Differentiated Services == Differentiated Scheduling Gary Kotton - VMware Gilad Zlotkin - Radware The role of the Nova scheduler in managing Quality of.

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Presentation transcript:

Differentiated Services == Differentiated Scheduling Gary Kotton - VMware Gilad Zlotkin - Radware The role of the Nova scheduler in managing Quality of Service 1

Enterprise Ready Openstack Migrating existing mission critical and performance critical enterprise applications requires: High service levels Availability Performance Security Compliance with existing architectures Multi-tier Fault tolerance models 2

Service Level for Applications Availability Fault levelRecovery Time Fault Tolerance (FT) Compute/Network/Storage element(s)0 High Availability (HA) Compute/Network/Storage element(s)SECs/MINs Disaster Recovery (DR) The whole site/connectivityHOURs/DAYs 3

Service Level for Applications Availability Performance o Transaction Latency (Sec) o Transaction Load/Bandwidth (TPS) Fault levelRecovery Time Fault Tolerance (FT) Compute/Network/Storage element(s)0 High Availability (HA) Compute/Network/Storage element(s)SECs/MINs Disaster Recovery (DR) The whole site/connectivityHOURs/DAYs 3

Service Level for Applications Availability Performance o Transaction Latency (Sec) o Transaction Load/Bandwidth (TPS) Security o Data Privacy o Data Integrity o Denial of Service Fault levelRecovery Time Fault Tolerance (FT) Compute/Network/Storage element(s)0 High Availability (HA) Compute/Network/Storage element(s)SECs/MINs Disaster Recovery (DR) The whole site/connectivityHOURs/DAYs 3

Service Level for Applications Availability Performance o Transaction Latency (Sec) o Transaction Load/Bandwidth (TPS) Security o Data Privacy o Data Integrity o Denial of Service Fault levelRecovery Time Fault Tolerance (FT) Compute/Network/Storage element(s)0 High Availability (HA) Compute/Network/Storage element(s)SECs/MINs Disaster Recovery (DR) The whole site/connectivityHOURs/DAYs What all this has to do with the Nova Scheduler? 3

High Availability Models Availability Zone Redundancy The cloud way Server Redundancy The classic way Both Server and Zone Redundancies The enterprise disaster recovery way 4

Availability Zone Redundancy WS3 DB2 LB2 WS4 Global Load Balancing AZ1AZ2 WS1 DB1 LB1 WS2 5

Server Redundancy WS1 DB1 LB1 WS2 WS3 LB2 DB2 6

Server and Zone Redundancies WS1 DB1 LB1 WS2 WS3 LB2 DB2 WS4 DB3 LB3 WS5 WS6 LB4 DB4 Global Load Balancing AZ1AZ2 7

Network Availability Controller Cluster Transport Network Logical Network LB1LB2 WS1WS3WS2 DB1DB2 VMwares NSX for example 8

Load Balancer Availability Radwares Alteon Load Balancer for example WS1 LB1 WS2 WS3 LB2 Active Standby Persistency State Synchronization Configuration Synchronization Auto Failover 9

Group Scheduling Group together VMs to provide a certain service Enables scheduling policies per group/sub-group Provides a multi-VM application designed for fault tolerance and high performance 10

Example 11

Example Bad placement: if a host goes down entire service is down! 11

Example Bad placement: if a host goes down entire service is down! Placement strategy - anti affinity: achieving fault tolerance 11

Placement Strategies Availability - anti affinity o VM's should be placed in different 'failure domains' (e.g., on different hosts) to ensure application fault tolerance 12

Placement Strategies Availability - anti affinity o VM's should be placed in different 'failure domains' (e.g., on different hosts) to ensure application fault tolerance Performance o Network proximity Group members should be placed as closely as possible to one another on the network (same 'connectivity domain') to ensure low latency and high performance 12

Placement Strategies Availability - anti affinity o VM's should be placed in different 'failure domains' (e.g., on different hosts) to ensure application fault tolerance Performance o Network proximity Group members should be placed as closely as possible to one another on the network (same 'connectivity domain') to ensure low latency and high performance o Host Capability IO-Intensive, Network-Intensive, CPU-Intensive,... 12

Placement Strategies Availability - anti affinity o VM's should be placed in different 'failure domains' (e.g., on different hosts) to ensure application fault tolerance Performance o Network proximity Group members should be placed as closely as possible to one another on the network (same 'connectivity domain') to ensure low latency and high performance o Host Capability IO-Intensive, Network-Intensive, CPU-Intensive,... o Storage Proximity 12

Placement Strategies Availability - anti affinity o VM's should be placed in different 'failure domains' (e.g., on different hosts) to ensure application fault tolerance Performance o Network proximity Group members should be placed as closely as possible to one another on the network (same 'connectivity domain') to ensure low latency and high performance o Host Capability IO-Intensive, Network-Intensive, CPU-Intensive,... o Storage Proximity Security - Resource Isolation/Exclusivity o Host, Network,... 12

Anti Affinity Havana: Anti affinity per group o nova boot --hint group=WS[:anti-affinity] --image ws.img --flavor 2 --num 3 WSi Instance Groups o Properties: Policies - for example anti affinity Members - the instances that are assigned to the group Metadata - key value pairs o Sadly did not make the Havana Release o Continue work in Icehouse with extended functionality 13

Network Proximity (Same Rack) 14

Host Capabilities - IO intensive - CPU intensive - Network intensive Smart resource placement - Yathi Udupi and Debo Dutta (Cisco) Host Capabilities - Don Dugger (Intel) 15

Storage Proximity Schedule instances to have affinity to Cinder volumes Scheduling Across Services - Boris Pavlovic (Mirantis) and Alex Glikson (IBM) Smart resource placement - Yathi Udupi and Debo Dutta (Cisco) 16

Resource Exclusivity Network Isolation: Neutron, for example VMwares NSX Host Allocation: enable user to have a pool of hosts for exclusive use. Private Clouds - Whole Host Allocation - Phil Day (HP), Andrew Laski (Rackspace) 17

Additional Scheduling Topics Scheduler Performance - Boris Pavlovic (Mirantis) Methods to Improve DB Host Statistics - Shane Wang and Lianhau Lu (Intel) Scheduler Metrics - Relationship with Ceilometer - Paul Murray (HP) Multiple Scheduler Policies - Alex Glikson (IBM) 18

Icehouse Expand on Instance Group support Topology of resources and relationships between them o Debo Dutta and Yathi Udupi (Cisco) o Mike Spreitzer (IBM) o Gary Kotton (VMware) 19

API - Aiming for I1 Proposed API (Nova Extension) o id - a unique UUID o name - human readable name o tenant_id - the ID of the tenant that owns the group o policies - a list of policies for the group (anti affinity, network proximity and host capabilities) o metadata - a way to store arbitrary key value pairs on a group o members - UUIDs of all of the instances that are members of the group 20

Flow Group will be created with no members o Group will have a policy Group ID will be used for scheduling o Passed as a hint o Scheduler will update members Pending support for group of groups Group membership will be removed when instance is deleted 21

Summary Migrating existing mission critical and performance critical enterprise applications requires: High service levels Group Scheduling Policies Availability Anti-Affinity Performance Proximity / Host Capability Security Resource Exclusivity 22

Q&A Thank You Gary Kotton: Gilad Zlotkin: