The document summarizes a presentation given by Jon Vines of AO.com on adopting microservices. Jon defines key concepts like monoliths and microservices. He discusses when to use microservices and the important role of data in microservices. Specifically, he covers accessing and sharing data between microservices using events, requests/responses, and materialized views. Jon also discusses avoiding anti-patterns like single responsibility services and independent deployments. He concludes by mentioning AO.com chose MongoDB due to its support for rapid schema evolution and low operational overhead.

1. FASTER, SIMPLER, BETTER –
MONGODB TO THE RESCUE
Thursday 23rd May
How Cloud & Microservices can help you
deliver a Superhero Advantage
#AO.com #MongoDB #Cloud #Microservices

2. WELCOME & INTRODUCTION
Dominic Wellington, Director, Field Initiatives & Readiness
Dominic.wellington@mongodb.com

3. 2
SPEAKERS
How Cloud & Microservices can help you deliver a Superhero advantage
MAT KEEP
JON VINES
DIRECTOR, FIELD INITIATIVES &
READINESS
MONGODB
SENIOR DIRECTOR, PRODUCT &
SOLUTIONS TEAM
MONGODB
PRINCIPAL SOLUTIONS ARCHITECT
MONGODB
JIM BLACKHURST
DOMINIC WELLINGTON
SOFTWARE ENGINEER & TEAM LEAD
AO.COM
#AO.com #MongoDB #Cloud #Microservices

4. • Welcome
• Building a Data Platform Strategy that Accelerates
Application Delivery
• Break
• Customer Story: AO.Com
• Accelerating Microservices Development with MongoDB
Atlas & Stitch
• Q&A
• Drinks & Networking
Agenda

5. 1000+
Employees
100
Countries
13,000+
Customers
60m+
Downloads
34 Offices
Globally
Nasdaq: MDB
Who is MongoDB?
Accelerate time
to value
Lower
costs
Reduce
risk
Create competitive
advantage
Intelligent Operational Data Platform
Best for
modern data
Intelligent
placement
Run
Anywhere

6. Why Do People Use Microservices?

7. BUILDING A DATA PLATFORM
STRATEGY THAT ACCELERATES
APPLICATION DELIVERY
Mat Keep, Senior Director, Product & Solutions Team
mat.keep@mongodb.com
@matkeep

8. The Cloud Age
Platform Shift

9. Mainframe Client-Server Web
1980s1960s-70s
The Cloud Age
Platform Shift

10. Mainframe Client-Server Web
1980s Late 90s – 2000s1960s-70s
The Cloud Age
Platform Shift

11. Mainframe Client-Server Web
Control & Efficiency AGILITY & INNOVATION
Cloud & Mobile
Distributed Systems
1980s Late 90s – 2000s 2010>1960s-70s
The Cloud Age
Platform Shift

12. Seismic Shifts
Adoption of cloud
infrastructure
Adoption of cloud
services
Maturing Cloud Strategies

13. Seismic Shifts
Adoption of cloud
infrastructure
Adoption of cloud
services
Maturing Cloud Strategies
Centralized IT
Self-reliant, agile
teams
DevOps Movement

14. Seismic Shifts
Adoption of cloud
infrastructure
Adoption of cloud
services
Maturing Cloud Strategies
Centralized IT
Self-reliant, agile
teams
DevOps Movement
Monolithic
architectures
Microservices &
Serverless
Application
Modernization

15. Why do I need to rethink my underlying data
layer…..?
Cloud Native Geo-distribution Innovate faster

16. 15
Maximizing developer velocity is key
Access to developers is a
bigger constraint on growth than
access to capital, according to
survey of thousands of C-level
executives.
The Developer Coefficient, Stripe
Developers spend 42% of their work
week on maintenance issues and fixing
bad code.

17. API Access Layer
Operational Data
Customers
Products
Accounts
ML Models
Multitenant Infrastructure
App1 App2 App3
1.Development agility
2.Enforce governance
3.Data re-use
Cloud Data Strategy
Standardized, fully automated database service
Cloud Portable
Any Cloud, Any Where

18. 17
The IMPACT of automated cloud services &
microservices
Application development
Performance optimization
Self-service and on-demand
Fully elastic
API-driven
Secure and compliant
Move faster
46x
more code deploys
Be strategic
44%
more time on new work
Improve quality
21%
less time on fixing code
Build securely
50%
less time on fixing
security issues
2017 State of DevOps Report, Puppet

19. 18
Why MongoDB?
Best way to work
with data
Intelligently put data
where you need it
Freedom
to run anywhere
Intelligent Data Platform

20. Freedom To Run Anywhere
On-Premises Private Cloud
Fully Managed
Cloud ServicesHybrid Cloud Public Cloud
Cloud Continuum
Database that runs
the same everywhere
Coverage in any
geography
Leverage the benefits
of a multi-cloud
strategy
Avoid lock-in

