The document discusses current challenges faced by businesses in leveraging data and providing seamless customer experiences, particularly during a crisis that has increased demand for online services. It highlights the need for scalable cloud solutions and the importance of modern architectures like event-driven systems, supported by technologies from Confluent and MongoDB. Joint case studies illustrate how organizations in various sectors, including healthcare and finance, successfully implemented these technologies to improve operational efficiency and responsiveness.

1. Stream me to the Cloud (and
back) with Confluent & MongoDB
Felix
Reichenbach
MongoDB
Gianluca
Natali
Confluent

2. Agenda
Current Challenges
A Cloud Story
Solution Presentation & Architecture
Demo
Joint use cases & Customer references

3. Current Challenges

4. Business Challenges
Provider needs:
- Tap new revenue streams to stay
competitive
- Scale with the demand and keep
TCO low
- Continuously evolve and improve
user/customer experience
Customer wants:
- Consume services anywhere and
anytime
- Omnichannel with seamless
transition (Mobile <-> Browser)
- Fast response times and Real Time
Interactions (Notifications, Status
Updates, Confirmations…)

5. Technical Challenges
Made worse by this crisis:
- Scaling for peak hours requires
heavy overprovisioning
- Purchasing Hardware may not be
possible
- Mobility of personnel is limited
Evergreen problems:
- Making use of data is very difficult
- Data is spread across many
applications / domains
- Low latency access is almost
impossible
- Agile development methodologies
cannot be applied

6. Common Initiatives
● Application Modernization
● Microservices Architectures
● Single View of XYZ
● Real-time Analytics
● Content Management
● IoT
● ...
Across Verticals:
Healthcare
Financial Services
Telco
Technology
Retail
Manufacturing / Automotive

7. a retail story...
AllGoodThings Inc.

8. Our Meetings
are changing...
By now probably everyone
of us had experienced a
crowded business video
call from home.
Let me introduce you to
the Conference call
Bingo!
😀

9. CEO CTO
CFO
● Our online store had 2 main outages last
week
● Surge in Customers complaints and
escalation are a concern
● We are unable to add/change products
as fast as we’d like
● 600% increase in overall traffic to website
● A tweet with a link to an hand sanitizer
product in our store went viral
● Adding a product requires downtime that
we can’t afford with current queue setup
Customer Success Head of Eng.
CMO
● Outages due to lack of resources in DC
● Our DBs is cracking under load.
● We limited concurrent users to stay online
● Need to triple our DC to support peak load
● Health category has skyrocketed to #1
● “Home office” and “Fitness” are
trending upwards
● People can’t visit our shops, all the
business moved to our online store
● #1 Complaints: “Item was successfully
ordered and paid but then received email
that is unavailable”,
● #2 Complaint: “Can’t access the website,
I am stuck in queue”
● Our Support team is working double
shifts, we need to grow the team ASAP
● DC: We can’t triple our DC size, the ROI
doesn’t work. We need to maintain our
margins
● Support: Can we establish more efficient
processes and automate concierge/triage
via support app or Chat bot?
● I can’t approve your requests as they are
AllTheGoodThings Inc.

10. Meeting Conclusion / Requirements
● Fix the scalability issue while limiting the investment on our DC.
● Leverage public Cloud services to reduce TCO.
● Explore the feasibility of an app to allow automatic resolution of
simple customer queries
● Increase agility in adding products
● Provide real time stock information

11. a few days later...
Solution Overview

12. Eng.CEO CTOCS CMOCFO
● Dynamic Scalability
● High Availability
● Increased Agility
● Avoid Lock In
● ...

13. Event Driven Architectures

14. Eng.CEO CTOCS CMOCFO

15. ETL/Data Integration Messaging
Batch
Expensive
Time Consuming
Difficult to Scale
No Persistence After
Consumption
No Replay
Highly Scalable
Durable
Persistent
Ordered
Real-time

16. ETL/Data Integration Messaging
Batch
Expensive
Time Consuming
Difficult to Scale
No Persistence After
Consumption
No Replay
Highly Scalable
Durable
Persistent
Ordered
Real-timeHighly Scalable
Durable
Persistent
Ordered
Real-time
Event Streaming

17. Today

18. Real-Time
Inventory
Real-Time
Fraud
Detection
Real-Time
Customer 360
Machine
Learning
Models
Real-Time
Data
Transformation
...
Contextual Event-Driven Applications
Universal Event Pipeline
Data Stores Logs 3rd Party Apps Custom Apps/Microservices
TREAMSSTREAMS
CONNECT CLIENTS
With
Event
Streaming
and
Kafka

19. Agility and Scalability
with MongoDB

20. Eng.CEO CTOCS CMOCFO

21. Isolated data in many different
applications / domains and structures

22. 22
Data which is accessed together, is stored together...
Customer Product Contact
Pricing Phone Phone
Objects
Tables isolated in several applications and domains
Lead
NameNameParts
ARR Address Contact Roles
SummaryCustomer Detail Specs
How to build a flexible and scalable operational data store??

