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Entropy: a Consolidation Manager for Clusters 
Fabien Hermenier1 Xavier Lorca2 Jean-Marc Menaud1 Gilles Muller3 
Julia Lawall4 
1 ASCOLA group, ´E 
cole des Mines de Nantes 
2 Constraints group, ´E 
cole des Mines de Nantes 
3 INRIA-R´egal, ´E 
cole des Mines de Nantes 
4 DIKU, University of Copenhagen 
International Conference on Virtual Execution Environments, 
Washington D.C., March 12 2009
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Context 
Cluster environment 
Static allocation of the resources to jobs 
Resources are underused 
Static allocation of CPUs vs. dynamic utilization 
Dynamic Consolidation 
Each task of a job is embedded into a Virtual Machine (VM) 
Resources are allocated depending on tasks needs 
VMs are packed to be hosted on a reduced number of nodes 
VMs are re-packed when necessary with migrations 
2 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Challenge 
Issues 
Packing the VMs may require several migrations 
Some migrations have to be delayed to succeed. 
Temporary hosting may be necessary 
! Migrations take time 
! Performance degrades 
Reactivity is essential 
3 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Our proposal 
Entropy 
A dynamic consolidation manager for clusters, 
Plans the migration process 
Reduces the duration of the migration process to improve reactivity 
4 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
1 Design 
2 Packing the Virtual Machines 
3 Planning the migrations 
4 Minimizing the migrations 
5 Evaluation 
6 Conclusion 
5 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Global Design of Entropy 
A Configuration : 
Each VM is assigned on a node, 
Each VM requires a fixed amount of memory. 
VMs executing a computation are active and require a private CPU. 
May be viable 
Example 
6 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Global Design of Entropy 
Monitor 
Extract the current configuration : 
The position of each VMs and its CPU consumption 
An indication of which of the VMs are active and inactive 
7 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Global Design of Entropy 
Reconfiguration Algorithm 
VMPP - Compute a viable configuration using a minimum number 
of nodes 
VMRP - Plan and reduce the reconfiguration process if necessary 
7 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Global Design of Entropy 
Execution 
Decompose a plan into simple migrations 
Migrations orders are sent to the concerned VMM 
7 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
1 Design 
2 Packing the Virtual Machines 
3 Planning the migrations 
4 Minimizing the migrations 
5 Evaluation 
6 Conclusion 
8 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Packing the Virtual Machines 
Definition 
The Virtual Machines Packing Problem (VMPP) 
Compute the minimum number of nodes needed for a viable 
configuration 
Example 
(a) viable but non minimal (b) viable and minimal 
9 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Packing the virtual machines 
Approach 
Based on constraint programming, 
Each condition defining a viable configuration is a constraint. 
The constraint solver : 
Computes a viable configuration from the current one 
Reduces the number of used nodes until the minimum or a timeout. 
10 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
1 Design 
2 Packing the Virtual Machines 
3 Planning the migrations 
4 Minimizing the migrations 
5 Evaluation 
6 Conclusion 
11 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
Migrations have to be ordered 
Example 
Current Result 
12 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
Migrations have to be ordered 
Example 
(1) non-viable (2) 
12 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
Migrations have to be ordered 
Example 
(1) Ok (2) Ok 
12 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
Inter-dependant migrations require a pivot 
Example 
Current Result 
13 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
Inter-dependant migrations require a pivot 
Example 
Current non-viable 
13 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
Inter-dependant migrations require a pivot 
Example 
(1) (2) (3) 
13 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Planning a reconfiguration 
The Reconfiguration Plan 
Describes a viable reconfiguration process 
Migrations feasible in parallel are grouped into a step 
Steps are executed sequentially 
14 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
1 Design 
2 Packing the Virtual Machines 
3 Planning the migrations 
4 Minimizing the migrations 
5 Evaluation 
6 Conclusion 
15 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Reducing the reconfiguration process 
VMRP - Looking for an equivalent configuration 
Which is a solution of the VMPP 
Where its associated plan has a minimal ”cost” 
Method 
The cost of a plan is estimated using a migration cost model 
The VMRP computes equivalent configurations with ”cheap” 
reconfiguration plans until the minimum or a timeout. 
