Visit This Web URL https://masterytrail.com/product/accredited-expert-level-ibm-cloud-migration-factory-advanced-video-course Lesson 1: Introduction to the IBM Cloud Migration Factory at Scale
1.1 Defining the Cloud Migration Factory concept in an enterprise context
1.2 The strategic imperative for a migration factory
1.3 Key characteristics of an expert-level migration factory
1.4 Overview of the IBM Cloud Migration Factory framework and accelerators
1.5 Understanding the factory lifecycle and phases
1.6 Roles and responsibilities within a large-scale factory
1.7 مترics for measuring factory success and maturity
1.8 Common challenges in large-scale migrations and factory approaches
1.9 The role of automation and AI in factory operations
1.10 Positioning the factory within the broader digital transformation journey
Lesson 2: Advanced Migration Strategy and Planning
2.1 Deep dive into advanced workload assessment methodologies
2.2 Developing sophisticated migration wave planning techniques
2.3 Portfolio analysis and rationalization for complex environments
2.4 Defining advanced migration patterns (Rehost, Replatform, Refactor, etc.)
2.5 Страtegic considerations for hybrid and multi-cloud migrations
2.6 Business case development and ROI analysis for factory initiatives
2.7 Identifying and mitigating advanced migration risks
2.8 Dependency mapping and orchestration for interconnected applications
2.9 Utilizing AI and machine learning for migration planning optimization
2.10 Capacity planning and cost modeling at scale
Lesson 3: Setting up the Migration Factory Governance Model
3.1 Establishing a robust governance framework for factory operations
3.2 Defining decision-making processes and escalation paths
3.3 Implementing policy and compliance enforcement within the factory
3.4 Role of a Cloud Center of Excellence (CCoE) in factory governance
3.5 Managing stakeholders and communication strategies for a large factory
3.6 Risk management and quality assurance processes
3.7 Establishing a continuous improvement framework for the factory
3.8 Legal and contractual considerations in factory engagements
3.9 Integrating security and compliance into the governance model
3.10 Auditing and reporting mechanisms for governance
Lesson 4: Deep Dive into Factory Methodologies and Frameworks
4.1 Adapting Agile and DevOps methodologies for migration factories
4.2 Implementing a repeatable and scalable migration process
4.3 Utilizing IBM's recommended migration methodologies and tools
4.4 Customizing methodologies for specific workload types (e.g., SAP, VMware)
4.5 Incorporating quality gates and checkpoints throughout the factory process
4.6 Managing in-flight migrations and pipeline management
4.7 Knowledge management and lessons learned within the factory
4.8 Building a culture of continuous delivery in migration
4.9 Applying lean principles to optimize factory throughput
4.10 Case studies and best practices from successful large-scale factories
Lesson 5: Advanced Discovery and Assessment Techniques
5.1 Implementing automated discovery tools for complex environments
5.2 Deep dependency mapping and analysis across applications and infrastructure
5.3 Performance profiling and baseline establishment
5.4 Security and compliance assessment of existing workloads
5.5 Cost analysis and optimization opportunities identification
5.6 Utilizing AI for anomaly detection in discovery data
5.7 Assessing technical debt and modernization potential
5.8 Data classification and handling requirements during assessment
5.9 Creating a comprehensive and accurate configuration management database (CMDB) for migration
5.10 Reporting and visualization of assessment findings for stakeholders
Lesson 6: Designing the Target IBM Cloud Environment
6.1 Advanced IBM Cloud architecture patterns for migration landing zones
6.2 Network design and connectivity strategies for hybrid and multi-cloud
6.3 Security architecture and control implementation in the target environment
6.4 Designing for high availability and disaster recovery on IBM Cloud
6.5 Cost optimization strategies for cloud resource provisioning
6.6 Identity and access management (IAM) design for the target state
6.7 Integrating with existing on-premises and other cloud environments
6.8 Infrastructure as Code (IaC) for target environment provisioning
6.9 Designing for scalability and elasticity
