Difference between revisions of "KeystonePerformance"
m |
|||
| Line 11: | Line 11: | ||
# Install Keystone Manually (from RDO release) on both of the above created instances | # Install Keystone Manually (from RDO release) on both of the above created instances | ||
# Using python multiprocessing module create users in parallel using keystoneclient.v2_0 module on each one of them. | # Using python multiprocessing module create users in parallel using keystoneclient.v2_0 module on each one of them. | ||
| − | ## key.users.create(<user>, "test", "test@test.com") | + | ## key.users.create(<user>, "test", "test@test.com") where ''key = client.Client( .... )'' |
# Collect the CPU, Disk, Memory and Database related stats while user creation is in progress. | # Collect the CPU, Disk, Memory and Database related stats while user creation is in progress. | ||
Revision as of 07:57, 16 December 2013
Contents
- 1 Keystone Performance
Keystone Performance
This is to track the performance work related to Keystone.
Work Items
Identify CPU, Disk, Memory, Database bottlenecks
Test #1, Create users in parallel and look for CPU, disk or memory bottleneck.
Methodology
- Install RDO Havana Stable [1] on a bare metal.
- Create one instance of m1.medium flavor and other of type m1.large, so that we can have different CPU and memory config
- Install Keystone Manually (from RDO release) on both of the above created instances
- Using python multiprocessing module create users in parallel using keystoneclient.v2_0 module on each one of them.
- key.users.create(<user>, "test", "test@test.com") where key = client.Client( .... )
- Collect the CPU, Disk, Memory and Database related stats while user creation is in progress.
