Lesson 1: Advanced DevOps Principles and Culture at Scale
1.1. Deep Dive into DevOps Evolution and Modern Trends
1.2. Fostering a Culture of Blamelessness and Continuous Improvement
1.3. Implementing InnerSource and Open Collaboration Practices
1.4. Leading Organizational Change for DevOps Adoption
1.5. Measuring DevOps Maturity and Performance
1.6. Building High-Performing, Cross-Functional Teams
1.7. Advanced Value Stream Mapping for Optimized Flow
1.8.chaos Engineering and Resilience Building Culture
1.9. Knowledge Sharing and Documentation Best Practices
1.10. Community Building and Advocacy for DevOps Principles
Lesson 2: Expert-Level Git and Trunk-Based Development
2.1. Advanced Git Workflows (e.g., Monorepos, Microrepos)
2.2. strategies for Large-Scale Git Repository Management
2.3. Implementing and Enforcing Branching Policies
2.4. Advanced Rebasing and Patching Techniques
2.5. Git Hooks for Automation and Policy Enforcement
2.6. Resolving Complex Merge Conflicts at Scale
2.7. cherry-picking and Patch Management Strategies
2.8. Git Performance Optimization for Large Repositories
2.9. Integrating Git with Advanced CI/CD Pipelines
2.10. Auditing and Security Best Practices for Git
Lesson 3: Mastering CI/CD Pipelines with IBM Technologies
3.1. Designing and Implementing Advanced CI/CD Architectures
3.2. Orchestrating Complex Multi-Stage Pipelines
3.3. integrating IBM UrbanCode Deploy for Application Deployments
3.4. Utilizing Tekton for Kubernetes-Native Pipelines on IBM Cloud
3.5. Advanced Jenkins Pipeline as Code with Shared Libraries
3.6. Implementing Pipeline Security and Hardening
3.7. Optimizing Pipeline Performance and Feedback Loops
3.8. canary Deployments and Blue/Green Deployments with Automation
3.9. Feature Flag Management and Progressive Delivery
3.10. Pipeline Monitoring, Analytics, and Troubleshooting
Lesson 4: Advanced Infrastructure as Code (IaC) with Terraform and Ansible
4.1. Designing Modular and Reusable Terraform Modules
4.2. Advanced Terraform State Management and Collaboration
4.3. Implementing Sentinel Policies for Terraform
4.4. Writing Idempotent and Efficient Ansible Playbooks
4.5. Ansible Roles and Collections for Large-Scale Configuration Management
4.6. Integrating Terraform and Ansible in CI/CD Pipelines
4.7. Managing Secrets and Sensitive Data in IaC
4.8. Testing Strategies for Infrastructure Code
4.9. Cloud Agnostic IaC Patterns
4.10. Cost Optimization through IaC
Lesson 5: Containerization and Orchestration with Kubernetes and OpenShift (IBM Cloud)
5.1. Advanced Kubernetes Architecture and Concepts
5.2. Deploying and Managing Applications on IBM Cloud Kubernetes Service (IKS)
5.3. Leveraging Red Hat OpenShift on IBM Cloud for Enterprise Workloads
5.4. Kubernetes Networking and Service Mesh (e.g., Istio)
5.5. Kubernetes Security Best Practices and Network Policies
5.6. Stateful Applications in Kubernetes
5.7. Kubernetes Storage Options and Persistent Volumes on IBM Cloud
5.8. Custom Resource Definitions (CRDs) and Operators
5.9. Troubleshooting and Debugging Kubernetes Applications
5.10. Kubernetes Cost Management and Optimization
Lesson 6: Expert-Level DevSecOps Practices in IBM Cloud
6.1. Shifting Security Left in the DevOps Pipeline
6.2. Integrating Security Scanning Tools (SAST, DAST, SCA)
6.3. implementing Secrets Management Solutions (e.g., HashiCorp Vault, IBM Key Protect)
6.4. Infrastructure Security Scanning and Compliance
6.5. Container Image Security and Vulnerability Scanning
6.6. Runtime Security Monitoring and Threat Detection
6.7. security Incident Response in a DevOps Context
6.8. Compliance and Governance in DevSecOps
6.9. Automated Security Testing in CI/CD
6.10. Building a Security Culture within DevOps Teams
Lesson 7: Site Reliability Engineering (SRE) Principles and Implementation (IBM Focus)
7.1. Introduction to SRE and its Relationship with DevOps
