Distributed Reliability: SRE Critical State Management

SRE    |    Intermediate
  • 14 Videos | 1h 19m 47s
  • Includes Assessment
  • Earns a Badge
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Anticipating failures that will affect your company's systems is a crucial site reliability engineer duty. These failures are especially significant when they affect distributed systems, which is why efficient algorithms and strategies are essential in minimizing the likelihood of failures. In this course, you'll explore both critical state management and the CAP theorem, identifying how both concepts relate to distributed systems. Next, you'll examine several distributed system management algorithms and strategies, including deterministic and nondeterministic algorithms, distributed system models, and Byzantine faults. You'll then outline how each of these benefits distributed system management. Finally, you'll investigate the Multi-Paxos message flow protocol and how it works with distributed systems. Finally, you'll describe what's involved in deploying and monitoring a consensus-based system to increase distributed system performance.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe critical state management and how it applies to distributed systems and affects reliability
    define the CAP theorem and describe how it relates to distributed systems
    outline how to coordinate system failures on distributed systems
    differentiate deterministic and nondeterministic algorithms and how they relate to distributed systems
    describe the system models that can be used with distributed systems
    define the concept of distributed consensus and list the stages of validation
  • define the concept of Byzantine fault and describe how it applies to distributed systems
    describe the distributed consensus architecture patterns used in distributed systems
    describe best practice and tricks for increasing performance for distributed systems
    define the Multi-Paxos protocol and describe how it relates to distributed systems
    outline how to deploy distributed consensus-based systems and name some key considerations
    name and describe the key considerations when monitoring distributed consensus systems
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 20s
    UP NEXT
  • Playable
    2. 
    Critical State Management
    5m 41s
  • Locked
    3. 
    CAP Theorem
    5m 19s
  • Locked
    4. 
    Distributed Systems Coordination Failure
    7m 22s
  • Locked
    5. 
    Deterministic vs. Nondeterministic
    7m 21s
  • Locked
    6. 
    Distributed System Models
    5m 51s
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    7. 
    Distributed Consensus
    5m 9s
  • Locked
    8. 
    Byzantine Fault
    4m 51s
  • Locked
    9. 
    Distributed Consensus Architecture Patterns
    6m 50s
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    10. 
    Distributed Consensus Performance
    5m 40s
  • Locked
    11. 
    Multi-Paxos Detailed Message Flow
    4m 50s
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    12. 
    Distributed Consensus-based System Deployment
    7m 33s
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    13. 
    Distributed Consensus System Monitoring
    4m 54s
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    14. 
    Course Summary
    1m 7s

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