Upon completion of this course, participants will be able to:

• Design scalable and resilient **Distributed SCADA Architectures** for wide-area networks.
• Master the use of virtualization, containerization, and cloud technologies for SCADA deployment.
• Conduct comprehensive trade-off analysis for selecting centralized versus distributed control models.
• Design and implement **Disaster Tolerance and Business Continuity (BCP)** strategies for control systems.
• Optimize data collection, polling, and buffering techniques for high-volume, high-speed applications.
• Integrate advanced systems (e.g., MES, ERP) with the control network for end-to-end data flow.
• Develop a comprehensive **SCADA System Upgrade and Migration Roadmap**.
• Evaluate the impact of high-performance design decisions on cybersecurity and maintenance.

• Lead SCADA and Control System Architects
• Senior Automation and IT/OT Integration Engineers
• Project Managers responsible for multi-site control system rollouts
• Enterprise Architects and Technology Planners
• Senior Consultants specializing in critical infrastructure
• Executives overseeing control system modernization

• Architectural workshop: working in teams to design a distributed SCADA solution for a large regional utility.
• Group activity: developing a comprehensive trade-off matrix for a virtualization vs. bare-metal deployment decision.
• Individual exercises in creating a phased migration plan for a legacy SCADA system.
• Case studies of large-scale SCADA deployments and their architectural challenges (e.g., oil pipeline networks).
• Discussions on the cost justification and ROI of investing in advanced redundancy.

Unit 1: Architectural Models and Trade-Offs

• Analyzing the benefits and limitations of centralized (MTU) vs. distributed architectures
• Designing multi-tier, multi-server architectures for performance and scale
• The role of communications infrastructure in dictating architectural choices

• Methodologies for accurately sizing servers, historians, and network capacity (data points, I/O counts)
• Planning for future expansion and lifecycle maintenance requirements

Unit 2: High Availability and Disaster Tolerance

• Designing geographically distributed redundancy and failover systems (hot, warm, cold sites)
• Developing comprehensive **Business Continuity Plans (BCP)** for control centers

• Techniques for optimizing system performance: load balancing, process isolation, and threading
• Best practices for implementing virtualized and containerized SCADA environments

Unit 3: Cloud and IT/OT Integration

• Evaluating the feasibility and security requirements of deploying SCADA services to the public or private cloud
• Strategies for secure, high-speed data exchange between the control network and cloud data lakes

• Architectural design for seamless data flow between SCADA/Historian and MES/ERP systems
• Using integration brokers and APIs to decouple systems and improve reliability

Unit 4: Data Handling and Network Optimization

• Techniques for handling high-frequency data logging and real-time data processing
• Optimizing SCADA and PLC driver configurations for massive data sets and low latency

• Designing the industrial network backbone (Layer 3 switching, fiber optic) for SCADA traffic priority
• Managing bandwidth and quality of service (QoS) for mission-critical protocols

Unit 5: Migration and Governance

• Developing a detailed, low-risk **SCADA Migration Roadmap** (Phasing, Parallel Operation, Rollback)
• Managing the technical and financial risks of modernizing legacy control systems

• Establishing architectural standards and governance processes for all future SCADA modifications
• Integrating security and maintenance requirements into the long-term design lifecycle