Votre application monolithique vous fait un peu honte, à l'heure où tout le monde semble résoudre ses problèmes à coups de microservices. Mais savez-vous qu'ils entraînent un grand nombre de challenges, aussi bien techniques qu'organisationnels, souvent découverts sur le tard et dans la douleur ? Après plus d'un an passé à développer des microservices pour un Pure Player à très fort trafic, je viens partager la check-list qui me semble indispensable avant de se lancer dans l'aventure.

1. Committed to innovate
LINKVALUE

2. JEAN-MARIE
LAMODIERE
Build microservices
since 07/2015
@JMLamodiere
LES MICROSERVICES,
C'EST PAS AUTOMATIQUE !
Linkvalue | Jean-Marie Lamodière
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Microservices? Think twice!
1935 CP

3. Linkvalue | Jean-Marie Lamodière
ASHAMED OF YOUR MONOLITH?
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Spaghetti code

Side effects

Team velocity decreasing

Hard to refactor

Bugs
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PROBLEMS THEY SOLVE
1.Autonomy
2.Autonomy
3.Autonomy
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PROBLEMS THEY SOLVE
1.Autonomy : deployment
2.Autonomy : langage, framework
3.Autonomy : scalability
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WHY AUTONOMY MATTERS?

Loosely coupled organisation
= less coupled systems

Quality audit on windows vista :
organizational structures
= most important factor!

Team accountability
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OTHER KEY BENEFITS
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Easier for newcomers
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Allows isolated POC

Teams scalability
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Simpler code design

Easy refactoring
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WHO USES IT?

Uber

Netflix

Amazon

Ebay

Sound Cloud

Groupon
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Guilt

Zalando

Spotify

Meetic
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M6 Web

Auchan

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« Trade-offs » appears 24x
in « Building Microservices » book
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TESTIMONY
(45' talks published on )

« We had to fall back to a monolith,
and retry when ready » – SAMUEL ROZE
PHP Tour 2016 • Prenons soin de nos microservices

« I wish I had known... » – MATT RANNEY
GOTO 2016 • What I Wish I Had Known
Before Scaling Uber to 1000 Services
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WHAT IS SO COMPLEX ?
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Boundaries : hard to find / change
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Huuuge dev-ops stack
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Distributed system
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Failure handling

Monitoring

End-to-end testing
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BOUNDARIES : WHERE TO SPLIT?

Splitting = hard to change

Size ? Small enough, not smaller

Splitting by technical layers? no!

Things that should change together
(« S » in S.O.L.I.D.)

Loose coupling, high cohesion
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DDD* TO THE RESCUE!
(* Domain Driven Design)
Toolset to help domain experts
and developers to refine and
share domain knowledge, reflect it in
the code base, and prioritize efforts.
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MAKE THE IMPLICIT, EXPLICIT!
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Copyright @DDDreboot ;)

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SPLIT BY BOUNDED CONTEXT

Bounded context = Team sharing
the same « ubiquitous language »
(same terms)

Vertical, business-focus slice
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WHEN TO SPLIT ?

When ready : technical stack chosen,
architectural decisions taken,
devs and ops willing to go,
autonomous 2 pizza feature teams

When sure of a splitting point

Start with a monolith (!) to find them
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CONWAY'S LAW
« Organizations which design systems
are constrained to produce designs
which are copies of the communication
structures of these organizations »
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2ND LAW OF CONSULTING
(Gerald Weinberg)
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SPLITTING STRATEGY

Implement double-writing
(microservice or legacy side)

Publish needed messages

One-shot data import script
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Assert data is sync

Read from microservice
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COMMUNICATION BETWEEN µS
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No shared database!
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Language agnostic (ex : rest / json)
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If weakly typed (json), have a clear doc
(optional? nullable?) or json-schema

Keep consistency. ex : pagination

Define minimal customer-centric api
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COMMUNICATION BETWEEN µS
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SYNCHRONOUS COMMUNICATION
- PROS -

Easier to understand
(= method call)

Easier transition from monolith

Instant feedback to the client
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SYNCHRONOUS COMMUNICATION
3030
User
Optin
Other service
depending on
1 optin
Register
Register
french user
Read 1 optin
Read

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SYNCHRONOUS COMMUNICATION
- CONS -

Fanout : 1% slow calls more
probable when cascading calls

Beware of coupling !