6.10 Environment provisioning automation and orchestration
Lesson 7: Advanced Application Migration Strategies
7.1 Migrating complex multi-tier applications
7.2 Strategies for handling legacy applications and systems
7.3 Microservices extraction and containerization strategies
7.4 Database migration techniques for various database platforms
7.5 Application refactoring and re-platforming approaches
7.6 Migrating COTS (Commercial Off-the-Shelf) applications
7.7 Handling application dependencies and integration points
7.8 Testing strategies for migrated applications (functional, performance, security)
7.9 Post-migration application optimization and tuning
7.10 Utilizing IBM Cloud services for application modernization
Lesson 8: Expert-Level Data Migration Techniques
8.1 Planning and executing large-scale data migrations with minimal downtime
8.2 Data migration strategies for different database types and sizes
8.3 Ensuring data integrity and consistency during migration
8.4 Data transformation and cleansing as part of the migration process
8.5 Security considerations for data in transit and at rest on IBM Cloud
8.6 Utilizing IBM data migration tools and services
8.7 Strategies for migrating big data and analytics platforms
8.8 Data validation and reconciliation after migration
8.9 Handling data sovereignty and compliance requirements
8.10 Continuous data synchronization strategies
Lesson 9: Networking and Connectivity in a Migration Factory
9.1 Advanced IBM Cloud networking concepts (VPC, Transit Gateway, Direct Link)
9.2 Designing secure and performant network connectivity for migration
9.3 IP addressing and subnetting strategies for large environments
9.4 DNS and load balancing considerations
9.5 Network segmentation and security group best practices
9.6 Troubleshooting network connectivity issues during migration
9.7 Optimizing network performance for data transfer
9.8 Utilizing network automation tools
9.9 Integrating with existing network infrastructure
9.10 Monitoring and managing network traffic
Lesson 10: Implementing Robust Security in the Factory
10.1 IBM Cloud security services and their application in migration
10.2 Implementing a layered security approach for the factory and migrated workloads
10.3 Identity and access management (IAM) best practices for migration personnel
10.4 Data security and encryption strategies
10.5 Vulnerability management and threat detection
10.6 Security testing and validation of migrated workloads
10.7 Compliance requirements and security framework adherence (e.g.,
HIPAA, GDPR)
10.8 Incident response planning for migration security events
10.9 Security automation and orchestration
10.10 Continuous security monitoring and improvement
Lesson 11: Automation and Tooling in the Migration Factory
11.1 Identifying automation opportunities across the migration lifecycle
11.2 Evaluating and selecting appropriate IBM Cloud and third-party migration tools
11.3 Implementing Infrastructure as Code (IaC) for environment provisioning
11.4 Automating workload migration using specialized tools
11.5 Orchestrating complex migration workflows
11.6 Implementing automated testing frameworks
11.7 Utilizing CI/CD pipelines for migration and modernization
11.8 Developing custom automation scripts and playbooks
11.9 Integrating automation tools with existing IT service management (ITSM) systems
11.10 Measuring the effectiveness of automation
Lesson 12: Financial Management and Cost Optimization in the Cloud
12.1 Advanced cloud cost modeling and forecasting
12.2 Implementing cost monitoring and reporting mechanisms
12.3 Strategies for optimizing cloud spend post-migration
12.4 Reserved instances, savings plans, and other cost-saving programs
12.5 Showback and chargeback models for cloud services
12.6 Rightsizing and auto-scaling strategies for cost efficiency
12.7 Utilizing IBM Cloud cost management tools
12.8 Financial governance and budget control for the factory
12.9 Identifying and addressing cost anomalies
12.10 Continuous cost optimization as an ongoing process
Lesson 13: Managing People and Skills in the Migration Factory
13.1 Building and organizing high-performing migration teams
13.2 Identifying required skills and addressing skill gaps
13.3 Training and upskilling programs for factory personnel
13.4 Establishing a culture of collaboration and knowledge sharing