23. 23
RDBMS vs. Flexible Data Model
Relational MongoDB
{ customer_id : 3,
first_name : ”Danilo",
last_name : ”Nobrega",
city : ”Stockholm",
phones: [
{
number : “46-64-223-9828”,
dnc : true,
type : “home”
},{
number : “46-173-555-
12144”,
type : “cell”
}]
}
Customer ID First Name Last Name City
0 Jonah Rosenboom Hamburg
1 Tim Schojohann München
2 Boris Bialek Zürich
3 Danilo Nobrega Stockholm
4 Ingo Marienfeld Düsseldorf
Phone Number Type DNC Customer ID
49-69-223-9828 home T 3
49-69-143-45986 home T 0
49-173-555-12144 cell (null) 3
49-69-777-1212 home T 1
49-175-698-1213 cell (null) 1
49-162-767-444 cell F 2

24. 24
The document model is the perfect fit because it is...
Easy:
Work with data in a
natural, intuitive
way, fully
transactional
Flexible:
Adapt and
make changes
quickly
Fast:
Get great
performance
with less code
Versatile:
Supports a
wide variety of
data models
and queries

25. 25
Multiple data models, rich query functionality...
Rich Queries
Point | Range | Geospatial | Faceted Search | Aggregations | JOINs | Graph Traversals
JSON Documents Tabular Key-Value Text GraphGeospatial

26. 26
Mobile App with
MongoDB Realm
Personalized
Marketing
Campaign
Analytics
Real-Time Online
Data Store
MongoDB Data Platform
Real Time
Data Sync
SPA with
MongoDB
Stitch

27. Freedom of Choice: Run wherever you need
Private Cloud
Deploy and self manage on premises
Deploy via Kubernetes with Kubernetes
Operators
Multi- Cloud / PaaS
Build on top of fully managed services
Leverage horizontal and vertical
elasticity
Avoid cloud provider lock-in
Hybrid Cloud
Deploy a homogeneous technology
stack across on-prem and cloud.
Reduce complexity and avoid lock-in

28. Joint Reference Architecture
Reference Architecture: https://www.confluent.io/resources/confluent-platform-reference-architecture-mongodb/

29. DEMO

30. Joint References

31. Centene, Healthcare Provider
Centene has the largest medicare and medicaid managed
care providers
Challenge
Centene’s Core Challenge is growth
caused by Mergers & Acquisitions
This caused them to reevaluate their
Enterprise Data Integration and Data
Migration Strategies…They wanted
better scalability, availability, faster ETL
Solution
Build centralized eventing
framework for enterprise use
across all Centene domains
Employing CDC for ingest and
leveraging microservices using
Confluent, Kafka, and MongoDB

32. Financial Services - a large global bank
Leading global financial services firm, a major provider of various investment banking,
retail banking and financial services.
Challenges
Need for centralized incident and event
management solution
Modernize legacy applications
Provide complete health dashboards
across various systems
Streamline payment processing,
customer activity tracking and real-time
data integration across the bank
Solution
The bank implemented a secure logging platform
running Kafka as a service and MongoDB databases
The environment has over 80 clusters and supports
data volumes between 200TB and 1PB per day
Data collection and normalization is at the edge and
data is replicated back to two central data centers
for global reporting and trend analysis

33. Modernized security information and event management
Filter, transform
aggregate
APP SIEM
Index
Search
Curated streams
Forensic
Archive
MongoDB
CDC
Syslog
Network traffic
Firewall logs
RDBMS
Application logs
Sensor Data
HTTP proxy logs
QRadar
Arcsight
Splunk
Elastic

34. Front, rear and top
view cameras
Parking assistant
Environment pointer
Ultrasonic Sensors
Parking assistant with
front and rear camera plus
environment indicator
Crash Sensors
Front protection adaptivity
Side protection
Tail impact protection
Front Camera
Audi Active lane assistant
Speed limit indicator
Adaptive light
Infrared Camera
Rearview assistance with
Pedestrian recognition
Front and Rear
Radar Sensors
ACC with stop and go function
Side assist
Real time data cluster

35. Real-Time Monitoring
Logs
Reference
data
(monitoring)
CDC
Syslog
MQTT
APP
Filter, transform
aggregate SIEM
Search
Aggregated event data
/ curated streams
iOT
iOT
iOT
Kafka Streams/ksqlDB

36. Modernize your architectures with Confluent and MongoDB
A new generation of technologies is needed to consume and exploit today's real
time, fast moving data sources. Run your business in real-time, building real-time
applications with historical context.
Together, Confluent and MongoDB enable you to
● Build sophisticated data-driven and event-driven applications
● Modernize your application architecture
● Uncover new sources of data
● Derive insights for a competitive advantage
&
Accelerate your Journey to the Cloud
and back! 😉

37. Driving innovation and remaining
operational in uncertain times
Koen Rousseau, Digital Lead,
Sanoma Learning Online Education
Tomorrow
10:30am CET
Tim Nutman, Manager Solutions
Architecture, MongoDB
mongodb.com/webinars

38. Thank You!
felix@mongodb.com gnatali@confluent.io