Главная
Study mode:
on
1
Introduction
2
Agenda
3
Storytime
4
Data Evolution
5
Scaling
6
Cloud Computing
7
Why Scale Horizontally
8
What Does It Mean To Run A Distributed System
9
A Node On Distributed Computing
10
Summary
11
Shared Nothing Architecture
12
Unreliable Message Delivery
13
Why Are We Fenced Off
14
Building Observability
15
What We Can Know
16
The Cap Theorem
17
C
18
Replication Lag
19
Consistency is a Spectrum
20
Availability is Not Binary
21
Partition Tolerance
22
Hardware
23
Hardware Failure
24
Cables
25
Sharks
26
Kevlar
27
Network Partitions
28
Resource Isolation
29
Process Suspension
30
Network Glitch
31
People do bad things
32
Why does this matter
33
Practical reality
34
The correctness result
35
Mitigation strategies
36
Consensus Algorithms
37
The Woods Theorem
38
Building Mental Models
39
Incident Analysis
40
Blameless Discussions
41
Mental Models
42
Human Failure
43
Alert Fatigue
44
User Mindsets
45
Designing Systems for Humans
46
HugOps
Description:
Explore the complexities of distributed systems in this 33-minute conference talk from LISA19. Delve into the history of distributed computing, debunk common myths about the CAP theorem, and understand why network partitions are inevitable. Examine popular consensus algorithms and their role in mitigating risks associated with distributed operations. Learn how to design systems that account for human factors, enhancing adaptability and reducing the impact of programmatic uncertainty. Gain insights into data evolution, scaling challenges, cloud computing, and the concept of shared nothing architecture. Investigate the intricacies of unreliable message delivery, building observability, and the practical realities of hardware failures. Discover strategies for incident analysis, blameless discussions, and designing systems that prioritize human interaction and understanding.

Why Are Distributed Systems So Hard?

USENIX
Add to list