The document discusses various aspects of cluster management and container migration, focusing on continuous placement and live migration methods using Apache Mesos and CRIU. It highlights limitations within the Mesos framework's scheduling health API and the challenges faced by existing open-source solutions like Netflix's Fenzo. The architecture of Layer X and proposed solutions for optimizing resource and task scheduling are also briefly mentioned.

1. 1
LAYER X
IDIT LEVINE

2. 2
INSPIRATION

3. 3
INSPIRATION
VM
Brain
Migration Tool
Virtual machine clusters have a
scheduler that continuously monitors
the physical location of the
machines, and initiate migration if
the its benefit exceeds its cost.

4. 4
CLUSTER MANAGEMENT
Docker Swam
kubernetes
Diego
Mesos
Frameworks
Today, none of the leading cluster management solutions implements “continuous placement”

5. 5
MIGRATION
Migration in containers: killing the
Container on one machine and starting
a new one on the other machine.
Live migration in containers: using
Project CRIU (checkpoint restore in
userspace). Via CRIU we can write
the state of the container to the
disk (checkpoint) and restore it on
another machine.
Migration
Live
Migration

6. 6
PLACEMENT OPTIMIZATION
Continuous placement: evaluate the placement
in the cluster and reshuffle as needed.

7. 7
ARCHITECTURE

8. 8
APACHE MESOS: ARCHITECTURE
Machines are registered
to Mesos master.
Mesos manages the
cluster, and offers
resources to the
frameworks.
The frameworks can
either accept or reject
offers.

9. 9
APACHE MESOS: FRAMEWORK
Scheduling
Health
API

10. 10
APACHE MESOS: FRAMEWORK
Scheduling
Health
API

11. 11
APACHE MESOS: FRAMEWORK
Scheduling
Health
API
A framework makes a
decision to either accept or
to decline an offer based
only on information
pertaining to its own status,
with no information about
other frameworks.

12. 12
APACHE MESOS: FRAMEWORK
Scheduling
Health
API
Status update is being invoke
incase of lost task. The
framework will be responsible
to spin up a new task.

13. 13
LIMITATIONS

14. 14
APACHE MESOS: LIMITATIONS
Scheduling
Health
API
A framework makes a
decision to either accept or
to decline an offer based
only on information
pertaining to its own status,
with no information about
other frameworks.

15. 15
APACHE MESOS: LIMITATIONS
Can a user schedule
tasks from different
frameworks on the
same slave?
Not really.

16. 16
APACHE MESOS: LIMITATIONS
Reservations in Mesos
are based on prioritizing
frameworks, rather than
individual tasks.
5% 80% 10% 5%

17. 17
OSS SOLUTIONS

18. 18
NETFLIX OOS: FENZO
This solution is hard to
integrate into existing
frameworks, and will not
work with multi
frameworks.

19. 19
SOLUTION

20. 20
LAYER X: ARCHITECTURE
LAYER X

21. 21
LAYER X: MULTI BRAINS

22. 22
LAYER X: ARCHITECTURE
LAYER X

23. 23
LAYER X: ARCHITECTURE
LAYER X

24. 24
LAYER X: ARCHITECTURE
LAYER X

25. 25
USE CASES

26. 26
LAYER X: ARCHITECTURE
LAYER X

27. 27
LAYER X: ARCHITECTURE
LAYER X

28. 28
LAYER X: ARCHITECTURE
LAYER X
Resource Provider Interface
Task Provider Interface
CORE

29. 29
LAYER X: ARCHITECTURE
LAYER X
Resource Provider Interface
CORE
Task Provider Interface

30. 30
LAYER X: ARCHITECTURE
LAYER X
Resource Provider Interface
Task Provider Interface
CORE

31. 31
LAYER X: ARCHITECTURE
LAYER X
Task Provider Interface
CORE
Resource Provider Interface

32. 32
LAYER X: ARCHITECTURE
US-WEST-1 US-EAST-1
LAYER X

33. 33
LAYER X: ARCHITECTURE
LAYER X

34. 34
SUMMARY

35. 35
THE STACK
Resources
manager
Scheduler
Cluster
Manager
Platform as
a Service

36. 36
EMC-Advanced-Dev
http://www.github.com/emc-advanced-dev
Idit Levine
CTO of Cloud Platform Team &
Office of the CTO, EMC
@idit_levine
Scott Weiss
Software Engineer, EMC
@ilackarms
Yuval Kohavi
Software Engineer, EMC
@uvgroovy

37. 37
@Idit_Levine

38. 38