16 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Reducing the reconfiguration process 
Example 
(1) 
17 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Reducing the reconfiguration process 
Example 
(1) (2) (3) 
cost = 9 
17 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Reducing the reconfiguration process 
Example 
(1) (2) (3) 
cost = 9 
(1) (2) 
cost = 4 
17 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
1 Design 
2 Packing the Virtual Machines 
3 Planning the migrations 
4 Minimizing the migrations 
5 Evaluation 
6 Conclusion 
18 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Comparison against ”First Fit Decrease” 
Timeouts to have a non-trivial solution with Entropy estimated 
using random configurations : 
30 secs. for the packing 
35 secs. for minimizing the migrations 
The packing is equivalent or better. Small 
benefits for 42% of the configurations 
Cost of the resulting plan reduced by at 
least 90% 
Cost 
19 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Experiments on a cluster 
Environment 
1 node hosting the consolidation manager 
3 nodes for serving the VMs virtual disks 
35 nodes running a hypervisor 
35 VMs executing a collection of NASGrid Benchmarks 
Method 
All the benchmarks are launched at the same time 
Comparison between 
Static allocation without consolidation 
Dynamic consolidation using FFD 
Dynamic consolidation using Entropy 
20 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Experiments on a cluster 
Benefits 
Better reactivity 
Stable packing 
Reduced overhead 
Comparing the reconfigurations against FFD 
Cost : -90% 
Duration : -74% 
Nb of reconfigurations : x2 
21 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Experiments on a cluster 
Benefits 
Better reactivity 
Stable packing 
Reduced overhead 
Impact on the packing 
Smaller plans imply fewer pivots 
21 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Experiments on a cluster 
Benefits 
Better reactivity 
Stable packing 
Reduced overhead 
Impact on performance 
Overhead reduced by 9% 
Node per hour consumption 
reduced by 25% 
21 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
1 Design 
2 Packing the Virtual Machines 
3 Planning the migrations 
4 Minimizing the migrations 
5 Evaluation 
6 Conclusion 
22 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Conclusion 
The interest of the dynamic consolidation is limited by the 
duration of the reconfiguration process. 
Entropy 
Reducing the cost of a plan is an efficient solution to reduce its 
duration 
1 minute to compute a solution reduces the reconfiguration process 
by up to 8 minutes. 
Reduces the nodes per hour consumption by 25% as compared to 
FFD and the overhead by 9%. 
23 / 24 
Entropy: a Consolidation Manager for Clusters
Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 
Questions ? 
http ://entropy.gforge.inria.fr 
Binary and sources available on LGPL 
Uses the Xen Hypervisor and the ganglia monitoring system 
24 / 24 
Entropy: a Consolidation Manager for Clusters

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Entropy: a Consolidation Manager for Clusters

  • 1. Entropy: a Consolidation Manager for Clusters Fabien Hermenier1 Xavier Lorca2 Jean-Marc Menaud1 Gilles Muller3 Julia Lawall4 1 ASCOLA group, ´E cole des Mines de Nantes 2 Constraints group, ´E cole des Mines de Nantes 3 INRIA-R´egal, ´E cole des Mines de Nantes 4 DIKU, University of Copenhagen International Conference on Virtual Execution Environments, Washington D.C., March 12 2009
  • 2. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Context Cluster environment Static allocation of the resources to jobs Resources are underused Static allocation of CPUs vs. dynamic utilization Dynamic Consolidation Each task of a job is embedded into a Virtual Machine (VM) Resources are allocated depending on tasks needs VMs are packed to be hosted on a reduced number of nodes VMs are re-packed when necessary with migrations 2 / 24 Entropy: a Consolidation Manager for Clusters
  • 3. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Challenge Issues Packing the VMs may require several migrations Some migrations have to be delayed to succeed. Temporary hosting may be necessary ! Migrations take time ! Performance degrades Reactivity is essential 3 / 24 Entropy: a Consolidation Manager for Clusters
  • 4. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Our proposal Entropy A dynamic consolidation manager for clusters, Plans the migration process Reduces the duration of the migration process to improve reactivity 4 / 24 Entropy: a Consolidation Manager for Clusters
  • 5. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 1 Design 2 Packing the Virtual Machines 3 Planning the migrations 4 Minimizing the migrations 5 Evaluation 6 Conclusion 5 / 24 Entropy: a Consolidation Manager for Clusters
  • 6. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Global Design of Entropy A Configuration : Each VM is assigned on a node, Each VM requires a fixed amount of memory. VMs executing a computation are active and require a private CPU. May be viable Example 6 / 24 Entropy: a Consolidation Manager for Clusters
  • 7. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Global Design of Entropy Monitor Extract the current configuration : The position of each VMs and its CPU consumption An indication of which of the VMs are active and inactive 7 / 24 Entropy: a Consolidation Manager for Clusters
  • 8. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Global Design of Entropy Reconfiguration Algorithm VMPP - Compute a viable configuration using a minimum number of nodes VMRP - Plan and reduce the reconfiguration process if necessary 7 / 24 Entropy: a Consolidation Manager for Clusters
  • 9. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Global Design of Entropy Execution Decompose a plan into simple migrations Migrations orders are sent to the concerned VMM 7 / 24 Entropy: a Consolidation Manager for Clusters
  • 10. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 1 Design 2 Packing the Virtual Machines 3 Planning the migrations 4 Minimizing the migrations 5 Evaluation 6 Conclusion 8 / 24 Entropy: a Consolidation Manager for Clusters
  • 11. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Packing the Virtual Machines Definition The Virtual Machines Packing Problem (VMPP) Compute the minimum number of nodes needed for a viable configuration Example (a) viable but non minimal (b) viable and minimal 9 / 24 Entropy: a Consolidation Manager for Clusters