13.5 Managing change and addressing resistance to new processes
13.6 Performance management and motivation within the factory
13.7 Resource allocation and capacity management for personnel
13.8 Partnering with external service providers and integrators
13.9 Fostering a DevOps culture within the migration teams
13.10 Ensuring knowledge transfer and sustainability
Lesson 14: Operationalizing the Migration Factory
14.1 Establishing standard operating procedures (SOPs) for factory processes
14.2 Implementing a ticketing and workflow management system
14.3 Monitoring factory progress and identifying bottlenecks
14.4 Reporting on factory performance and key metrics
14.5 Managing communication and collaboration within the factory
14.6 Incident management and problem resolution within the factory
14.7 Quality assurance and control processes
14.8 Knowledge base management and documentation
14.9 Continual service improvement for factory operations
14.10 Scaling factory operations to meet demand
Lesson 15: Advanced Hybrid Cloud Migration Scenarios
15.1 Strategies for migrating workloads to and from on-premises environments
15.2 Integrating IBM Cloud with existing data centers
15.3 Managing hybrid cloud networking and security
15.4 Data synchronization and replication in hybrid environments
15.5 Workload placement decisions in a hybrid model
15.6 Utilizing IBM Cloud Satellite for hybrid deployments
15.7 Disaster recovery and business continuity in hybrid scenarios
15.8 Operational challenges in managing hybrid cloud migrations
15.9 Governing hybrid cloud environments within the factory
15.10 Future trends in hybrid cloud migration
Lesson 16: Multi-Cloud Migration Strategies
16.1 Planning and executing migrations involving multiple cloud providers
16.2 Challenges and benefits of multi-cloud migration
16.3 Designing for interoperability and portability across clouds
16.4 Managing multi-cloud networking and security complexities
16.5 Data migration and synchronization across different cloud platforms
16.6 Utilizing multi-cloud management tools and platforms
16.7 Governance and compliance in a multi-cloud factory
16.8 Cost management in a multi-cloud environment
16.9 Vendor lock-in mitigation strategies
16.10 Future of multi-cloud migration and the role of the factory
Lesson 17: Migrating Specific Workload Types - Databases
17.1 Advanced strategies for migrating relational databases (e.g., Db2, Oracle, SQL Server)
17.2 Migrating NoSQL databases and data stores
17.3 Techniques for minimizing downtime during database migration
17.4 Data replication and synchronization methods
17.5 Performance tuning and optimization of migrated databases
17.6 Security considerations for databases in the cloud
17.7 Utilizing IBM Cloud database services and migration tools
17.8 Migrating data warehouses and data lakes
17.9 Handling database schema changes and compatibility issues
17.10 Post-migration database management and monitoring
Lesson 18: Migrating Specific Workload Types - Applications
18.1 Strategies for migrating enterprise resource planning (ERP) systems (e.g., SAP)
18.2 Migrating customer relationship management (CRM) applications
18.3 Handling custom-built and legacy applications
18.4 Migrating web applications and microservices
18.5 Strategies for migrating containerized applications
18.6 Testing and validation of migrated applications
18.7 Performance optimization of applications in the cloud
18.8 Security considerations for migrated applications
18.9 Utilizing IBM Cloud services for application modernization
18.10 Post-migration application support and maintenance
Lesson 19: Migrating Specific Workload Types - Infrastructure
19.1 Migrating virtual machines (VMs) from various hypervisors (VMware, Hyper-V)
19.2 Strategies for migrating physical servers
19.3 Handling complex server configurations and dependencies
19.4 Storage migration techniques and options on IBM Cloud
19.5 Network infrastructure migration considerations
19.6 Migrating operating systems and their configurations
19.7 Bare metal server migration strategies
19.8 Utilizing IBM Cloud infrastructure services for migration
19.9 Testing and validation of migrated infrastructure
19.10 Post-migration infrastructure management and monitoring
Lesson 20: Application Modernization within the Factory
20.1 Identifying applications suitable for modernization during migration
