This book is a must-read, providing insights into SRE principles for beginners and experienced professionals. Study the fundamentals and evolution of SRE, gaining a solid foundation for success in today's tech-centric world. Starting with the fundamentals, it expands into the evolution of SRE from traditional IT roles, laying a solid foundation for understanding its pivotal role in today’s tech-driven world. The core of the book focuses on practical strategies and advanced techniques. Readers will learn about automating tasks, effective incident management, setting realistic service level objectives, and managing error budgets. These topics are crucial for maintaining system reliability while fostering innovation. Additionally, the book emphasizes performance optimization and scalability, ensuring that systems run smoothly and adapt and grow effectively. High performance SRE emphasizes more than just technical skills. It encourages teamwork, a blame-free culture, and continuous learning, empowering SRE professionals for operational excellence and organizational success.

• Cover
• Title Page
• Copyright Page
• Dedication Page
• About the Author
• About the Reviewer
• Acknowledgement
• Preface
• Table of Contents
• 1. Introduction to Site Reliability Engineer
  • Introduction
  • Structure
  • Objectives
  • Historical context and origin of the SRE role
  • Type of DevOps teams in different companies
  • Roles and responsibilities of SRE
  • Bridging the gap between development and operations
    • Maintaining system and service reliability
  • Importance of SRE in the modern tech ecosystem
  • Skills and knowledge for SRE
    • Necessary technical skills
    • Soft skill requirements
  • Culture of SREs and DevOps
    • Understanding DevOps
    • SRE’s role in promoting the DevOps culture
    • Effect on the process of making and delivering software
  • Importance of SRE in the digital age
    • Effect of service downtime on businesses
    • SRE’s role in reducing and preventing downtime
    • Prospects and developments for SREs in the future
  • Career path and professional development
    • Starting point and prerequisites for becoming an SRE
    • Continuous learning and upskilling
    • Career progression for SREs
    • Evolving SRE role
  • Conclusion
  • Multiple choice questions
    • Answers
• 2. DevOps to Site Reliability Engineering
  • Introduction
  • Structure
  • Objectives
  • DevOps to site reliability engineering
  • Need for site reliability engineering
    • Site reliability engineering team structure
    • Site reliability engineering discipline
    • Unspoken commitments
  • Site reliability engineering engagement model
    • Site reliability engineering implements DevOps
  • Site reliability engineering strategy adoption
  • Site reliability engineering challenges
  • Site reliability engineering best practices
  • Site reliability engineering best practices tools
  • Conclusion
  • Multiple choice questions
    • Answers
• 3. Monitoring
  • Introduction
  • Structure
  • Objectives
  • Need for monitoring
  • Pillars of monitoring
    • Latency
    • Errors
    • Saturation
  • Threshold monitoring
  • Monitoring and observability
  • Application monitoring
  • Monitoring best practices
    • Examples of monitoring and observability tools
  • Conclusion
  • Multiple choice questions
    • Answers
• 4. Incident Management and Risk Mitigation
  • Introduction
  • Structure
  • Objectives
  • Purpose of incident management
    • More about software risks
  • Incident prioritization
  • Incident severity level
    • Use of severity level
    • Difference between severity and priority
    • Defining incident severity levels
  • Incident response planning
  • Risks to consider
  • Analyzing the risks
    • Production incident lifecycle
      • Cost of reliability
      • Response plan
  • Best practices to reduce production incidents
  • Risk and mitigation
  • Best practices for risk mitigation
  • Conclusion
  • Multiple choice questions
    • Answers
• 5. Error Budgets
  • Introduction
  • Structure
  • Objectives
  • Purpose of error budgets
  • Defining error budgets
    • Error budget equation
    • Prioritizing development over end-user experience
  • Relation of error budgets with SLI and SLO
  • Benefits to setting the proper error budgets
  • Outage policies
  • Action items if the error budget is exceeded
  • Best practices to get the correct error budgets
  • Conclusion
  • Multiple choice questions
    • Answers
• 6. SLI/SLO/SLA
  • Introduction
  • Structure
  • Objectives
  • Introduction to service level management
    • Overview of service level management
    • Key components of SLM: SLI, SLO, and SLA
    • Benefits of implementing an SLM program
  • Understanding service level indicators
    • Purpose of SLIs
    • Types of SLIs and their use cases
    • Key features of selecting appropriate SLI
    • Importance of SLIs
  • Setting service level objectives
    • Purpose of SLOs
    • Setting up appropriate SLOs
  • Creating service level agreements
    • Purpose of SLAs
    • Components of SLA
    • Negotiations of SLA
  • Implementing and managing the SLM program
    • Steps for implementing the SLM program
    • Best practices for managing SLIs, SLOs, and SLAs
    • Common challenges in setting up correct SLA
    • Role of technology in automating SLM
  • Case studies and real-world examples
    • Netflix
    • Adobe
    • LinkedIn
  • Conclusion
  • Multiple choice questions
    • Answers
• 7. Capacity Planning
  • Introduction
  • Structure
  • Objectives
  • Importance of capacity planning
    • Principles of capacity management
  • Understanding resource requirements
    • Identifying key resources
    • Analyzing historical usage data
    • Forecasting future usage patterns
  • Capacity analysis
    • Capacity analysis to determine workload resources
    • Trade-offs between performance, availability, and cost
  • Scaling strategies
    • Choosing the right scaling strategy