  • 12. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Packing the virtual machines Approach Based on constraint programming, Each condition defining a viable configuration is a constraint. The constraint solver : Computes a viable configuration from the current one Reduces the number of used nodes until the minimum or a timeout. 10 / 24 Entropy: a Consolidation Manager for Clusters
  • 13. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 1 Design 2 Packing the Virtual Machines 3 Planning the migrations 4 Minimizing the migrations 5 Evaluation 6 Conclusion 11 / 24 Entropy: a Consolidation Manager for Clusters
  • 14. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration Migrations have to be ordered Example Current Result 12 / 24 Entropy: a Consolidation Manager for Clusters
  • 15. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration Migrations have to be ordered Example (1) non-viable (2) 12 / 24 Entropy: a Consolidation Manager for Clusters
  • 16. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration Migrations have to be ordered Example (1) Ok (2) Ok 12 / 24 Entropy: a Consolidation Manager for Clusters
  • 17. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration Inter-dependant migrations require a pivot Example Current Result 13 / 24 Entropy: a Consolidation Manager for Clusters
  • 18. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration Inter-dependant migrations require a pivot Example Current non-viable 13 / 24 Entropy: a Consolidation Manager for Clusters
  • 19. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration Inter-dependant migrations require a pivot Example (1) (2) (3) 13 / 24 Entropy: a Consolidation Manager for Clusters
  • 20. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Planning a reconfiguration The Reconfiguration Plan Describes a viable reconfiguration process Migrations feasible in parallel are grouped into a step Steps are executed sequentially 14 / 24 Entropy: a Consolidation Manager for Clusters
  • 21. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 1 Design 2 Packing the Virtual Machines 3 Planning the migrations 4 Minimizing the migrations 5 Evaluation 6 Conclusion 15 / 24 Entropy: a Consolidation Manager for Clusters
  • 22. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Reducing the reconfiguration process VMRP - Looking for an equivalent configuration Which is a solution of the VMPP Where its associated plan has a minimal ”cost” Method The cost of a plan is estimated using a migration cost model The VMRP computes equivalent configurations with ”cheap” reconfiguration plans until the minimum or a timeout. 16 / 24 Entropy: a Consolidation Manager for Clusters
  • 23. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Reducing the reconfiguration process Example (1) 17 / 24 Entropy: a Consolidation Manager for Clusters
  • 24. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Reducing the reconfiguration process Example (1) (2) (3) cost = 9 17 / 24 Entropy: a Consolidation Manager for Clusters
  • 25. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Reducing the reconfiguration process Example (1) (2) (3) cost = 9 (1) (2) cost = 4 17 / 24 Entropy: a Consolidation Manager for Clusters
  • 26. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 1 Design 2 Packing the Virtual Machines 3 Planning the migrations 4 Minimizing the migrations 5 Evaluation 6 Conclusion 18 / 24 Entropy: a Consolidation Manager for Clusters
  • 27. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Comparison against ”First Fit Decrease” Timeouts to have a non-trivial solution with Entropy estimated using random configurations : 30 secs. for the packing 35 secs. for minimizing the migrations The packing is equivalent or better. Small benefits for 42% of the configurations Cost of the resulting plan reduced by at least 90% Cost 19 / 24 Entropy: a Consolidation Manager for Clusters
  • 28. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Experiments on a cluster Environment 1 node hosting the consolidation manager 3 nodes for serving the VMs virtual disks 35 nodes running a hypervisor 35 VMs executing a collection of NASGrid Benchmarks Method All the benchmarks are launched at the same time Comparison between Static allocation without consolidation Dynamic consolidation using FFD Dynamic consolidation using Entropy 20 / 24 Entropy: a Consolidation Manager for Clusters
  • 29. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Experiments on a cluster Benefits Better reactivity Stable packing Reduced overhead Comparing the reconfigurations against FFD Cost : -90% Duration : -74% Nb of reconfigurations : x2 21 / 24 Entropy: a Consolidation Manager for Clusters
  • 30. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Experiments on a cluster Benefits Better reactivity Stable packing Reduced overhead Impact on the packing Smaller plans imply fewer pivots 21 / 24 Entropy: a Consolidation Manager for Clusters
  • 31. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Experiments on a cluster Benefits Better reactivity Stable packing Reduced overhead Impact on performance Overhead reduced by 9% Node per hour consumption reduced by 25% 21 / 24 Entropy: a Consolidation Manager for Clusters
  • 32. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion 1 Design 2 Packing the Virtual Machines 3 Planning the migrations 4 Minimizing the migrations 5 Evaluation 6 Conclusion 22 / 24 Entropy: a Consolidation Manager for Clusters
  • 33. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Conclusion The interest of the dynamic consolidation is limited by the duration of the reconfiguration process. Entropy Reducing the cost of a plan is an efficient solution to reduce its duration 1 minute to compute a solution reduces the reconfiguration process by up to 8 minutes. Reduces the nodes per hour consumption by 25% as compared to FFD and the overhead by 9%. 23 / 24 Entropy: a Consolidation Manager for Clusters
  • 34. Design Packing the Virtual Machines Planning the migrations Minimizing the migrations Evaluation Conclusion Questions ? http ://entropy.gforge.inria.fr Binary and sources available on LGPL Uses the Xen Hypervisor and the ganglia monitoring system 24 / 24 Entropy: a Consolidation Manager for Clusters