Beware of distributed monolith !!
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« Distributed monolith »
@tiffyshindo

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ASYNCHRONOUS COMMUNICATION

Message broker

Reactive : event driven
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Choregraphy over orchestration
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Autonomy over authority :
each service copy the data it needs

Work well with CQRS / ES
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ASYNCHRONOUS COMMUNICATION
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Message brokerMessage broker
Message brokerMessage broker
User French user registered
Optin User optins changed
Other service
depending on
1 optin
Register
Read

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COMMUNICATION TRAPS

Chatty communication = coupling
feature envy, wrong splitting…

Perf overhead : define « acceptable »
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DESIGN FOR FAILURE
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It will fail, have a plan!
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Define what to do, to return
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Define timeout for each call

Message hospital (dead letter queue)
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Circuit breaker / back pressure

Blameless culture needed
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NETFLIX CHAOS MONKEY

Randomly shut
down services

Cure developers
optimism ;)
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SERVICE DISCOVERY

Each µs scales individualy : which
IP should we call ?

DNS in front of a load-balancer

Kubernetes services

Docker Swarm discovery
(libkv + consul/etcd/zookeeper)
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CAP THEOREM
(Distributed Systems)

Choose 2 between consistency (C),
availability (A) and partition (P)
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Avoid distributed transactions

Embrase eventual consistency
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Use idempotent operations
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Worker to clean inconsistency
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MICROSERVICES CLIENTS

Libraries ok, 1 per language needed
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No business logic in client :
avoid anemic CRUD microservices

To call a complex api (legacy,
external), build a facade service
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CHANGE PROOF CLIENTS
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Old and new api should cohexist
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Postel's law : « be conservative in
what you do, be liberal in what you
accept from others »
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Tolerant reader (Martin Fowler) :
ignore changes not impacting you
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CHANGE PROOF CLIENTS
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API GATEWAY
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Avoid exposing µs to frontend
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Hide spliting to new microservices
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Handle authentication / roles

Pro-tips : Back-end for frontend,
1 gateway per front application
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API GATEWAY
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Microservice
Legacy
Monolith
Microservice Microservice
Android
API Gateway
Android
application
Public
Private
ReactJS
Web application
ReactJS
API Gateway

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TESTING A MICROSERVICE

No end-to-end testing at µs level
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Stub/mock others µs in functional tests

Have consumer-driven tests

No continuous integration = no µs!

One c.i. pipeline per microservice
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END TO END TESTING
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Test journeys (main features),
not user stories (already tested)
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Goal : check wiring
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Should be done in each front app
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Can run in production
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TESTING = TRUST
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Involve a quality assurance member
in your feature team

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ARCHITECT ROLE
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Keep µs map up to date
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Define communication between µs
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Define automatic deploying,
monitoring and logging strategy
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Adapt to change, like a city planner

Enforce team autonomy inside a µs
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WHAT SHOULD µS KEEP COMMON ?
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Rules : communication, logs...

Template to create new µs,
but no synchronization afterward

Violate DRY accross µs !
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Shared code = coupling

Priority : autonomy
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MONITORING / LOGGING TIPS

Pass a unique « correlation id »
to each sub-calls, including
messages and asynchronous calls

Make sure your APM supports
each language + versions

Have a look at Sysdig.org
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Extreme Programming

TDD / BDD

S.O.L.I.D.

Loose coupling,
high cohesion

DDD

Hexagonal

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BEFORE YOU START

microservices.io

martinfowler.com
/microservices/
/articles/microservices.html
/articles/microservice-trade-offs.html

groups.google.com
/forum/#!forum/microservices
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ASYNCHRONOUS COMMUNICATION

blog.christianposta.com
Why Microservices Should Be
Event Driven:Autonomy vs Authority

reactivemanifesto.org
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Lightbend.com (free)

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TALKS

What I Wish I Had Known Before
Scaling Uber to 1000 Services
GOTO 2016 • Matt Ranney

Prenons soin de nos microservices
PHP Tour 2016 • SAMUEL ROZE

Meetic backend mutation with Symfony
SymfonyLive 2015 • J. Calabrese E. Broutin

Kafka event architecture at Meetic
Forum PHP 2015 • B. Pineau M. Robin
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DDD RECOMMENDED BOOKS
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leanpub.com (free)

60. Thank you!
Linkvalue | Jean-Marie Lamodière
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Committed to innovate
LINKVALUE JEAN-MARIE
LAMODIERE
Build microservices
since 07/2015
@JMLamodiere
1935 CP