Presentations from the London Cloud Data Strategy event in London on Wednesday 14th March 2018.

1. ACCELERATING A PATH TO DIGITAL
WITH A CLOUD DATA STRATEGY
Wednesday 14th March 2018

2. WELCOME & INTRODUCTION
Daniel Barrett, Vice President UK&I
daniel@mongodb.com

3. 3
SPEAKERS
Accelerating a Path to Digital with a Cloud Data Strategy
DANIEL BARRETT
MAT KEEP
SION O’HARE
VICE PRESIDENT, UK&I
MONGODB
HEAD OF ONLINE SERVICES
TELEFÓNICA/02
DIRECTOR OF PRODUCT
MONGODB
SENIOR SOLUTIONS ARCHITECT
MONGODB
MOSTAFA ZAKARIA

4. EXECUTING ON A CLOUD DATA STRATEGY
Mat Keep, Director, Product Team
mat.keep@mongodb.com
@matkeep

5. Mainframe Client-Server Web
Control & Efficiency AGILITY & INNOVATION
Cloud & Mobile
Distributed Systems
1980s Late 90s – 2000s 2015>1960s-70s
The Cloud Age
Generational Shift

6. Seismic Shifts — Organizational

7. Seismic Shifts — Application Architecture

8. Why do I need to rethink my underlying data
layer…..?
Architectural
affinity
Geo-locality Rapid, iterative
changes

9. API Access Layer
Operational Data
Customers
Products
Accounts
ML Models
Shared Physical Infrastructure
App1 App2 App3
1.Development agility
2.Corporate governance
3.Data re-use
Cloud Data Strategy
Standardized, on-demand database service
Cloud Portable
Any Cloud, Any Where

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

11. MongoDB – Freedom To Run Anywhere
Database that runs
the same everywhere
Coverage in any
geography
Leverage the benefits
of a multi-cloud
strategy
Avoid lock-in
Mainframe
Database as a service
ServerLaptop Self-managed in the cloud

12. Private Cloud

13. 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:
Virtualization
Strategy
Step 2:
Hardware & OS
Selection
Step 9:
Cost Accounting &
Chargeback
Step 10:
Design Reviews
Discovery
Design
Deploy

14. 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

15. Data Fabric
Multi-tenant PaaS
Exposing APIs for data streaming and
storage
Cloud native, self-service
Modern, industry standard, open source
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&Audit
Data Fabric

16. 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 applications
Simplification
• 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

17. Database on Public Cloud

18. 18
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

19. 19
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

20. 20
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

21. MongoDB Atlas
Managed DatabaseAs A Service For MongoDB
• Run for You
• Resilient & Secure
• Multi-Cloud

22. 22
MongoDB Atlas unlocks agility & reduces cost
Self-service, elastic,
and automated
Global and highly
available
Secure by default
Comprehensive
monitoring
Managed disaster
recovery
Cloud agnostic

23. MongoDB Atlas Powering
Microservices Architecture
Problem Why MongoDB ResultsProblem Solution Results
Over 35 different apps accessed by
10,000+ unique customers on AWS
Each experiment produces millions of
“rows” of data, which led to suboptimal
performance with incumbent databases
RDS & Aurora slow, added code
complexity
DynamoDB limited query functionality &
expensive
MongoDB Atlas managed
database service
Flexible document model allows
storage of multi-structured data
Expressive query language and
secondary indexes allow ad-hoc
analysis of experiment data
Scalability to handle growing data
volumes
Thermo Fisher customers now obtain
real-time insights from mass
spectrometry experiments from any
mobile device or browser; not possible
before
Improved developer productivity with
40x less code, improved performance
by 6x
Easy migration process & zero
downtime. Testing to production in
under 2 months

24. Cloud Data Strategy:
Wrapping Up

25. 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

26. MONGODB 4.0:
MULTI-DOCUMENT
ACID TRANSACTIONS

27. SAFE HARBOUR STATEMENT
This presentation contains “forward-looking statements” within the meaning of Section 27A of the
Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as
amended. Such forward-looking statements are subject to a number of risks, uncertainties, assumptions
and other factors that could cause actual results and the timing of certain events to differ materially from
future results expressed or implied by the forward-looking statements. Factors that could cause or
contribute to such differences include, but are not limited to, those identified our filings with the
Securities and Exchange Commission. You should not rely upon forward-looking statements as
predictions of future events. Furthermore, such forward-looking statements speak only as of the date of
this presentation.
In particular, the development, release, and timing of any features or functionality described for
MongoDB products remains at MongoDB’s sole discretion. This information is merely intended to
outline our general product direction and it should not be relied on in making a purchasing decision nor
is this a commitment, promise or legal obligation to deliver any material, code, or functionality. Except
as required by law, we undertake no obligation to update any forward-looking statements to reflect
events or circumstances after the date of such statements.