7.2. Defining and Measuring Service Level Objectives (SLOs) and Service Level Indicators (SLIs)
7.3. Error Budgets and their Application
7.4. Implementing Effective Monitoring and Alerting Strategies
7.5. Distributed Tracing and Observability
7.6. incident Response and Postmortem Analysis
7.7. Capacity Planning and Performance Optimization
7.8. Chaos Engineering for System Resilience
7.9. Automation for Toil Reduction
7.10. SRE in the Context of IBM Cloud Services
Lesson 8: Advanced Monitoring, Logging, and Alerting in IBM Cloud
8.1. Designing a Comprehensive Monitoring Strategy
8.2. Implementing Centralized Logging with the ELK Stack or IBM Log Analysis
8.3. Utilizing IBM Cloud Monitoring with Sysdig for Container Monitoring
8.4. Setting up Advanced Alerting and Notification Systems
8.5. Application Performance Monitoring (APM) with IBM Instana
8.6. log Analysis for Root Cause Analysis and Troubleshooting
8.7. Creating Custom Dashboards and Visualizations
8.8. Proactive Anomaly Detection
8.9. Integrating Monitoring and Alerting with Incident Management
8.10. Cost Optimization of Monitoring and Logging Solutions
Lesson 9: GitOps: Declarative Infrastructure and Application Management
9.1. Understanding the Core Principles of GitOps
9.2. Implementing GitOps with Argo CD or Flux CD on Kubernetes
9.3. Managing Infrastructure Configuration with GitOps
9.4. Automated Application Deployment with GitOps
9.5. GitOps for Multi-Cluster Management
9.6. GitOps Security Considerations and Best Practices
9.7. Integrating GitOps with CI/CD Pipelines
9.8. Rollback Strategies with GitOps
9.9. Monitoring and Observability in a GitOps Environment
9.10. Adopting GitOps in an Enterprise Setting
Lesson 10: FinOps: Cloud Financial Management in DevOps
10.1. Introduction to FinOps and its Principles
10.2. Cloud Cost Monitoring and Allocation on IBM Cloud
10.3. Cost Optimization Strategies for Cloud Resources
10.4. Rightsizing and autoscaling for Cost Efficiency
10.5. Reserved Instances and Savings Plans on IBM Cloud
10.6. showback and Chargeback Mechanisms
10.7. Anomaly Detection in Cloud Spending
10.8. Integrating FinOps into the CI/CD Pipeline
10.9. Building a Cost-Aware Culture in DevOps Teams
10.10. Utilizing IBM Cloud Cost Management Tools
Lesson 11: Advanced Release Management and Orchestration with IBM UrbanCode Release
11.1. Designing Complex Release Trains and Calendars
11.2. Orchestrating Deployments Across Multiple Environments
11.3. Integrating UrbanCode Release with CI/CD Tools
11.4. Managing Dependencies Between Applications and Services
11.5. Implementing Gates and Approvals in the Release Process
11.6. Automated Rollbacks and Disaster Recovery Planning
11.7. Release Dashboarding and Reporting
11.8. Customizing UrbanCode Release Workflows and Plugins
11.9. User and Permission Management in UrbanCode Release
11.10. Scaling UrbanCode Release for Enterprise Needs
Lesson 12: Automated Testing Strategies for Expert DevOps
12.1. Advanced Unit Testing Techniques and Frameworks
12.2. Integration Testing in Complex Distributed Systems
12.3. contract Testing for Microservices
12.4. End-to-End Testing Automation
12.5. Performance Testing and Load Testing
12.6. Security Testing Automation (SAST, DAST)
12.7. Test Data Management Strategies
12.8. Testing in Production and Chaos Testing
12.9. Utilizing IBM Rational Test Workbench for Comprehensive Testing
12.10. Test Reporting and Analytics
Lesson 13: Managing Technical Debt in a DevOps Environment
13.1. Identifying and Quantifying Technical Debt
13.2. Strategies for Prioritizing and Addressing Technical Debt
13.3. Integrating Technical Debt Management into the Development Workflow
13.4. Automating Technical Debt Detection
13.5. Refactoring Techniques and Best Practices
13.6. Measuring the Impact of Technical Debt
13.7. Communication and Collaboration Around Technical Debt
