Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
The Walking Dead - A Survival Guide to Resilien...
Search
Michael Nitschinger
April 23, 2015
Programming
0
360
The Walking Dead - A Survival Guide to Resilient Reactive Applications
This talk was given at JAX 2015 in Mainz.
Michael Nitschinger
April 23, 2015
Tweet
Share
More Decks by Michael Nitschinger
See All by Michael Nitschinger
High Performance JVM Networking with Netty
daschl
5
1.2k
Reactive Data Access with RxJava... and N1QL!
daschl
0
180
Spark with Couchbase
daschl
0
150
Reactive Data Access with RxJava ... and N1QL!
daschl
0
170
The Walking Dead - A Survival Guide to Resilient Reactive Applications
daschl
0
210
State of the Art JVM Networking with Netty
daschl
2
440
The Walking Dead - A Survival Guide to Resilient Reactive Applications
daschl
1
430
The Walking Dead - A Survival Guide to Resilient Applications
daschl
0
1.3k
Building a Reactive Database Driver on the JVM
daschl
2
950
Other Decks in Programming
See All in Programming
チームの境界をブチ抜いていけ
tokai235
0
220
Introduce Hono CLI
yusukebe
6
3.1k
釣り地図SNSにおける有料機能の実装
nokonoko1203
0
200
モテるデスク環境
mozumasu
3
1.3k
登壇は dynamic! な営みである / speech is dynamic
da1chi
0
360
Building, Deploying, and Monitoring Ruby Web Applications with Falcon (Kaigi on Rails 2025)
ioquatix
4
2.5k
Vueのバリデーション、結局どれを選べばいい? ― 自作バリデーションの限界と、脱却までの道のり ― / Which Vue Validation Library Should We Really Use? The Limits of Self-Made Validation and How I Finally Moved On
neginasu
2
1.5k
bootcamp2025_バックエンド研修_WebAPIサーバ作成.pdf
geniee_inc
0
130
オープンソースソフトウェアへの解像度🔬
utam0k
17
3.1k
alien-signals と自作 OSS で実現する フレームワーク非依存な ロジック共通化の探求 / Exploring Framework-Agnostic Logic Sharing with alien-signals and Custom OSS
aoseyuu
2
600
CSC509 Lecture 06
javiergs
PRO
0
270
TransformerからMCPまで(現代AIを理解するための羅針盤)
mickey_kubo
7
5.1k
Featured
See All Featured
GraphQLの誤解/rethinking-graphql
sonatard
73
11k
The World Runs on Bad Software
bkeepers
PRO
72
11k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
53k
Visualization
eitanlees
149
16k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
46
7.7k
[RailsConf 2023] Rails as a piece of cake
palkan
57
5.9k
Git: the NoSQL Database
bkeepers
PRO
431
66k
Build The Right Thing And Hit Your Dates
maggiecrowley
38
2.9k
Optimizing for Happiness
mojombo
379
70k
Product Roadmaps are Hard
iamctodd
PRO
55
11k
How to Think Like a Performance Engineer
csswizardry
27
2.1k
Speed Design
sergeychernyshev
32
1.2k
Transcript
Michael Nitschinger | Couchbase, Inc. The Walking Dead A Survival
Guide to Reactive Resilient Applications
the right Mindset 2
– U.S. Marine Corps “The more you sweat in peace,
the less you bleed in war.” 3
4
5
Not so fast, mister fancy tests! 6
What can go wrong? Always ask yourself 7
Fault Tolerance 101 8
Fault Error Failure A fault is a latent defect that
can cause an error when activated. 9
Fault Error Failure Errors are the manifestations of faults. 10
Fault Error Failure Failure occurs when the service no longer
complies with its specifications. 11
Fault Error Failure Errors are inevitable. We need to detect,
recover and mitigate them before they become failures. 12
Reliability is the probability that a system will perform failure
free for a given amount of time. MTTF Mean Time To Failure MTTR Mean Time To Repair 13
Availability is the percentage of time the system is able
to perform its function. availability = MTTF MTTF + MTTR 14
Expression Downtime/Year Three 9s 99.9% 525.6 min Four 9s 99.99%
