For the past 3 years, ASOS has been on a journey of moving its monolithic architecture to Microservices - and what has been driving this change is not just the buzzword: as with any monolith, the spiraling cost of change stifles the business and innovation. And in this market, advancing your competitive edge by constant improvement is a big factor in the overall success of your business. Probably not many know that ASOS website drives more traffic (and way more bandwidth) than the showcase Stackoverflow. Some of the services are built to serve up to 10K RPS (request/second). And the services are spread around the globe currently on more than 4 Azure DCs. And on the top, we have pretty thick data pipelines moving many GBs of data to enable traditional BI - as well as the trendy Machine Learning algorithms powering recommendations and personalisation. This talk will be a brief intro to the overall view of what +20 2-pizza teams are doing and in specific, goes into some of the details of ML-enabled recommendations platform. Underneath the success of the transition, has been a Logging/Monitoring/Alerting system (Elasticsearch+ConverorBelt+Kibana) to empower platform teams to ensure health of the system and keeping Mean-Time-to-Recovery low. As with any such talk, there will be a section on lessons learned...

1. © 2016 ||| ASOS Plc@aliostad @dav3green
Microservice
Architecture at ASOS
Ali Kheyrollahi

2. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS
Established at 2000
Global Fashion destination for “20-something”.
Hires +2500 staff & +250 in tech (700)
Grown average of 35% YoY
39th biggest global online retailer

3. © 2016 ||| ASOS Plc@aliostad @dav3green
In Numbers
A c t i v e C u s t o m e r s → 12 M
N e w P r o d u c t s / w k → 4 k
U n i q u e V i s i t s / m o → 123 M
P a g e V i e w s / d a y → 95 M
P l a t f o r m T e a m s → 40
A z u r e D a t a C e n t r e s → 5
T u r n O v e r 2 0 1 6 → 1.5b

4. © 2016 ||| ASOS Plc@aliostad @dav3green
Nick Beighton - CEO
from “IT Cascade” slides - Oct 2014
ASOS - A Tech Company

5. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS Stock Price: 2009-2013
More than 2000% growth!

6. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS Stock Price: 2009-2014
Multiple IT project failures
Tech issues disrupting promotions
Overdue features
were not delivered

7. © 2016 ||| ASOS Plc@aliostad @dav3green
Microservices
…
why?

8. © 2016 ||| ASOS Plc@aliostad @dav3green
“Can I haz microservicez?”
“It is all a marketing hoax.”
“I dunno…” The sceptic…

9. © 2016 ||| ASOS Plc@aliostad @dav3green
Scaling People
not the solution
↓Complexity of each service
at the cost of ↑overall solution
Frequent and
independent Deployments
Decentralising
decision centres
Governance and
EA is different
Auftragstaktik Doctrine is the conceptual underpinning
of HOW to think and operate effectively;
teaching leaders WHAT to think is
dogma…
Auftragstaktik encourages commanders
to exhibit initiative, flexibility and
improvisation while in command…
In what may be seen as surprising to
some, Auftragstaktik empowers
commanders to disobey orders and
revise their effect as long as the intent of
the commander is maintained…

10. © 2016 ||| ASOS Plc@aliostad @dav3green
SOA Microservices
Main Goal Architectual Decoupling Agility
Audience Mainly Architecture Everyone (inc Buisness)
Set out to solve Architectural Coupling
Scaling People,
Frequent Deployment
Impact on Structure of
Organisation
Minimal Huge
Service Cardinality Usually up to a dozen >40 (Commonly >100)
When to do Always teams > ~5**
Law Conway’s Reverse Conway’s

11. © 2016 ||| ASOS Plc@aliostad @dav3green
Principles (ASOS)
*
All queries and commands through HTTP API
(No ESB-like pseudo-Microservices!)
*
Microservices can subscribe to events raised by
other Microservices
*
*
Each Microservice owns a business responsibility and defines
a clear boundary for communication (APIs and Events)
They own their data (all access to data through API only)
*
Each Microservice is realised in one (sometimes more) physical
components

12. © 2016 ||| ASOS Plc@aliostad @dav3green
Domain Modelling
Operating
ModelPeople
Successful
Architecture

13. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS
Architecture

14. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS Journey

15. © 2016 ||| ASOS Plc@aliostad @dav3green
Two-speed IT
Enterprise Domain
Digital Domain
• Predominantly “Buy”
• Integrated at top tier
• Minimal Engineering
• Project-centric
• Predominantly “Build”
• Drives sales and customer
touchpoint
• Product-centric
• Downtime unacceptable

16. © 2016 ||| ASOS Plc@aliostad @dav3green
❤ASOS

17. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS Tech Stack

18. © 2016 ||| ASOS Plc@aliostad @dav3green
Digital Domains & Platforms This is Domain
This is Platform
Logical Services
•“Domains” are ASOS’ organisational
structure for managing Platform Teams
• Platform Teams look after collections
of aligned services. They are
accountable for the full lifecycle
management