13.8. Preventing the Accumulation of New Technical Debt
13.9. Tools and Techniques for Managing Technical Debt
13.10. The Role of DevOps in Reducing Technical Debt
Lesson 14: Advanced Cloud-Native Development Patterns
14.1. Microservices Architecture Design and Best Practices
14.2. Twelve-Factor App Principles in Detail
14.3. Serverless Computing with IBM Cloud Functions
14.4. Event-Driven Architectures
14.5. API Gateway Management and Security
14.6. Designing for Resilience and Fault Tolerance
14.7. Implementing Circuit Breakers and Bulkheads
14.8. Saga Pattern for Distributed Transactions
14.9. Observability in Cloud-Native Applications
14.10. Migration Strategies to Cloud-Native
Lesson 15: AI and Machine Learning in DevOps (AIOps)
15.1. Introduction to AIOps and its Applications
15.2. Utilizing AI for Anomaly Detection in Monitoring Data
15.3. Predicting and Preventing System Outages with ML
15.4. Automated Root Cause Analysis with AI
15.5. Intelligent Alerting and Noise Reduction
15.6. AI-Powered Capacity Planning
15.7. Chatbots and Conversational AI for DevOps Support
15.8. Machine Learning for Optimizing Release Cycles
15.9. Implementing AIOps Solutions on IBM Cloud
15.10. Ethical Considerations in AIOps
Lesson 16: Disaster Recovery and Business Continuity in DevOps
16.1. Designing a Comprehensive DR Strategy
16.2. Implementing Active-Passive and Active-Active DR Solutions
16.3. Automated DR Drills and Testing
16.4. Backup and Restore Strategies for Cloud-Native Applications
16.5. Data Replication and Consistency
16.6. Defining Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO)
16.7. DR in a Multi-Cloud or Hybrid Cloud Environment
16.8. Utilizing IBM Cloud Services for DR
16.9. Communication and Coordination During a DR Event
16.10. Post-Disaster Recovery Analysis and Improvement
Lesson 17: Advanced Network Management for DevOps
17.1. Software-Defined Networking (SDN) Concepts
17.2. Network Automation with Ansible and Terraform
17.3. Load Balancing Strategies and Implementation
17.4. DNS Management and Optimization
17.5. Content Delivery Networks (CDNs)
17.6. Network Security Groups and Access Control Lists
17.7. VPNs and Secure Connectivity to Cloud Resources
17.8. Network Monitoring and Troubleshooting
17.9. Infrastructure as Code for Network Configuration
17.10. Network Performance Optimization
Lesson 18: Database DevOps and Data Management
18.1. Database Schema Versioning and Migration
18.2. Automated Database Deployment and Configuration
18.3. Database Performance Monitoring and Tuning
18.4. Database Backup and Restore Automation
18.5. Data Masking and Security in Non-Production Environments
18.6. Managing Databases in a Cloud-Native Architecture
18.7. Database as a Service (DBaaS) on IBM Cloud
18.8. Data Replication and Synchronization
18.9. Database Observability and Logging
18.10. Compliance and Governance for Database Changes
Lesson 19: Edge Computing and IoT DevOps
19.1. DevOps Challenges in Edge Computing Environments
19.2. Deploying and Managing Applications at the Edge
19.3. CI/CD Pipelines for Edge Devices
19.4. Monitoring and Managing Edge Infrastructure
19.5. Security Considerations for Edge DevOps
19.6. Data Synchronization and Management at the Edge
19.7. Utilizing IBM Edge Application Manager
19.8. Over-the-Air (OTA) Updates for Edge Devices
19.9. Testing Strategies for Edge Applications
19.10. Scaling DevOps for Large-Scale Edge Deployments
Lesson 20: Mainframe DevOps Integration
20.1. Understanding the Challenges of Mainframe Integration in DevOps
20.2. Tools and Techniques for Mainframe Source Code Management
20.3. Automated Mainframe Builds and Compiles
20.4. Integrating Mainframe Testing into the CI/CD Pipeline
20.5. Automated Mainframe Deployments
20.6. Monitoring and Managing Mainframe Applications in a DevOps Context
