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Reliability of Distributed Systems
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Piyush Verma
June 22, 2019
Technology
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Reliability of Distributed Systems
Piyush Verma
June 22, 2019
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Transcript
Reliability of Distributed Systems - Piyush Verma
Every product either dies a hero or lives long enough
to hit Reliability issues. 2
Customer Empathy No Chooran. Cost to Everything Architectures adapt to
$ Priority 01 02 03 04 3 Take it and Go
Service receives SMS User sends SMS Remind me to buy
milk at 6:30 PM to 53308 Cron gets Activated when time is right. Call the User 4 Sample Product
Service receives SMS User sends SMS Remind me to buy
milk at 6:30 PM to 53308 Cron gets Activated when time is right. Call the User 5 Sample Product: Inbound
Cron gets Activated when time is right. Call the User
6 Sample Product: Outbound Service receives SMS User sends SMS Remind me to buy milk at 6:30 PM to 53308
7 Inbound Connection
— Leslie Lamport https://www.microsoft.com/en-us/research/uploads/prod/2016 /12/Distribution.pdf “A distributed system is one
in which the failure of a computer you didn’t even know existed can render your own computer unusable” 8
Four Flavors of Failure 9 Disk Network CPU Memory
Network is Reliable Intra-LAN latency is ~ Zero Network is
Homogeneous Network cost is Zero 01 02 03 04 10
11 Scope of Failures: Again
At-least one server is online All servers are below 100%
All servers are responding within x ms. All of the above. 01 02 03 04 12
13 #1 Server is Unavailable
14 Replication Available
15 Replication Available
16 Available != Load Balanced
17 Load Balanced
18 Architecture of a Balancer
GCP AWS On-Prem Azure Who uses What? 19
Trilemma 20
Trilemma 21 Available Economical Endurable
22 Available + Load Balanced
Load Balancing 23
24 Monty Hall Problem: Was Marilyn vos Savant, right?
25 Server-side Load Balancing Example: Fabio
26 Look-aside Load Balancing Example: Consul/ DNS
27 Client-side Load Balancing Example: Ribbon
28 Client-side Load Balancing Example: Ribbon + Curator
29 Problems
30 Load Shedding
— Tyler McMullen https://www.infoq.com/presentations/load-balancing/ “Load Balancing is almost Impossible” 31
Alternate Reliability 32
33 Asynchronous Architectures
34 Asynchronous Architectures Example: RabbitMQ Kafka Kinesis SQS
Cron gets Activated when time is right. Call the User
35 Sample Product: Outbound Service receives SMS User sends SMS Remind me to buy milk at 6:30 PM to 53308 Part 1
36 Outbound
37 Scope of Failure: Outbound
38 Retries
39 Retries: Transient Failures
40 Exponential Backoff: Short term Transient Failures ✋ ✋ ✋
✋ ✋
41 Circuit Breaking: Long Term Transient Failures
42 Revisited
Dilemma 43 At-least Once Exactly-Once At-most Once
44 At-most once delivery
45 At-least once delivery
46 Exactly once delivery
47 Exactly once delivery = At-least-once Delivery + Exactly-once Processing
Keys to Only-Once delivery 48 Atomic Window Idempotent
Out-of-Order delivery 49
Revisit 50
Service receives SMS User sends SMS Remind me to buy
milk at 6:30 PM to 53308 Cron gets Activated when time is right. Call the User 51 Sample Product
52 Problems of State
53 Problems of State
54 Locked /Serialization
55 Master/ Master/ Slave
56 Clustering
Scalability 57 Data Replication Reduced Communication Logic/Data Decentralization
CAP Theorem [Sab topi pehna rahe] 58
59 Trilemma Available Partition Consistent
PACeLC Theorem 60
Dilemma 61 Consistency Latency
62 Revised Flow
63 What about Spanner? What about Calvin?
Reliable System 64 Scalable Correct Transparent
Access Transparency Location Transparency Concurrency Transparency Failure Transparency 01 02
03 04 65
Size Scalability Geographical Scalability 01 02 66
Summary 67 Consistent Available Economical Low Latency
68 All Put Together
Embrace your Bugs No Silver Bullet Cost to Everything Product
First 01 02 03 04 69
Does anyone have any questions?
[email protected]
Thanks 70