28. MongoDB: Already Used Across Every
Industry and Use Case...
eCommerce
Travel Graph &
Recommendation System
Analytics
Internet of Things
Product Catalog
Artificial Intelligence
Digital Transformation
Drug Sequencing
Gaming
Single View
Mobile
Database as a Service
...without multi-document ACID transactions

29. DATA MODELS AND TRANSACTIONS
Relational Database
Related data split across multiple records and tables.
Multi-record transactions essential
Different databases take different approaches
Document Database
Related data contained in a single, rich document.
Transaction scoped to the document

30. MULTI-DOCUMENT TRANSACTION EXAMPLES
Finance
Account debit/credit
Retail
Insert orders, decrement inventory
Telco
Insert call detail, update
subscriber’s plan

31. MONGODB MULTI-DOCUMENT TRANSACTIONS
Just like relational transactions
● Multi-statement, familiar relational syntax
● Easy to add to any application
● Multiple documents in 1 or many collections
ACID guarantees
● Snapshot isolation, all or nothing execution
● No performance impact for non-transactional
operations
Schedule
● MongoDB 4.0, Summer ‘18: replica set
● MongoDB 4.2: extended to sharded clusters

32. OUR JOURNEY TO ACID TRANSACTIONS
Major engineering investment over 3+ years touching every part of
the server and drivers
● Storage layer
● Replication consensus protocol
● Sharding architecture
● Consistency and durability guarantees
● Global logical clock
● Cluster metadata management
● Exposed to drivers through API enhancements
We’re 85% done…...

33. SUMMARY: MONGODB UNIQUELY DELIVERS…...
Scale-out, data locality, and
resilience of distributed systems
ACID transactional guarantees
of relational databases
Developer productivity
of document databases
Freedom to Run Anywhere

34. JOURNEY INTO THE CLOUD
CLOUD EXPLORERS
Sion O’Hare, Head of Online Services
Telefónica

35. Journey into the Cloud
Cloud explorers_
Sion O’Hare
Head of Online, Integrate & Cloud Services
Telefónica
Telefonica
14.03.2018

36. 36
Telefónica is one of the largest telecommunications companies in the
world by market capitalization and number of customers providing a
comprehensive offering and quality of connectivity that is delivered
over world class fixed, mobile and broadband networks.
We run operations in 17 countries, split into two geographic regions:
Europe and Latin America. We have 350 million customers out of
which more than 276 million are mobile, over 9 million fiber/cable
customers and more than 8 million pay TV customers
Telefonica
Our Story_

37. 37
We are building a powerful data-house, evolving each one of our assets and combining
around 4 Platforms. Video from 2018 MWC @ LINK
– with one clear focus: to put them to work at the service of our customers.
Telefonica
Our business model_
- Harmonise client information across our
platforms and transform into knowledge
- Focused on digital services our
differentiated offer takes advantage from
our physical assets & systems.
- Enabled real-time, automated end to end
support & commercial systems, digitize out
customer orientation
- Our physical estate from Network base
stations to high street stores, generates
real time customer relevant data
Markets_
Spain
UK
Germany
Hispam North
Hispam South
Brasil

38. 38
Value
Agility
Cost
Security
Legacy
Security
Network
Infrastructure
Access
Tooling
IaaS
Saas
PaaS
DaaS
VPC
On Premise
% of estate / Total Data
Costs
Security
Performance
Compliance
GRAPH 1
Operation Measure
Adoption
Framework
Cloud First in the UK
2017 Cloud explorers_
Placement
Foundation
Set Direction
Mobilise
Prove
Review & Repeat
Channels Virtualisation
- £1.3m Infrastructure
- HW Hosting/Sup. halved
BDaas
PaaS/IaaS+
IaaS
On Premise/Hybrid/VPC
On Prem