20.7. Utilizing IBM Z DevOps Solutions
20.8. data Virtualization for Mainframe Testing
20.9. Security Considerations for Mainframe DevOps
20.10. Cultural Challenges and Collaboration Between Mainframe and Distributed Teams
Lesson 21: Quantum Computing and its Potential Impact on DevOps
21.1. Introduction to Quantum Computing Concepts
21.2. Potential Applications of Quantum Computing in Software Development
21.3. DevOps Considerations for Quantum Software Development
21.4. Quantum Software Development Kits (SDKs) and Tools (e.g., Qiskit)
21.5. Building and Testing Quantum Programs
21.6. Deploying Quantum Applications
21.7. Monitoring and Managing Quantum Resources
21.8. Security in Quantum Computing
21.9. The Future of DevOps in a Quantum World
21.10. Getting Started with Quantum Computing on IBM Cloud
Lesson 22: Blockchain and Distributed Ledger Technology in DevOps
22.1. Introduction to Blockchain and DLT Concepts
22.2. DevOps for Blockchain Networks
22.3. Smart Contract Development and Testing
22.4. Deploying and Managing Blockchain Applications
22.5. Monitoring and Managing Blockchain Nodes
22.6. Security Considerations for Blockchain DevOps
22.7. Utilizing IBM Blockchain Platform
22.8. CI/CD Pipelines for Blockchain Solutions
22.9. Governance and Compliance in Blockchain DevOps
22.10. Use Cases for Blockchain in DevOps
Lesson 23: Advanced Security Practices for the DevOps Pipeline
23.1. Supply Chain Security in DevOps
23.2. Code Signing and Verification
23.3. Implementing a Secure Software Factory
23.4. Automated Security Policy Enforcement
23.5. Threat Modeling for DevOps Pipelines
23.6. Security Auditing and Compliance Automation
23.7. Managing Security Certificates and Keys
23.8. Incident Response for Pipeline Compromises
23.9. Security Awareness and Training for DevOps Teams
23.10. Emerging Security Threats in DevOps
Lesson 24: Chaos Engineering: Principled Introduction of Failure
24.1. Understanding the Principles of Chaos Engineering
24.2. Designing Chaos Experiments
24.3. Setting up a Safe and Controlled Chaos Environment
24.4. Tools for Chaos Engineering (e.g., Chaos Monkey, Gremlin)
24.5. Analyzing the Results of Chaos Experiments
24.6. Automating Chaos Experiments in the Pipeline
24.7. Integrating Chaos Engineering with Monitoring and Alerting
24.8. Building a Culture of Resilience Through Chaos Engineering
24.9. Chaos Engineering for IBM Cloud Services
24.10. Advanced Chaos Engineering Techniques
Lesson 25: Advanced Performance Engineering in DevOps
25.1. Performance Testing in the CI/CD Pipeline
25.2. Identifying and Resolving Performance Bottlenecks
25.3. Application Profiling and Tracing
25.4. Database Performance Optimization
25.5. Infrastructure Performance Tuning
25.6. Performance Monitoring and Alerting
25.7. Utilizing APM Tools (e.g., IBM Instana) for Performance Analysis
25.8. Capacity Planning Based on Performance Metrics
25.9. Automated Performance Regression Detection
25.10. Continuous Performance Optimization
Lesson 26: Technical Leadership and Mentoring in DevOps
26.1. Leading DevOps Transformations
26.2. Mentoring and Coaching DevOps Teams
26.3. Building a Learning Organization
26.4. Facilitating Collaboration and Communication
26.5. Resolving Conflicts in a DevOps Environment
26.6. Empowering Teams and Individuals
26.7. Driving Innovation and Adoption of New Technologies
26.8. Presenting and Communicating DevOps Concepts to Stakeholders
26.9. Building a Personal Brand as a DevOps Expert
26.10. Continuing Education and Staying Current in DevOps
Lesson 27: DevOps for Data Science and Machine Learning Pipelines
27.1. Understanding the Unique Challenges of MLOps
27.2. Versioning and Managing Machine Learning Models
27.3. CI/CD for Machine Learning Pipelines
27.4. Deploying and Serving Machine Learning Models
27.5. Monitoring and Managing ML Model Performance
