The document outlines the architecture and operations of Wix's microservice stack, including topology, networking, and service scheduling challenges. It discusses various protocols, load balancing strategies, and the structure of code repositories while emphasizing the importance of health monitoring and debugging practices. The presentation highlights the complexity of service management and operational metrics while inviting potential job candidates to consider employment opportunities at Wix.

1. The Wix Microservice
Stack
Tomer Gabel, Wix
March 2017 @ Dnipro, UA

2. Agenda
1. Topology
2. Networking
3. Structure
4. Operations
5. Beer

3. Our conceptual system
Store Service
Checkout
Service
Cart Service

4. 1. TOPOLOGY
Image: Penrose Steps by Alex Eylar (CC BY-NC-SA 2.0)

5. Our conceptual system
Store Service
Checkout
Service
Cart Service
Host A
Host B Host C

6. Topology
Topology
Service→
host
mapping
Server
inventory
Service
catalogue
Formally,
“scheduling”

7. Service Scheduling
• A hard problem!
• Multiple dimensions:
– Resource utilization
(disk space, I/O, RAM,
network, power…)
– Resource availability
– Failover
(physical server, rack, row…)
– Custom constraints
(zoning, e.g. PCI compliance)

8. Service Scheduling
• A hard problem!
• Multiple dimensions:
– Resource utilization
(disk space, I/O, RAM,
network, power…)
– Resource availability
– Failover
(physical server, rack, row…)
– Custom constraints
(zoning, e.g. PCI compliance)

9. Service Scheduling
• The middle ground:
– Naïve automatic
scheduler
– Human-configured
overrides for zoning,
optimization
• Easy but limited scale
– A few hundred servers

10. Our conceptual system
Store Service
Checkout
Service
Cart Service
http://err:42/uh
… derp?

11. Service Discovery
Static Dynamic
Logical
Physical
That way
madness lies

12. Service Discovery
Static Dynamic
Logical
Physical

13. Service Discovery
Static Dynamic
Logical
Physical

14. In practice
• Static topology
– Managed with Frying Pan
– Exported to Chef
– Deployed via
configuration files
• Live registry in
Zookeeper
– Deployment only
– … for now

15. 2. NETWORKING
Image: Neurons by Birth Into Being (CC BY-NC-SA 2.0)

16. Back to diagrams
Store Service
Checkout
Service
Cart Service

17. Back to diagrams
Store Service
Checkout
Service
Cart Service
Protocol

18. Protocol
• RPC-style
– Sync or async
– Point-to-point
• Message passing
– Async only
– Requires broker
Shared
Concerns
Topology Serialization Operations

19. Protocol
• Wix RPC
– RPC-style
– Custom JSON
– HTTP
• Pros/cons
– Rock-solid
– Sync/blocking
– Legacy
Image: psycho chicken by Bernhard Latzko (CC BY-ND 2.0)

20. Protocol
• Greyhound
–Message-passing
–Custom JSON
–Kafka
• Pros/cons
–Async + replayable
–Still experimental
Image: Robin Fledgeling by edgeplot (CC BY-NC-SA 2.0)

21. Load balancing
• Centralized
– Simple
– Limited flexibility
– Limited scale
– Thin implementation
 highly portable
– Suitable for static
topologies
• Distributed
– Highly scalable
– Flexible
– Fully dynamic
– Fat implementation
 difficult to port
• Quasi-distributed
– e.g. Synapse
– Best of both worlds?

22. Load balancing
• Centralized
– Simple
– Limited flexibility
– Limited scale
– Thin implementation
 highly portable
– Suitable for static
topologies
• Distributed
– Highly scalable
– Flexible
– Fully dynamic
– Fat implementation
 difficult to port
• Quasi-distributed
– e.g. Synapse
– Best of both worlds?
Frying Pan
 Chef
 Nginx

23. To our shame
• There’s always IDL.
• Informal
– Text documentation
– Code samples
• Formal
– Swagger, Apiary etc.
– ProtoBuf, Thrift, Avro
– WSDL, god forbid!
• … or
– Ad-hoc
public interface SiteMembersService {
SiteMemberDto getMemberById(
Guid<SiteMember> memberId,
UserGuid userId);
SiteMemberDto getMemberOrOwnerById(
Guid<SiteMember> memberId,
Guid<SMCollection> collectionId);
SiteMemberDto getMemberDtoByEmailAndCollectionId(
String email,
Guid<SMCollection> collectionId);
List<SiteMemberDto> listMembersByCollectionId(
Guid<SMCollection> collectionId);
}

24. To our shame
• There’s always IDL.
• Informal
– Text documentation
– Code samples
• Formal
– Swagger, Apiary etc.
– ProtoBuf, Thrift, Avro
– WSDL, god forbid!
• … or
– Ad-hoc
public interface SiteMembersService {
SiteMemberDto getMemberById(
Guid<SiteMember> memberId,
UserGuid userId);
SiteMemberDto getMemberOrOwnerById(
Guid<SiteMember> memberId,
Guid<SMCollection> collectionId);
SiteMemberDto getMemberDtoByEmailAndCollectionId(
String email,
Guid<SMCollection> collectionId);
List<SiteMemberDto> listMembersByCollectionId(
Guid<SMCollection> collectionId);
}