19. © 2016 ||| ASOS Plc@aliostad @dav3green

20. © 2016 ||| ASOS Plc@aliostad @dav3green
Operating Model
Indicative Team Numbers
6 Digital Domains
19 Platforms
35 Dev / Scrum teams
24 Solution Architects
700+ people in Technology
(2500 in Asos total)
Avg +20 people per month over last year

21. © 2016 ||| ASOS Plc@aliostad @dav3green
Governance
Bottom-Up
Top-Down

22. © 2016 ||| ASOS Plc@aliostad @dav3green
Microservice
Example:
Recommendations

23. © 2016 ||| ASOS Plc@aliostad @dav3green
- Recommendations as a destination
- Widgets
- Personalisation

24. © 2016 ||| ASOS Plc@aliostad @dav3green

25. © 2016 ||| ASOS Plc@aliostad @dav3green
1 x Soft Store (Redis)
5 x Redis Caches
3 x Cloud Services (Microservie)
2 x SQL Databases
5 x Table Storages
1 x External API
1 x Elasticsearch cluster

26. © 2016 ||| ASOS Plc@aliostad @dav3green
<SQL>
Models
<uservice>
Recommendations
API
<uservice>
Composition
API
<uservice>
Feedback
API
<External API>
Product Catalogue
API
<SQL>
Signal
<Redis>
Realtime
<Elasticsearch>
Catalogue
Computation/Retrieval
Filtering
Faceting
Authentication
Composition
Pagination

27. © 2016 ||| ASOS Plc@aliostad @dav3green
LMA
Platform

28. © 2016 ||| ASOS Plc@aliostad @dav3green
API
Application Logging
Microservice Component
cid
ETW
cid
Thread.CurrentThread.SetLogicalData(…)
[EventSource.ActivityId does not flow
over async methods]
SLAB
Azure Table
Storage Sink
Application Code
cid
To other APIs
cid
Raising Events
Listener
EC
cid
IIS Logs

29. © 2016 ||| ASOS Plc@aliostad @dav3green
API
Performance
Microservice Component
WAD
Windows Azure
Monitoring Agent
CPC
CPC: Custom Performance Counters
Inst: Instrumentation
Perfit Library
SLAB
Azure Table
Storage Sink
Application Code
Inst
Inst
Call to Data Stores or other services
CPC

30. © 2016 ||| ASOS Plc@aliostad @dav3green
Woodpecker
For `Pull` (rather than `Push`) metrics
Queue
Depth/Size
Azure SQL
Diagnostics
Canaries and
Health Endpoints

31. © 2016 ||| ASOS Plc@aliostad @dav3green
Logsink API
For Native and Web Clients
API
Logsink
/logchannels/<channel>
GET /logchannels/channelOne?a=b&c=d HTTP1.1
200 OK
Content-Type: image/gif
POST /logchannels/channelOne?a=b HTTP1.1
{
“c”: “d”
}
202 Accepted
POST /logchannels/_bulk HTTP1.1
[
{“channel”: “…”, “payload”: {...} }
]
202 Accepted
[
{“status”: 202}, ...
]
Channels
Config
EventHub

32. © 2016 ||| ASOS Plc@aliostad @dav3green
ConveyorBelt
Performance
Counters
ConveyorBelt
Azure
WAD logs
ETW Logs
Elasticsearch
Highly Available Headless Cluster shovelling data to ES
Instrumentation
Logs
IIS Logs
Woodpecker
Outputs (Pull Logs)
Sources Config
Up to 1TB/day

33. © 2016 ||| ASOS Plc@aliostad @dav3green
Monitoring (Demo)

34. © 2016 ||| ASOS Plc@aliostad @dav3green
Alerting
Elasticsearch
Platform Team LMA Support
Watch
OAT Spec
EC
1st-2nd line
Support
- xxx EC seen more than 10 times over
the last minute. Back-off for 15 minutes
- 90th percentile of API response > 100ms over
the last hour... Back-off for an hour

35. © 2016 ||| ASOS Plc@aliostad @dav3green
Lessons Learnt
‣In cloud? Design for failure… “Cloud is a Jungle”
‣Network latency & failures add up: understand and optimise time from
the user to the data
‣Using any cloud technology? Forget the hype and trust no one: test,
measure, adopt/drop, monitor, engage with your provider
‣Managing platform costs can be difficult
‣Distributed computing is hard, making it geo-distributed even harder
‣Expect to roll your sleeves up: maturity in a lot of areas is can be low
‣ (platform, tooling, skills, supporting technologies) but is changing rapidly
‣At this scale, owning your LMA data and process very important

36. © 2016 ||| ASOS Plc@aliostad @dav3green
ASOS is Hiring!
If you are intrigued by what we do,
we would love to hear from you!
Just get in touch with us in twitter
@aliostad @dav3green

37. © 2016 ||| ASOS Plc@aliostad @dav3green
Q AThank You!

38. © 2016 ||| ASOS Plc@aliostad @dav3green
References and external artwork
used
Adrian Cockcroft talk: Simplifying the future
Work in progress: Picture
Rusty Rolls Royce: Picture
Tesla S Blueprint: Picture
Two-Speed (Slow Lane, Fast Lane): Picture
Copyright of the artworks listed here belong the owners specified in the links below