20.2 Strategies for modernizing applications (re-platforming, refactoring, re-architecting)
20.3 Utilizing containerization and Kubernetes for modernization
20.4 Implementing serverless architectures on IBM Cloud
20.5 Extracting microservices from monolithic applications
20.6 APIfication of legacy application functionalities
20.7 Integrating modernization with the migration factory process
20.8 Skills and resources required for application modernization
20.9 Measuring the business value of modernization
20.10 Future trends in application modernization and the factory's role
Lesson 21: Data Center Exit Strategies with a Migration Factory
21.1 Planning and executing a complete data center exit
21.2 Strategies for migrating all workloads and data from a physical data center
21.3 Managing the logistics and complexities of a data center shutdown
21.4 Minimizing business disruption during a data center exit
21.5 Decommissioning of physical infrastructure
21.6 Security and compliance considerations for data center exit
21.7 Cost considerations for data center exit
2.1.8 Utilizing the migration factory to accelerate data center exit
21.9 Case studies of successful data center exits
21.10 Lessons learned from data center exit projects
Lesson 22: Advanced Testing and Validation in the Factory
22.1 Developing a comprehensive testing strategy for large-scale migration
22.2 Types of testing in a migration factory (functional, performance, security, UAT)
22.3 Automating migration testing processes
22.4 Establishing test environments and data requirements
22.5 Performance and load testing methodologies for the cloud
22.6 Security testing and vulnerability assessment of migrated workloads
22.7 User acceptance testing (UAT) planning and execution
22.8 Defect tracking and management in the factory
22.9 Reporting and analysis of testing results
22.10 Continuous testing as part of the migration pipeline
Lesson 23: Performance Monitoring and Optimization
23.1 Establishing baseline performance metrics before migration
23.2 Implementing robust monitoring solutions on IBM Cloud
23.3 Performance analysis and troubleshooting of migrated workloads
23.4 Identifying and addressing performance bottlenecks
23.5 Utilizing auto-scaling and load balancing for performance
23.6 Capacity management and performance forecasting
23.7 Cost optimization through performance tuning
23.8 Utilizing AI for performance anomaly detection
23.9 Continuous performance monitoring and optimization as an ongoing process
23.10 Reporting on performance improvements
Lesson 24: Security Operations in the Cloud Migration Factory
24.1 Integrating security operations into the factory workflow
24.2 Monitoring security events and incidents
24.3 Incident response and management in the cloud
24.4 Vulnerability management and patch management for migrated workloads
24.5 Security automation and orchestration in SecOps
24.6 Threat intelligence and proactive security measures
24.7 Compliance monitoring and reporting
24.8 Security awareness and training for factory personnel
24.9 Collaborating with security teams
24.10 Continuous improvement of security operations
Lesson 25: Governance, Risk, and Compliance (GRC) in Depth
25.1 Establishing a comprehensive GRC framework for cloud migration
25.2 Identifying and assessing migration-related risks
25.3 Developing and implementing risk mitigation strategies
25.4 Adhering to industry-specific compliance regulations (e.g.,
PCI DSS, ISO 27001)
25.5 Utilizing IBM Cloud compliance offerings and tools
25.6 Conducting audits and assessments for compliance
25.7 Implementing data privacy and protection measures (GDPR, CCPA)
25.8 Managing contractual obligations and service level agreements (SLAs)
25.9 Establishing a continuous GRC monitoring program
25.10 Reporting on GRC posture to stakeholders
Lesson 26: Financial Operations (FinOps) for Cloud Migration
26.1 Implementing FinOps principles in a migration factory
26.2 Cloud cost allocation and showback/chargeback
26.3 Budgeting and forecasting for cloud spend
26.4 Cost optimization strategies and best practices
26.5 Utilizing FinOps tools and platforms
26.6 Establishing a FinOps culture within the organization
26.7 Reporting on cloud financial performance
26.8 Identifying cost-saving opportunities
26.9 Collaborating with finance teams
26.10 Continuous monitoring and optimization of cloud costs