25. In Detail
• Java interfaces?
+ Ridiculously simple
+ Lend well to RPC
– Coupled to JVM
• JSON serialization
+ Jackson-based
+ Custom, extensible
mapping
– Reflection-based
• Server stack (JVM)
– Jetty
– Spring + Spring MVC
– Custom handler
• RPC client stack (JVM)
– Spring
– Proxy classes
generated at runtime
– AsyncHttpClient

26. In Detail
• Java interfaces?
+ Ridiculously simple
+ Lend well to RPC
– Coupled to JVM
• JSON serialization
+ Jackson-based
+ Custom, extensible
mapping
– Reflection-based
• Alternative stack
– Based on Node.js
– Generated RPC clients
– Manually-converted
entity schema :-(

27. In Detail
• Java interfaces?
+ Ridiculously simple
+ Lend well to RPC
– Coupled to JVM
• JSON serialization
+ Jackson-based
+ Custom, extensible
mapping
– Reflection-based
• Alternative stack
– Based on Node.js
– Generated RPC clients
– Manually-converted
entity schema :-(

28. Cascade Failures
• What is a
cascade failure?
• Mitigations
– Bulkheading
– Circuit breakers
– Load shedding
• We don’t do any
of that (mostly)

29. Does it go?
• Short answer: yes.
• Battle-tested
– Evolving since 2010.
– >200 services in
production.
• Known quantity
– Easy to operate
– Performs well enough
– Known workarounds

30. Not all is well, though
• Polyglot development
– Custom client stack
– Expensive to port!

31. Not all is well, though
• Polyglot development
– Custom client stack
– Expensive to port!
• Implicit state
– Transparently handled
by the framework
– Thread local storage
– Hard to go async!
Client Proxy
Service A
Service B
Session info
Session info
Transaction ID
Session info
Transaction ID
A/B experiment
Transaction ID
A/B experiment

32. 3. STRUCTURE

33. Codebase modeling
• A product comprises
multiple services
• Services have
dependencies
– Creating a DAG
– Tends to cluster
around domains
• Org structure reflects
the clustering
(Conway)

34. Codebase modeling
Repository-per-domain
• Small repositories
• Artifacts built
independently
• Binary dependencies
• Requires specialized tools
to manage:
– Versions
– Build dependencies
Monorepo
• Repository contains
everything
• Code is built atomically
• Source dependencies
• Requires a specialized
build tool

35. At Wix
• One repo per domain
• Dependencies:
– Declared in POMs
– Version management
via custom plugin
– Builds managed by
custom tool*
• Custom dashboard,
“Wix Lifecycle”
* Lifecycle – Dependency Management Algorithm

36. Version management
[INFO] QuickRelease
/home/builduser/agent01/work/d9922a1c87aee4bb
bf1bc8bcfb2eccebc4268651c5f19faa689be6e4
[08:10:55][INFO] Adding tag RC;.;1.20.0
[08:10:56][INFO] Tag RC;.;1.20.0 added
successfully
[08:10:56][INFO] Working on onboarding-server-web
[08:10:56][INFO] onboarding-server-web-1.19.0-
SNAPSHOT jar deployable copied
[08:10:56][INFO] onboarding-server-web-1.19.0-
SNAPSHOT jar sources copied
[08:10:56][INFO] onboarding-server-web-1.19.0-
SNAPSHOT jar copied
[08:10:56][INFO] onboarding-server-web-1.19.0-
SNAPSHOT jar tests copied
[08:10:56][INFO] onboarding-server-web pom
deployed
[08:10:57][INFO] Deploying artifacts to release
artifacts repository
[08:10:57][INFO] Deploying onboarding-server-web
to RELEASE
[08:10:57][INFO] pushing new pom
[08:10:59]2016-02-22 08:10:39 [INFO ] /usr/bin/git
push --tag origin master exitValue = 0
• All artifacts share a
common parent
– Master list of versions
• Manually-triggered
release builds
– Custom release plugin
– Increments version
– Updates master
– Pushes changes to git

37. 4. OPERATIONS

38. Back to diagrams
Store Service
Checkout
Service
Cart Service
How ya
doin’?

39. Health
• Host monitoring
– Sensu alerts
– Usual host metrics
– Health-check endpoint
in framework
• End-to-end
– Pingdom
• Business
– Custom BI toolchain

40. Instrumentation
• Metrics
– DropWizard Metrics
– Graphite and Anodot
– Built-in metrics (RPC,
resource pools…)
– APIs for custom
metrics
• Alerts
– Anodot, NewRelic
– Via PagerDuty

41. Debugging
• Logs
– Good old Logback
– No centralized
aggregation
– Not particularly useful
• Feature toggle
overrides
• Distributed tracing

42. WE’RE DONE HERE!
… AND YES, WE’RE HIRING :-)
Thank you for listening
tomer@tomergabel.com
@tomerg
http://il.linkedin.com/in/tomergabel
Wix Engineering blog:
http://engineering.wix.com