21. MongoDB – The Polyglot Data Layer for
Microservices
Analytics, BI & AI
Aggregations

22. Data Platform on Private Cloud

23. 10-step Methodology For Private DBaaS
Step 1:
Common
Workload Reqs
Step 4:
Enabling
Multitenancy
Step 5:
Security
Enforcement
Step 6:
Performance &
Uptime SLAs
Step 7:
Provisioning &
Mgmt
Step 8:
Implementation
Step 3:
Container
Strategy
Step 2:
Hardware & OS
Selection
Step 9:
Cost Accounting &
Chargeback
Step 10:
Design Reviews
Discovery
Design
Deploy

24. 23
Run by You, With MongoDB Ops Manager
MongoDB Ops Manager
• Automation: Provision, Upgrade, Scale
• Monitoring & Alerting
• Continuous Backup & PiT Restore
• Patching
• Performance Advice
• Kubernetes integration
MainframeOn-Prem Cluster
Self-managed
in the cloud

25. From Traditional To DBaaS
• Slow to build and launch
new applications
• Multiple copies of data
• Complex data
reconciliation controls
• High licensing costs
• Sprawling server estate
12,000+ RDBMS Instances
3,500 Systems, 40,000 Cores
1,200+ Coherence Instances

26. Data Fabric
✔ Multi-tenant PaaS
✔ Exposing APIs for data streaming and
storage
✔ Cloud native, self-service
✔ Modern, industry standard, open
technologies
✔ Intra-day releases
✔ Multi-data center
“Data Fabric provides data storage, query and distribution as
a service, enabling application developers to concentrate on
business functionality.”
Data Fabric Clients
Java, .NET, REST
API Layer
CRUD & Streaming
App Server Layer
Java + Linux
Database
MongoDB
Messaging
Kakfa
Security
Authentication&AuditData Fabric

27. Results
• £m license cost avoidance (Coherence)
• Plans to decommission hundreds of servers
• Coherence
• Oracle/SQL Server databases
Cost
Reduction
• 2 foundational applications refactored off Coherence
• Supporting data needs of a dozen applicationsSimplification
• Velocity: Develop new applications in days
• No need for database administration
• self-service data service
• Promotes collaboration and data sharing
Velocity
Slide taken from https://www.mongodb.com/presentations/mongodb-days-uk-building-an-enterprise-data-fabric-at-royal-bank-of-scotland-with-mongodb

28. Data Platform on Public Cloud

29. 28
You have 2 choices: Self-Managed or DBaaS
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road

30. 29
You have 2 choices: Self-Managed or DBaaS
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road
1. Provision instances and storage
2. Configure HA
3. Configure security
4. Configure backup/restore
5. Monitoring & alerting
6. Ongoing upgrades & maintenance

31. 30
You have 2 choices: Self-Managed or DBaaS
Cloud Migration
or Cloud First
Self-Managed
Aka “Lift and Shift”
Database as
a service
Fork in
the road
1. Provision instances and storage
2. Configure HA
3. Configure security
4. Configure backup/restore
5. Monitoring & alerting
6. Ongoing upgrades & maintenance
Choose instance, hit deploy,
wait a couple of minutes

32. Global Cloud Database Service

33. 32
MongoDB Atlas unlocks agility & reduces cost
Self-service, elastic,
and automated
Global and highly
available
Secure by default
Comprehensive
monitoring
Managed disaster
recovery
Serverless
Stitch Platform

35. Gaming giant Square Enix builds big data gaming platform on MongoDB
Atlas aiming for maximum efficiency, with expert help from MongoDB
Professional Services
Highlights
● Multiple critical services hosted on
MongoDB, including:
○ Player state
○ Async gameplay features
○ Telemetry
● Each game generates 0.5TB data
per day. Migrating to MongoDB
enables Square Enix to serve players
with lower latency, elastically scale,
and analyse streams of event data to
improve gaming experience
MongoDB cloud
services provide
complete operational
automation
Only 1
Resource needed to
manage entire MongoDB
game estate
Migration from SQL
Server to MongoDB
enables company to
build faster, and run
at lower cost
£1m+
Per annum database
licensing savings

36. Cloud Data Strategy:
Getting Started

37. MongoDB Professional Services Cloud
Factory
People
Model
Security
Model
Infrastructure
Management
Application
Management
Support
Model
Financial
Model
MongoDB Cloud Operating Model

38. Next application
sprint
Optimize
Cloud Native Roadmap
Validate
Application Outputs
Implement
Solution Iteration
Design
Application
Iterate to next batch of
applications
Analyze
Application Portfolio
Define
Cloud Operating Model
MongoDB Professional Services Cloud Factory

39. Conclusion
1 Cloud is more than just a new
platform: microservices, agile,
DevOps enable new ways of
delivering apps faster
2 Cloud data strategy is an
essential building block
3 MongoDB is the foundation for
cloud data

40. Resources To Learn More
Spin up a cluster on the
Free Tier today
Download the Whitepaper

41. THANK YOU
Mat Keep, Senior Director, Product & Solutions Team
mat.keep@mongodb.com
@matkeep

42. COFFEE BREAK
20 MINS
#AO.com #MongoDB #Cloud #Microservices

43. WELCOME BACK
#AO.com #MongoDB #Cloud #Microservices

44. Adopting Microservices at AO.com
Jon Vines, Lead Digital Architect
Software Engineer and Team Lead

45. @_jonvines@_jonvines
adopting microservices at AO.com

46. @_jonvines
talking about…
• talk a little bit about who we are
• definitions
• when to use microservices
• the role of data in a microservice
• microservice anti-patterns
• another way