Lesson 27: Disaster Recovery and Business Continuity
27.1 Designing and implementing DR/BC strategies on IBM Cloud
27.2 RTO and RPO considerations for different workload tiers
27.3 Utilizing IBM Cloud DR services (e.g., Cloud Satellite for DR)
27.4 Testing and validating DR/BC plans
27.5 Automating DR/BC processes
27.6 Managing DR/BC for hybrid and multi-cloud environments
27.7 Cost considerations for DR/BC solutions
27.8 Integrating DR/BC into the migration planning
27.9 Establishing a continuous DR/BC testing program
27.10 Reporting on DR/BC readiness
Lesson 28: Incident Management and Problem Resolution
28.1 Establishing incident management processes for migration events
28.2 Identifying and classifying migration-related incidents
28.3 Troubleshooting and diagnosing issues during migration
28.4 Root cause analysis of migration failures
28.5 Implementing problem resolution strategies
28.6 Utilizing monitoring and logging tools for incident detection
28.7 Communicating incident status to stakeholders
28.8 Post-incident review and lessons learned
28.9 Automating incident response
28.10 Integrating with existing IT service management (ITSM) tools
Lesson 29: Communication and Stakeholder Management
29.1 Developing a comprehensive communication plan for the migration factory
29.2 Identifying key stakeholders and their communication needs
29.3 Establishing regular communication channels and cadences
29.4 Reporting on migration progress and status
29.5 Managing stakeholder expectations
29.6 Handling resistance to change and addressing concerns
29.7 Celebrating successes and recognizing contributions
29.8 Utilizing collaboration tools
29.9 Crisis communication planning
29.10 Tailoring communication for different audiences
Lesson 30: Building a Cloud-First Culture
30.1 Strategies for fostering a cloud-first mindset within the organization
30.2 Educating employees about the benefits of cloud migration
30.3 Addressing cultural barriers to cloud adoption
30.4 Empowering teams to embrace cloud technologies
30.5 Establishing a culture of innovation and experimentation
30.6 Recognizing and rewarding cloud adoption
30.7 Leading by example
30.8 Communicating the vision and strategy for cloud
30.9 Creating a continuous learning environment
30.10 Measuring the impact of cultural change
Lesson 31: Advanced Migration Tooling and Automation Platforms
31.1 Deep dive into specific IBM Cloud migration tools (e.g., Cloud Migration Services)
31.2 Evaluating and integrating third-party migration tools
31.3 Utilizing infrastructure as Code (IaC) tools (Terraform, Ansible)
31.4 Implementing configuration management tools (Chef, Puppet)
31.5 Orchestration platforms and workflow automation
31.6 Scripting and programming for migration automation
31.7 Utilizing AI-powered automation in migration
31.8 Building a custom migration automation framework
31.9 Testing and validating automation scripts and workflows
31.10 Maintaining and updating automation assets
Lesson 32: Leveraging AI and Machine Learning in the Factory
32.1 Identifying use cases for AI/ML in cloud migration
32.2 Utilizing AI for workload assessment and dependency mapping
32.3 Applying ML for migration wave planning and optimization
32.4 AI-powered performance monitoring and anomaly detection
32.5 Automating migration tasks using AI
32.6 Predicting migration risks and issues using ML
32.7 Utilizing AI for cost optimization
32.8 Implementing chatbots and virtual assistants for factory support
32.9 Ethical considerations of using AI in migration
32.10 Future potential of AI/ML in cloud migration factories
Lesson 33: Advanced Troubleshooting and Problem Solving
33.1 Advanced techniques for diagnosing migration issues
33.2 Utilizing logging and monitoring tools for troubleshooting
33.3 Analyzing network and connectivity problems
33.4 Debugging application migration failures
33.5 Resolving database migration challenges
33.6 Troubleshooting infrastructure provisioning issues
33.7 Identifying and addressing performance bottlenecks
33.8 Collaborating with IBM support for complex issues
33.9 Developing a troubleshooting knowledge base
33.10 Learning from past migration problems
Lesson 34: Optimizing the Migration Factory for Performance
34.1 Identifying bottlenecks in the migration pipeline
34.2 Streamlining factory processes for efficiency
