The document discusses the integration of Apache Flink with Apache Mesos and DC/OS for real-time data processing and analytics. It highlights the benefits of this architecture, including fault tolerance, scalability, and resource allocation efficiency. The presentation concludes with a demo showcasing how financial data is processed through Kafka and Flink within this ecosystem.

1. Till Rohrmann
till@data-artisans.com
@stsffap
Apache Flink® Meets
Apache Mesos® and DC/OS
Jörg Schad
joerg@mesosphere.io
@joerg_schad

4. MapReduce is
crunching Data

5. We need to turn faster!

6. Evolution of Data Analytics
Batch Event ProcessingMicro-Batch
Days Hours Minutes Seconds Microseconds
Solves problems using predictive and
prescriptive analytics
Reports what has happened using descriptive
analytics
Predictive User InterfaceReal-time Pricing and
Routing
Real-time
Advertising
Billing,
Chargeback
Product
recommendations

7. FMACK Stack
EVENTS
Ubiquitous data
streams from
connected devices
INGEST
Apache
Kafka
STORE
Apache
Flink
ANALYZE
Apache
Cassandra
ACT
Akka
Ingest millions of
events per second
Distributed & highly
scalable database
Real-time and batch
process data
Visualize data & build
data driven apps
Mesos/ DC/OS
Sensors
Devices
Clients

8. Datacenter

9. Naive Approach
Typical Datacenter
siloed, over-provisioned servers,
low utilization
Industry Average
12-15% utilization
mySQL
microservice
Cassandra
Flink
Kafka

10. © 2017 Mesosphere, Inc. All Rights Reserved. 10

11. Apache Mesos
Typical Datacenter
siloed, over-provisioned servers,
low utilization
Industry Average
12-15% utilization
mySQL
microservice
Cassandra
Flink
Kafka
Mesos
automated schedulers, workload multiplexing
onto the same machines

12. Apache Mesos
Why Mesos?
! 2-level scheduling
! Fault-tolerant, battle-tested
! Scalable to 10,000+ nodes
! Created by Mesosphere founder
@ UC Berkeley; used in production
by 100+ web-scale companies [1]
[1] http://mesos.apache.org/documentation/latest/powered-by-mesos/

13. Apache Flink & Apache Mesos

14. Why Apache Mesos?
▪ Mesos offers full functionality to implement fault
tolerant and elastic distributed applications
▪ 30% of survey respondents were running Flink
on Mesos (prior to proper Mesos support,
September 2016)

15. Flink’s Mesos Integration
Apache Flink Framework
Mesos Master
Mesos App Master
Flink Mesos
ResourceManager
JobManager
Mesos Task
TaskManager
Mesos Task
TaskManager
Allocate
Resources
Launch Mesos
tasks
Register
Execute Job

16. Resource Manager Components
▪ Monitors connection to Mesos
Connection Monitor Launch Coordinator
▪ Resource offer processing and task
scheduling
▪ Gathers offers and matches them to
tasks using Fenzo
Task Monitor
Reconciliation
Coordinator
▪ Monitors Mesos tasks
▪ Triggers reconciliation
▪ Makes sure tasks are properly killed
▪ Reconciles tasks view between
ResourceManager and Mesos Master

17. Component Interplay
ResourceManager
Connection
Monitor
Launch
Coordinator
Task MonitorReconciliation
Coordinator
Mesos Master
Resource offers
Launch
tasks
Monitor tasks
Status
messages
Trigger
reconciliation
Status messages
Mesos Task
Reconcile tasks
Start
TaskManagers
Recover tasks
Kill task

18. Fenzo
▪ Generic task scheduler for Mesos frameworks
▪ Developed by Netflix
▪ Matching between tasks and resource offers
▪ Pluggable fitness evaluator
Fenzo
Mesos
Launch
Coordinator
Periodic
resource
offers
Tell Fenzo offered
resources & tasks
Fenzo returns resource
task matchings
Tasks to launch

19. New Distributed Architecture
Mesos Master
Mesos Cluster
Client
(2) HTTP POST
JobGraph/Jars
Flink Master Process
Flink Mesos
ResourceManager
JobManager
(4) Start Process
(and supervise)
(8) Deploy
Tasks
(7) Register
(5) Request slots
Flink Mesos
Dispatcher
(3) Allocate
container
for Flink
master
(6) Allocate
containers
for TaskManagers
Marathon
(1) Start and
monitor
dispatcher
Mesos Task
TaskManager
Mesos Task
TaskManager

21. DC/OS
Datacenter Operating System (DC/OS)
Distributed Systems Kernel (Mesos)
Big Data + Analytics EnginesMicroservices (in containers)
Streaming
Batch
Machine Learning
Analytics
Functions &
Logic
Search
Time Series
SQL / NoSQL
Databases
Modern App Components
Any Infrastructure (Physical, Virtual, Cloud)

22. Demo Time
Generator
▪ Financial data generated by generator
▪ Written to Kafka topics
▪ Kafka topics consumed by Flink
▪ Flink pipeline operates on Kafka data
▪ Results written back into Kafka

23. Conclusion

24. TL;DL
▪ Apache Flink runs on Mesos using Fenzo
▪ New distributed architecture supports
dynamic resource allocation
▪ DC/OS offers easy to use Flink package

25. 25
Thank you!
@joerg_schad
@stsffap
@ApacheFlink
@dataArtisans
@dcos

26. We are hiring!
data-artisans.com/careers