Mastering the Maze: Navigating Complexity in Distributed Systems

Mastering the Maze: Navigating Complexity in Distributed Systems

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linearizability

29 of 52

29 of 52

linearizability

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Mastering the Maze: Navigating Complexity in Distributed Systems

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  1. 1 intro
  2. 2 preamble
  3. 3 agenda
  4. 4 what is a distributed system?
  5. 5 what is complexity?
  6. 6 monolithic architecture
  7. 7 disadvantages
  8. 8 microservices architecture
  9. 9 what do distributed systems give us?
  10. 10 challenges, quality attributes
  11. 11 what are main troubles?
  12. 12 unreliable networks
  13. 13 strategy: timeout
  14. 14 strategy: retry
  15. 15 strategy: idempotency
  16. 16 strategy: circuit breaker
  17. 17 concurrency and lost writes
  18. 18 strategy: snapshot isolation
  19. 19 strategy: compare and set
  20. 20 strategy: lease
  21. 21 dual write problem
  22. 22 strategy: transactional outbox
  23. 23 strategy: log tailing
  24. 24 unreliable clocks
  25. 25 availability and consistency
  26. 26 high availability
  27. 27 failure
  28. 28 consistency types
  29. 29 linearizability
  30. 30 strategy: distributed consensus algorithm, e.g. raft
  31. 31 more complexities
  32. 32 eventual consistency
  33. 33 strategy: read from leader
  34. 34 process pauses
  35. 35 strategy: fencing
  36. 36 observability
  37. 37 strategy: distributed tracing
  38. 38 strategy: orchestration over choreography
  39. 39 evolvability and cybernetics principles
  40. 40 systems thinking
  41. 41 feedback loops
  42. 42 adaptability and learning
  43. 43 goal-oriented design
  44. 44 big ball of mud
  45. 45 hierarchy
  46. 46 fallacy: all microservices are the same
  47. 47 strategy: service types
  48. 48 sre principles
  49. 49 infrastructure as code
  50. 50 chaos engineering and testing: jepsen tests
  51. 51 simplicity and measuring complexity
  52. 52 thank you for attending!

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