment synchronization
• Testing frameworks: RSpec-Puppet, Beaker, and setting up integration test pipelines
• Lab: Scaffold production-grade modules, configure Git-backed code management, and execute automated test suites

Puppet Module Architecture & Code Compression

• Advanced module structure: roles, profiles, base modules, and dependency management
• Custom facts, custom functions, and dynamic node classification techniques
• Catalog compilation optimization: fact caching, --compile mode, and resource filtering
• Code compression techniques: reducing agent runtime, optimizing file synchronization, and filebucket management
• Lab: Optimize a bloated module into a lean, cached architecture; benchmark catalog compilation times before and after optimization

Hiera v5: Data Separation & Encryption

• Hiera hierarchy design: environment, role, and node-level data sources
• Backend configuration: JSON, YAML, PuppetDB, and external secrets manager integration
• Hiera-eyaml implementation: symmetric/asymmetric key management, GPG encryption, and secure credential storage
• Dynamic data lookups, interpolation, and fallback chain optimization
• Lab: Implement encrypted password/secret storage, configure multi-tier hierarchy, and resolve dynamic lookups across environments

Virtual & Exported Resources: Cross-Node Resource Aggregation

• Virtual resource types: defining, collecting, and synchronization patterns
• Exported resources: @@, << syntax, PuppetDB-backed resource queries, and modern catalog aggregation
• Use cases: centralized DNS, certificate distribution, firewall topology, and load balancer state synchronization
• Lab: Deploy cross-node service registration, synchronize resource states, and validate aggregation accuracy

Reporting, Auditing & Compliance Tracking

• PuppetDB architecture: data models, indexing, and API usage for external tools
• Custom reporting hooks, Logstash/Elastic integration, and SIEM forwarding patterns
• Compliance mapping: audit trails, configuration drift detection, and policy enforcement via catalogs
• Node state visualization, catalog history, and fact retention strategies
• Lab: Configure PuppetDB data retention, build custom audit dashboards, and enforce compliance checks via catalogs

MCollective: Infrastructure Automation & Coordination

• MCollective architecture: RPC framework, agent registry, filters, and security model (ActiveMQ, SSL, certificates)
• Writing custom action classes and agent scripts for infrastructure automation
• Coordinating Puppet runs, service restarts, patching, and batch operations
• Integration patterns with Puppet: catalog-driven automation and event-triggered workflows
• Lab: Deploy MCollective, create custom agents, run batch orchestration, and synchronize with Puppet agent runs

Troubleshooting & Performance Profiling

• Advanced log analysis: --debug, --trace, --detailed-exitcodes, and PuppetDB query logs
• Fact resolution debugging, environment classification errors, and dependency cycle detection
• Catalog compilation bottlenecks, memory profiling, and network timeout mitigation
• Recovery strategies: node reset, PuppetDB cleanup, and state reconciliation
• Lab: Diagnose and resolve simulated catalog failures, fact resolution loops, and performance degradation scenarios

Scaling Puppet at Enterprise Scale

• Database tuning: PostgreSQL/MongoDB optimization, connection pooling, and indexing
• Node caching, catalog caching, and DNS/TLS optimization for high-frequency polling
• Load distribution, worker thread tuning, and PuppetDB sharding strategies
• Site-wide rollouts, maintenance windows, and rollback procedures
• Lab:Simulate a high-node environment, tune database/agent parameters, validate scaling limits, and document operational runbooks