Course Overview: Storage Automation Masterclass
Theme: Transition from CLI to Infrastructure-as-Code (IaC)
Access: 5 Years of Repeated Live Training Access
Scope: NetApp, Hitachi, Pure, PowerMax, and Brocade SAN
π Training Logistics
Schedule: 8:00 PM β 9:00 PM IST
Duration: 35 Hours (Live, Instructor-led)
Bonus: Python Certification (PCEP) guidance.
Contact: +91 9647524712 (WhatsApp)
π Key Highlights
Zero-to-Hero: No prior coding needed; covers Python & Ansible from scratch.
Multi-Vendor: Automate NetApp, Hitachi, Pure, PowerMax, and Brocade.
Modern Tech: Python REST APIs, Terraform, Ansible, and GitOps.
Advanced AI: AIOps, Predictive Self-Healing, and Event-Driven Ansible.
π Technical Syllabus
Phase 1: Foundations & Python Automation
Python for Storage: Master ONTAP REST APIs, Python Client Libraries, and SVM/Volume management.
REST Use Cases: Automate Aggregates, Volumes, and Snapshot workflows.
Phase 2: Configuration & Ansible Orchestration
Ansible Essentials: YAML basics, Playbook architecture, and Module installation.
Protocol Automation: CIFS (SMB), NFS, and SAN (iSCSI, FC, NVMe-OF) configuration.
Object Storage: Automating S3 provisioning via Ansible.
Phase 3: Multi-Vendor & SAN Switching
Storage Arrays: Hitachi VSP, Pure Storage, and PowerMax allocation automation.
SAN Infrastructure: Brocade SAN zoning, FOS upgrades, and Logical Switch setup.
Phase 4: Advanced Operations & Hybrid Cloud
Monitoring & Metrics: Performance tracking and AIQUM data collection.
Data Protection: SnapMirror automation, Snapshot management, and SVM-DR.
Cloud IaC: NetApp CVO setup on AWS/GCP via Ansible and Terraform.
Phase 5: DevOps, SecOps & AI (The "Future" Track)
Git for IaC: Version control, Branching, Secrets management, and GitOps.
Terraform: State management and automated deployments (CVO/ANF).
Lifecycle & Health: Bulk ONTAP upgrades and AI-driven automated health reports.
Predictive AIOps: Active IQ integration, self-healing drift management, and capacity prediction.
Security: AI-enhanced Autonomous Ransomware Protection (ARP) and data classification.