34.3 Optimizing resource allocation within the factory
34.4 Implementing parallel migration strategies
34.5 Utilizing automation to accelerate throughput
34.6 Continuous monitoring of factory performance metrics
34.7 Implementing feedback loops for continuous improvement
34.8 Benchmarking factory performance against industry standards
34.9 Identifying and addressing technical debt within the factory
34.10 Scaling the factory for increased demand
Lesson 35: Measuring and Reporting Business Value
35.1 Defining key performance indicators (KPIs) for migration success and business value
35.2 Establishing baseline metrics before migration
35.3 Tracking and reporting on cost savings and ROI
35.4 Measuring improvements in agility and time to market
35.5 Quantifying the impact on business continuity and disaster recovery
35.6 Reporting on security and compliance posture improvements
35.7 Communicating business value to stakeholders
35.8 Utilizing dashboards and reporting tools
35.9 Conducting post-migration business value assessments
35.10 Continually demonstrating the value of the migration factory
Lesson 36: Future Trends in Cloud Migration
36.1 Emerging cloud migration methodologies and strategies
36.2 The impact of edge computing on migration
36.3 Serverless and container adoption trends
36.4 The role of AI and machine learning in future migrations
36.5 Sustainability considerations in cloud migration
36.6 Evolutions in hybrid and multi-cloud environments
36.7 The impact of regulatory changes on cloud migration
36.8 New tools and technologies for migration
36.9 The evolving role of the migration factory
36.10 Preparing for the future of cloud migration
Lesson 37: Case Studies and Real-World Examples
37.1 Analyzing successful large-scale IBM Cloud migration factory deployments
37.2 Examining migration case studies from various industries
37.3 Learning from challenging migration projects and how they were overcome
37.4 Analyzing the approaches taken for different workload types
37.5 Understanding the organizational impact of real-world migrations
37.6 Evaluating the tools and technologies used in case studies
37.7 Analyzing the business outcomes achieved in real-world scenarios
37.8 Discussions on lessons learned from actual factory operations
37.9 Comparing different factory models and their effectiveness
37.10 Expert insights and perspectives from real-world practitioners
Lesson 38: Accreditation and Certification Preparation
38.1 Overview of IBM Cloud Migration Factory accreditation requirements
38.2 Recommended study materials and resources
38.3 Practice exams and assessment strategies
38.4 Tips and techniques for exam preparation
38.5 Understanding the exam format and question types
38.6 Review of key concepts and topics covered in the accreditation
38.7 Strategies for demonstrating expert-level knowledge
38.8 Q&A with accredited professionals (simulated or actual)
38.9 Building a personal development plan for continuous learning
38.10 Maintaining accreditation and staying current
Lesson 39: Advanced Topics and Emerging Practices
39.1 Exploring cutting-edge techniques in cloud migration
39.2 Deep dive into specific advanced IBM Cloud services for migration
39.3 Researching and evaluating new migration tools and technologies
39.4 Participating in cloud migration communities and forums
39.5 Contributing to best practices and knowledge sharing
39.6 Exploring the role of blockchain in cloud migration (potential use cases)
39.7 The impact of quantum computing on future migration strategies (theoretical)
39.8 Advanced security threats and mitigation strategies in the cloud
39.9 The evolving landscape of cloud governance and compliance
39.10 Preparing for unforeseen challenges in large-scale migrations
Lesson 40: Course Capstone: Designing Your IBM Cloud Migration Factory
40.1 Applying course concepts to design a tailored migration factory
40.2 Developing a comprehensive factory blueprint
40.3 Defining the factory's governance model, methodologies, and processes
40.4 Selecting appropriate tools and automation strategies
40.5 Planning for people, skills, and organizational change
40.6 Developing a detailed migration plan for a complex scenario
40.7 Incorporating advanced security, GRC, and FinOps considerations
40.8 Presenting and defending the factory design
40.9 Peer review and feedback on factory designs