39. 39
Cloud first strategy
Atlas DBaaS
Our journey_
Community Open
Source adoption
Tactically
implemented by local
teams with no
strategic intent.
On Premise
V2.2.1
Out of support
On Premise
2 DBs / V2.6.9
Vendor Support / version level
Public Cloud
14 DBs / V3.2.8 and V3.6.0
DBaaS
Atlas
POC
Virtualisation programme requiring
BDs to be upgraded to min version x.x

40. 40
Atlas DBaaS
Telefonica UK_ 2 Environments (Production & Non Production)
2 Replica sets & 6 DB instances
O2 ASK
Application Environment SDLC-Cycle Replica Set
Aura
Non
Production Reference 1 Replica set with 3 members
Production Production 1 Replica set with 3 members
Total 2 Replica sets
Component Version
Cloud Provider AWS
Region Ireland (eu-west-1)
Instance Type M10 (2GB RAM, 10GB storage)
MongoDB Version 3.4

41. 41
Atlas DBaaS
Telefonica UK_
2 Environments (Production & Non Production)
6 Replica sets & 18 DB instances
Access
&
Registration
Application Environment SDLC-Cycle Replica Set
Messaging
Non
Production Reference 1 Replica set with 3 members
Performance 1 Replica set with 3 members
Production Production 1 Replica set with 3 members
Total 3 Replica sets
Application Environment SDLC-Cycle Replica Set
Identity
Non
Production Reference 1 Replica set with 3 members
Performance 1 Replica set with 3 members
Production Production 1 Replica set with 3 members
Total 3 Replica sets
Component Version
Cloud Provider AWS
Region Ireland (eu-west-1)
Instance Type
M20 (4GB RAM, 20GB storage)
M60 (64GB RAM, 320GB storage)
MongoDB Version 3.2 / 3.4

42. 42
Atlas DBaaS
Telefonica UK_
Priority
O2
Component Version
Cloud Provider AWS
Region Ireland (eu-west-1)
Instance Type
M10 (2GB RAM, 10GB storage)
M20 (4GB RAM, 20GB storage)
MongoDB Version 3.6.1
Application Environment SDLC-Cycle Replica Set Version
Non production Dev 3 Replica sets with 3 Instances v3.6.1
Non production Test 3 Replica sets with 3 Instances v3.6.1
Non production Perf 3 Replica sets with 3 Instances v3.6.1
Non production Stage 3 Replica sets with 3 Instances v3.6.1
Production Prod 3 Replica sets with 3 Instances v3.6.1
Total 15 Replica sets & 45 Instances v3.6.1
12 services
5 Environments (Production & Non Production)
15 Replica sets & 45 DB instances

44. LANDING IN THE CLOUD
MIGRATING FROM RELATIONAL, ON PREMISES TO MONGODB IN THE CLOUD
Mostafa Zakaria, Senior Solutions Architect
mostafa@mongodb.com

45. LANDING IN THE CLOUD
Migrating from Relational, On Premises, to MongoDB in the Cloud.

46. AGENDA
• What’s so Hard about Data Migration?
• Crossing the Idiomatic Divide.
• How to Get MongoDB Off the Ground.
• Why MongoDB Atlas?

47. WHAT’S SO HARD ABOUT DATA MIGRATION?

48. WHAT’S SO HARD ABOUT DATA MIGRATION?
1. Apply for ESTA
2. Identify Travel Dates
3. Search for Available Flights
4. Book and Confirm Flights
5. Search for Accommodation
6. Reserve Accommodation
7. Ensure Cat is Adequately
Fed/Sedated
8. Pack Bags
9. Check-In Online
10.Identify best way of going to
Airport.
11.Go to Airport
12.Locate Bag Drop
13.Tag and Drop of Bags
14.Go through Security
15.Identify and Locate Gate
16.Wait for Boarding
17.Board and Go to Seat
18.Identify and Locate Gate
19.Wait for Boarding
20.Identify Seat
21.Read Book/Watch Movies
22.Survive Landing
23.Go through Immigration
24.Collect Baggage
25.Locate Mode of Transportation
26.Go to Accommodation
27.Locate and Go to Rooms
28.Unpack Baggage
29.Decide What to do…

49. WHAT’S SO HARD ABOUT DATA MIGRATION?
Then A Miracle
Occurs!
[Insert Product Placement Here]

50. WHAT’S SO HARD ABOUT DATA MIGRATION?
• Data Migration doesn’t just Happen.
• Data Migration is not just Copying the Data.
• Data Migration requires Understanding the Data.
• Data Migration is a Data Discovery & Data Quality Project.
• Data Migration process must be Repeatable.