27.6. Data Versioning and Management for ML
27.7. Utilizing IBM Watson Studio and Cloud Pak for Data
27.8. Automated Model Retraining and Deployment
27.9. Ethical Considerations in MLOps
27.10. Building an MLOps Platform
Lesson 28: Advanced Cloud Cost Management with IBM Cloud
28.1. Deep Dive into IBM Cloud Billing and Cost Structures
28.2. Advanced Cost Allocation and Tagging Strategies
28.3. Utilizing IBM Cloud Cost Management Tools and Dashboards
28.4. Identifying and Optimizing Underutilized Resources
28.5. Negotiating and Managing Enterprise Cloud Agreements
28.6. Forecasting Cloud Spending
28.7. Anomaly Detection and Alerting for Cost Spikes
28.8. Implementing Cost Governance Policies
28.9. automation for Cost Optimization Actions
28.10. Reporting and Communicating Cloud Costs to Stakeholders
Lesson 29: Implementing and Managing an Internal Developer Platform (IDP)
29.1. Understanding the Concept and Benefits of an IDP
29.2. Designing and Architecting an IDP
29.3. Components of an IDP (e.g., Self-Service Portals, Golden Paths)
29.4. Integrating IDP with Existing DevOps Tools
29.5. Building and Maintaining Developer Workflows
29.6. Measuring the Success of an IDP
29.7. User Experience and Adoption of the IDP
29.8. Security Considerations for an IDP
29.9. Case Studies of Successful IDP Implementations
29.10. The Future of Developer Productivity and IDPs
Lesson 30: DevOps for Enterprise Resource Planning (ERP) Systems
30.1. Challenges of Applying DevOps to ERP Systems
30.2. Strategies for Versioning and Managing ERP Configurations
30.3. Automated Testing for ERP Customizations and Upgrades
30.4. CI/CD Pipelines for ERP Deployments
30.5. Managing Complex Dependencies in ERP Releases
30.6. Monitoring and Managing ERP System Performance
30.7. Utilizing IBM Solutions for ERP DevOps
30.8. Data Management and Masking for ERP Testing
30.9. Security and Compliance for ERP DevOps
30.10. Overcoming Organizational Silos for ERP DevOps
Lesson 31: Advanced API Management and DevOps
31.1. Designing and Versioning APIs
31.2. API Gateway Implementation and Management (e.g., IBM API Connect)
31.3. Automated API Testing (Functional, Performance, Security)
31.4. CI/CD Pipelines for API Deployment
31.5. API Monitoring and Analytics
31.6. API Security Best Practices
31.7. Developer Portals and API Documentation
31.8. API Monetization Strategies
31.9. Governing API Usage and Access
31.10. The Role of APIs in Microservices Architectures
Lesson 32: ChatOps: Conversational Driven Development and Operations
32.1. Introduction to ChatOps and its Benefits
32.2. Integrating Chat Platforms with DevOps Tools
32.3. Building ChatOps Bots and Commands
32.4. Automating Workflows Through Chat
32.5. Utilizing ChatOps for Incident Response
32.6. Monitoring and Alerting Through Chat
32.7. Security Considerations for ChatOps
32.8. Implementing ChatOps in an Enterprise
32.9. Measuring the Impact of ChatOps
32.10. The Future of Conversational Interfaces in DevOps
Lesson 33: Advanced Concepts in Cloud Security Posture Management (CSPM)
33.1. Understanding CSPM and its Importance
33.2. Automated Security Configuration Scanning
33.3. Identifying and Remediating Cloud Misconfigurations
33.4. Compliance Monitoring and Reporting
33.5. Integrating CSPM with CI/CD Pipelines
33.6. Utilizing IBM Cloud Security Advisor and Security and Compliance Center
33.7. Threat Detection and Response Based on CSPM Findings
33.8. Governing Cloud Resource Provisioning
33.9. Implementing Security Guardrails
33.10. Continuous Cloud Security Improvement
Lesson 34: Observability Beyond Monitoring
34.1. Differentiating Monitoring and Observability
34.2. The Three Pillars of Observability (Metrics, Logs, Traces)
34.3. Implementing Distributed Tracing (e.g., Jaeger, Zipkin)
34.4. Structured Logging and Contextualization
34.5. Utilizing OpenTelemetry for Vendor-Neutral Observability