52.56 min Four 9s and a 5 99.995% 26.28 min Five 9s 99.999% 5.256 min Six 9s 99.9999% 0.5256 min 100% 0 15
Pop Quiz! Edge Service User Service Session Store Data Warehouse
Wanted: 99.99% Availability ??? ??? ??? 16
Pop Quiz! Edge Service User Service Session Store Data Warehouse
Wanted: 99.99% Availability 99.99% 17 99.99% 99.99%
Pop Quiz! Edge Service User Service Session Store Data Warehouse
Wanted: 99.99% Availability ~99.999% ~99.999% ~99.999% 18
Fault Tolerant Architecture 19
Units of Mitigation are the basic units of error containment
and recovery. 20
Escalation is used when recovery or mitigation is not possible
inside the unit. 21
Escalation 22 Cluster Node Node Service Service Service Service Service
Endpoint Endpoint Endpoint Endpoint Endpoint
Escalation 23 Cluster Node Node Service Service Service Service Service
Endpoint Endpoint Endpoint Endpoint Endpoint
Escalation 24 Cluster Node Node Service Service Service Service Service
Endpoint Endpoint Endpoint Endpoint Endpoint
Escalation 25 Cluster Node Node Service Service Service Service Service
Endpoint Endpoint Endpoint Endpoint Endpoint
Redundancy Cost Active/Active Active/Standby N+M Active/Passive Cost Time To Recover
26
The Fault Observer receives system and error events and can
guide and orchestrate detection and recovery Unit Unit Observer Listener Listener Unit Unit 27
28
29
Detecting Errors 30
A silent system is a dead system. 31
A System Monitor helps to study behaviour and to make
sure it is operating as specified. 32 http://cdn-www.airliners.net/aviation-photos/photos/9/2/1/0982129.jpg
https://github.com/Netflix/Turbine 33
Periodic Checking Heartbeats monitor tasks or remote services and initiate
recovery Routine Exercises prevent idle unit starvation and surface malfunctions 34
35 Encoder( Encoder( Ne*y( Writes( Ne*y( Reads( Decoder( Decoder( Event
on Idle No Traffic Endpoint
Riding over Transients is used to defer error recovery if
the error is temporary. “‘Patience is a virtue’ to allow the true signature of an error to show itself.” - Robert S. Hanmer 36
37 The Leaky Bucket
And more! • Complete Parameter Checking • Watchdogs • Voting
• Checksums • Routine Audits 38
Recovery and Mitigation of Errors 39
Timeout to not wait forever and keep holding up the
resource. 40 X
Failover to a redundant unit when the error has been
detected and isolated. Cost Active/Active Active/Standby N+M Cost Time To Recover Redundancy Reminder 41
Intelligent Retries Time between Retries Number of Attempts Fixed Linear
Exponential 42
Restart can be used as a last resort with the
trade-off to lose state and time. 43
Fail Fast to shed load and give a partial great
service than a complete bad one. Boundary 44
Backpressure & Batching! 45
Case Study: Hystrix https://raw.githubusercontent.com/wiki/Netflix/Hystrix/images/hystrix-flow-chart-original.png 46
And more! • Rollback • Roll-Forward • Checkpoints • Data
Reset Recovery Mitigation • Bounded Queuing • Expansive Controls • Marking Data • Error Correcting Codes 47
And more! • Rollback • Roll-Forward • Checkpoints • Data
Reset Recovery Mitigation • Bounded Queuing • Expansive Controls • Marking Data • Error Correcting Codes 48
Recommended Reading 49
Patterns for Fault-Tolerant Software by Robert S. Hanmer 50
Release It! by Michael T. Nygard 51
Announcement CB Server 4.0 dp! 52 http://blog.couchbase.com/introducing-developer-preview-for-couchbase-server-4.0
Any Questions? 53
twitter @daschl email
[email protected]
Thank you! 54