    • Considerations for auto-scaling and load balancing
  • Monitoring and alerting
    • Setting up monitoring tools
    • Defining alerting thresholds for key metrics
    • Strategies for proactive capacity planning
  • Capacity planning in the cloud
    • Understanding cloud resource allocation
    • Leveraging cloud provider tools
  • Capacity planning for disaster recovery
    • Disaster recovery capacity needs
    • Developing disaster recovery capacity plans
    • Disaster recovery plans and capacity
  • Conclusion
  • Multiple choice questions
    • Answers
• 8. On-call and First-response
  • Introduction
  • Structure
  • Objectives
  • Understanding on-call
    • Types of on-call rotations
    • Key responsibilities of on-call engineers
  • First response processes
    • Common steps in first response processes
    • Best practices for first response
    • Preparing for on-call and first-response
    • Importance of proactive preparation
    • Key tools and resources for on-call engineers
    • Strategies for reducing stress and avoiding burnout
  • Communicating during incidents
    • Importance of effective communication
    • Best practices for communicating with stakeholders
    • Tools for effective incident communication
  • Incident review and post-mortems
    • Incidents and post-mortems
    • Common post-mortem processes and best practices
    • Preventing incidents with post-mortems
  • Case studies
    • Google
    • Amazon
    • Atlassian
    • Netflix
  • Conclusion
  • Multiple choice questions
    • Answers
• 9. RCA and Post-mortem
  • Introduction
  • Structure
  • Objectives
  • Root cause analysis
    • Understanding the RCA process
      • Problem identification
      • Data collection
      • Root cause identification
      • Implementing solutions
      • Reviewing the efficiency of the solutions
    • Various methods of RCA
      • The five whys
      • Fishbone/Ishikawa diagrams
      • Fault tree analysis
    • Role of RCA in problem-solving and actions
  • Post-mortem
    • How to conduct a post-mortem
      • Gathering data and information
      • Analyzing the incident
      • Identifying actions for improvement
      • Implementing changes
    • Role of a blameless post-mortem
    • Role of post-mortem in learning and improvement
    • Real-world examples of effective post-mortems
    • Challenges and pitfalls in conducting post-mortems
  • Relationship between RCA and post-mortem
    • RCA feeds into the post-mortem process
    • RCA and post-mortem: Synergies and differences
    • Optimizing incident management
  • Future trends
    • Applying AI and ML to RCA and post mortem
    • Post-mortem best practices
  • Conclusion
  • Multiple choice questions
    • Answers
• 10. Chaos Engineering
  • Introduction
  • Structure
  • Objectives
  • Principles of chaos engineering
    • Building a hypothesis
    • Introducing real-world events
    • Observing the system
    • Verifying the hypothesis
    • Incremental complexity
  • Role of chaos engineering in SRE
  • Key concepts in chaos engineering
    • Blast radius
    • Failure injection
    • Steady-state
    • Observability and monitoring
    • Chaos experiments
    • Game days
  • Preparing for chaos engineering
    • Setting objectives and metrics
    • Building an observability infrastructure
    • Establishing a strong incident response strategy
  • Implementing chaos testing
  • Tools and technologies for chaos engineering
    • Chaos toolkit
    • Gremlin
    • Chaos Monkey
  • Case studies on chaos engineering
    • Netflix
    • Amazon
    • Google
  • Future of chaos engineering
  • Conclusion
  • Multiple choice questions
    • Answers
• 11. Artificial Intelligence for Site Reliability Engineering
  • Introduction
  • Structure
  • Objectives
  • Role of AI in transforming SRE processes
  • Automated testing and quality assurance
    • Role of AI in test case generation and automation
    • Role of AI in testing
  • Intelligent debugging
    • AI techniques for code analysis and issue identification
    • Real-time insights and suggestions for issue resolution
    • Impact of intelligent debugging on system stability
  • Predictive maintenance
    • AI for maintenance and upgrades
    • Predicting potential failures and resource depletion
    • Predictive maintenance and resource optimization
  • Code generation and augmentation
    • Code snippets and faster development
    • AI-assisted code review for improved code quality
    • Enhanced development and coding practices
  • Performance optimization
    • Monitoring and analysis
    • Bottleneck detection and root cause analysis
    • Automated performance tuning
    • Predictive and adaptive scaling
    • User experience optimization
  • Anomaly detection and security
    • AI for anomaly detection
    • Leveraging AI to prevent security threats
    • Enhancing system security and maintaining data
  • Continuous integration and deployment
    • Automation of CI/CD processes using AI
    • AI-driven code analysis and release management
    • Software delivery and development
  • Natural language processing for SRE
    • Role of NLP in processing requirements
    • Tools for requirement analysis
    • Sentiment analysis and user feedback
  • Future trends and challenges
    • Potential challenges and ethical considerations
    • Future of AI in SRE
  • Conclusion
    • Multiple choice questions
    • Answers
• 12. Case Studies
  • Introduction
  • Structure
  • Objectives
  • Google
    • Background and difficulties
      • Google’s software reliability engineering model
  • Netflix
    • Background and difficulties
      • Netflix’s software reliability engineering methodology
      • Core ideas of Netflix’s SRE strategy
  • Spotify
    • Background and difficulties
      • Spotify’s software reliability engineering approach
  • LinkedIn
    • Background and difficulties
      • Journey of LinkedIn’s software reliability engineering
  • Amazon
    • Background and challenges
      • SRE at Amazon
  • Conclusion
• Index