47. @_jonvines
Jon Vines
Software Engineer and Team Lead
Co-organiser DevOps Manchester
Loves reading, recommends:

48. @_jonvines@_jonvines

49. @_jonvines@_jonvines

50. @_jonvines
defining a monolith

51. @_jonvines@_jonvines

52. @_jonvines@_jonvines

53. @_jonvines
microservices

54. @_jonvines
path to microservices

55. @_jonvines
data in a microservice

56. @_jonvines@_jonvines

57. @_jonvines
domain driven design - bounded contexts

58. @_jonvines

59. @_jonvines
accessing data in a microservice

60. @_jonvines
avoiding future data silos

61. @_jonvines
sharing data in a database

62. @_jonvines
request/response

63. @_jonvines
events

64. @_jonvines
events as the source of truth

65. @_jonvines
service owned materialised views

66. @_jonvines
the role of your data store
within a microservice

67. @_jonvines
rapid schema development
and easy evolution

68. @_jonvines
low operational overhead

69. @_jonvines
easy to deploy and manage

70. @_jonvines
Our choice …

71. @_jonvines
microservice anti-patterns

72. @_jonvines
our services have more than
one reason to change

73. @_jonvines
we need to deploy more than
one service at a time

74. @_jonvines
our service should be a
vertical slice of functionality

75. @_jonvines
all of our data is in the same database

76. @_jonvines@_jonvines

77. @_jonvines
a services’s data is being accessed
by other services directly

78. @_jonvines
can we do even better?

79. @_jonvines

80. @_jonvines
why Serverless?
scales ● resilient ● secure ● cheaper

81. @_jonvines
code footprint is much smaller

82. @_jonvines
event driven by design

83. @_jonvines
spend more time solving business problems

84. @_jonvines

85. @_jonvines@_jonvines

86. @_jonvines

87. @_jonvines
Still pulling data out of MSSQL
using CDC

88. @_jonvines
Still pulling data out of MSSQL
using CDC
Prepare events using KSQL

89. @_jonvines

90. @_jonvines
Prepare events using KSQL
Still pulling data out of MSSQL
using CDC
The push to S3 allows us to
trigger lambdas within AWS

91. @_jonvines
The push to S3 allows us to
trigger lambdas within AWS
We derive materialised views for
our read APIs in MongoDB
Still pulling data out of MSSQL
using CDC
Prepare events using KSQL

92. @_jonvines
We repeat the cycle using the
change streams or first class
events from the new materialsed
views

93. @_jonvines
think event driven

94. @_jonvines
build fast view layers in MongoDB

95. @_jonvines
experiment with new business ideas
and validate learnings

96. @_jonvines
what have we achieved?

97. @_jonvines

98. @_jonvines
20+ services running in
production (team owned)

99. @_jonvines
deploy on-demand
within 30 minutes of code-commit

100. @_jonvines
run integration tests against
specifically provisioned MongoDB instances
on demand

101. @_jonvines
respond and fulfil GDPR requests in seconds

102. @_jonvines
identify new business accounts in
seconds rather than days

103. @_jonvines
capture visitor click-stream as it’s happening to
provide personalised experience

104. @_jonvines
Recap
• defined monolith and microservice
• when to use microservices
• the role of data in a microservice
• microservice anti-patterns
• the future is serverless

105. @_jonvines@_jonvines
thank you

106. Accelerating Microservices Development with
MongoDB Atlas and Stitch
Jim Blackhurst, Principal Solutions Architect
jim@mongodb.com

107. Consider the following…
Multiple Data Sources (Systems of Record)
Applications / Channels (Web, Mobile)
Operational Data Layer /
Data Persistence / Read-Write
Change Data Capture
Messaging / ETL
Data Access Layer
Microservices
“Microservices”

108. Consider the following…
Multiple Data Sources (Systems of Record)
Applications / Channels (Web, Mobile)
Operational Data Layer / Data Persistence / Read-Write
Change Data Capture
Messaging / ETL
Data Access Layer
Microservices
As a Service
MongoDB Stitch
MongoDB Atlas

109. Demo

110. Thank you
Jim Blackhurst, Principal Solutions Architect
jim@mongodb.com

111. Closing
Dominic Wellington, Director, Field Initiatives & Readiness
Dominic.wellington@mongodb.com
#AO.com #MongoDB #Cloud #Microservices

112. $100 Atlas voucher for those who complete the above
survey…
bit.ly/mongodb-ao

113. Where Europe’s fastest growing database community
comes to connect, explore, and learn.
USE CODE: A050 (£50 reduced from £199)
MongoDB.local London
2019

114. Q&A
#AO.com #MongoDB #Cloud #Microservices

115. DRINKS
NETWORKING
#AO.com #MongoDB #Cloud #Microservices