34.6. Analyzing Observability Data for Insights
34.7. Building Observable Applications
34.8. Troubleshooting Complex Systems with Observability
39.9. Observability for Serverless and Containerized Applications
34.10. The Future of Observability
Lesson 35: Advanced topics in Configuration Management Databases (CMDB) for DevOps
35.1. The Role of CMDB in a DevOps Landscape
35.2. Automated CMDB Updates and Synchronization
35.3. Integrating CMDB with IaC and CI/CD Tools
35.4. Utilizing CMDB for Impact Analysis and Change Management
35.5. CMDB for Incident Management and Root Cause Analysis
35.6. Data Quality and Governance in the CMDB
35.7. Discovery and Mapping of Application Dependencies
35.8. CMDB for Security and Compliance
35.9. Selecting and Implementing a CMDB Solution
35.10. The Evolution of CMDB in a Cloud-Native World
Lesson 36: Implementing a Service Catalog and Self-Service Portals
36.1. Understanding the Benefits of a Service Catalog
36.2. Designing and Building a Service Catalog
36.3. Implementing Self-Service Provisioning Workflows
36.4. Integrating the Service Catalog with IaC and Orchestration Tools
36.5. Governance and Approval Workflows for Service Requests
36.6. Measuring the Usage and Value of the Service Catalog
36.7. User Experience and Adoption of Self-Service Portals
36.8. Security Considerations for Self-Service
36.9. Automating the Onboarding of New Services
36.10. Case Studies of Successful Service Catalog Implementations
Lesson 37: DevOps for Hybrid Cloud and Multi-Cloud Environments
37.1. Challenges of DevOps in Hybrid and Multi-Cloud
37.2. Designing Architectures for Hybrid and Multi-Cloud
37.3. CI/CD Pipelines for Deployments Across Clouds
37.4. managing Configuration Across Diverse Environments
37.5. Network Connectivity and Security in Hybrid/Multi-Cloud
37.6. Monitoring and Observability in Distributed Environments
37.7. Data Management and Synchronization Across Clouds
37.8. Cost Management in Multi-Cloud Setups
37.9. Utilizing IBM Cloud Satellite for Extending IBM Cloud
37.10. Strategies for Cloud Vendor Lock-in Avoidance
Lesson 38: Advanced Techniques for Legacy Application Modernization with DevOps
38.1. Assessing Legacy Applications for Modernization
38.2. Strangler Fig Pattern and Other Modernization Strategies
38.3. Containerizing Legacy Applications
38.4. Re-platforming and Re-architecting Legacy Systems
38.5. Data Migration Strategies for Modernization
38.6. Automated Testing for Legacy Applications
38.7. CI/CD Pipelines for Modernized Applications
38.8. Managing Technical Debt During Modernization
38.9. Utilizing IBM Tools and Services for Modernization
38.10. Post-Modernization Monitoring and Optimization
Lesson 39: The Future of DevOps: Trends and Emerging Technologies
39.1. serverless 2.0 and Beyond
39.2. The Impact of AI on DevOps Practices
39.3. GitOps Evolution and Advanced Patterns
39.4. DevSecOps Beyond the Basics
39.5. The Rise of Platform Engineering
39.6. Sustainability in DevOps (Green IT)
39.7. The Role of WebAssembly in Cloud-Native
39.8. Quantum Computing’s Potential Influence
39.9. The Evolving Landscape of DevOps Tools
39.10. Preparing for the Next Wave of DevOps Innovation
Lesson 40: Expert-Level DevOps Capstone Project and Certification Preparation
40.1. Project Overview and Requirements Analysis
40.2. Designing a Comprehensive DevOps Solution for a Complex Scenario
40.3. Implementing Advanced CI/CD Pipelines
40.4. Deploying and Managing Applications on IBM Cloud
40.5. Implementing Advanced Monitoring, Logging, and Alerting
40.6. Integrating Security into the Solution
40.7. Applying SRE Principles to the Project
40.8. Optimizing for Cost and Performance
40.9. Troubleshooting and Debugging the Solution
40.10. Preparing for the IBM Advanced DevOps Certification Exam (Expert Level)
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