51. CROSSING THE IDIOMATIC DIVIDE
Hello
!

52. CROSSING THE IDIOMATIC DIVIDE
Tabular Document

53. CROSSING THE IDIOMATIC DIVIDE
Design Decision
Embedding
Referencing
1. Top Down vs. Bottom Up
2. Use Case / Access Patterns
3. Entity Relationships
4. Cardinality & Direction
5. MongoDB Document Size

54. HOW TO GET OFF THE GROUND

55. HOW TO GET OFF THE GROUND
Migrate existing deployments running anywhere
into MongoDB Atlas with minimal impact to your
application. Live migration works by:
● Performing a sync between your source
database and a target database hosted in
MongoDB Atlas
● Syncing live data between your source
database and the target database by tailing
the oplog
● Notifying you when its time to cut over to the
MongoDB Atlas cluster
Live Migration

56. HOW TO GET OFF THE GROUND
3rd Party Tools

57. WHY MONGODB ATLAS?
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
“You have 2 Choices…”

58. Morphia
MEAN Stack
Support for Popular Languages and Frameworks
DRIVERS & ECOSYSTEM

59. MONGODB CONNECTOR FOR BI
• Run analytical queries on live MongoDB data
• Can run against your primary or secondaries
• Runs on any server, or co-locate with your database
process for optimal performance
• BI Connector is also available in Atlas

60. All MongoDB Atlas nodes are single-tenant and deployed
into their own VPC for security isolation.
In-flight security:
● TLS/SSL for in-flight data encryption
● Authentication and authorization access controls with
SCRAM-SHA1
● IP whitelists
● VPC Peering
At-rest security:
● Encrypted storage volumes
● AES-256 (CBC mode) hardware encryption with
Seagate Self-Encrypting Drives
Under the hood
SECURE IN THE CLOUD

61. MongoDB 4.0: Multi-Document ACID
Transactions

62. Under the hood
Out-of-the-Box Operational Tooling
● Fine Grained Monitoring and Alerts
● Real-Time Performance Panel
● Data Explorer
● Query/Performance Optimization
● Continuous Backup/Point-in-Time Restore
● Query-able Backup
● Enterprise APM Integration
● Programmatic API Management

63. Highly Available by Default
Under the hood
● A minimum of three data nodes per replica
set/shard are automatically deployed
across availability zones for high
availability
● If your primary node does go down for any
reason, the self healing recovery process
in MongoDB Atlas will typically occur in
under 2 seconds
● BI Connector also available on Atlas

64. The Latest MongoDB Features
Under the hood
● MongoDB Atlas comes out-of-the-box with MongoDB
3.2 and MongoDB 3.4 available. When maintenance
releases become available, MongoDB Atlas will
automatically upgrade your cluster, using a rolling
process to maintain cluster availability at all times
● When new versions of MongoDB are released,
MongoDB Atlas will also allow you to make seamless
upgrades without risking downtime

65. FREEDOM TO RUN ANYWHERE

66. ELASTIC SCALABILITY & ON-DEMAND
PROVISIONING
Under the hood
● WiredTiger storage engine with compression and fine-
grained concurrency control to meet the most demanding
SLAs
● MongoDB Atlas supports automatic-sharding, giving you the
ability to scale up or out with no impact to your app
● MongoDB Atlas allows you to pick the shard key that best
suits your application needs
● All 10m+ MongoDB Atlas clusters are single-tenant and
deployed on servers allocated specifically to the cluster

67. REPLICATE DATA NEAR USERS

68. Integrated services and
functions for complex,
multi-stage workflows
Native SDKs for Android,
JS, and iOS apps
Direct Database Access
MongoDB Stitch