6.21.3.1.2.5. Create and list networks with kill of one of MySQL servers

This report is generated on results collected by execution of the following Rally scenario:

---
{% set repeat = repeat|default(3) %}
  NeutronNetworks.create_and_list_networks:
{% for iteration in range(repeat) %}
    -
      args:
        network_create_args: {}
      runner:
        type: "constant_for_duration"
        duration: 60
        concurrency: 4
      context:
        users:
          tenants: 1
          users_per_tenant: 1
        quotas:
          neutron:
            network: -1
      hooks:
        -
          name: fault_injection
          args:
            action: kill mysql service on one node
          trigger:
            name: event
            args:
              unit: iteration
              at: [100]
{% endfor %}

6.21.3.1.2.5.1. Summary

In this scenario we kill one of MySQL servers while working with Neutron API. In Fuel architecture MySQL is deployed with Galera in active-active mode, thus no dramatic impact should occur.

Service downtime, s	MTTR, s	Absolute performance degradation, s	Relative performance degradation, ratio
N/A	7.73 ±0.72	1.4 ±1.1	3.8 ±2.3

Metrics:

• Service downtime is the time interval between the first and the last errors.

• MTTR is the mean time to recover service performance after the fault.

• Absolute performance degradation is an absolute difference between the mean of operation duration during recovery period and the baseline’s.

• Relative performance degradation is the ratio between the mean of operation duration during recovery period and the baseline’s.

6.21.3.1.2.5.2. Details

This section contains individual data for particular scenario runs.

6.21.3.1.2.5.2.1. Run #1

6.21.3.1.2.5.2.1.1. Baseline

Baseline samples are collected before the start of fault injection. They are used to estimate service performance degradation after the fault.

Samples	Median, s	Mean, s	Std dev	95% percentile, s
86	0.48	0.8	0.49	1.6

6.21.3.1.2.5.2.2. Run #2

6.21.3.1.2.5.2.2.1. Baseline

Baseline samples are collected before the start of fault injection. They are used to estimate service performance degradation after the fault.

Samples	Median, s	Mean, s	Std dev	95% percentile, s
85	0.46	0.5	0.12	0.7

6.21.3.1.2.5.2.2.2. Service performance degradation

The tested service has measurable performance degradation during the following time period(s).

#	Time to recover, s	Absolute degradation, s	Relative degradation
1	6.824 ±0.093	1.5 ±1.2	4.1 ±2.5

6.21.3.1.2.5.2.3. Run #3

6.21.3.1.2.5.2.3.1. Baseline

Baseline samples are collected before the start of fault injection. They are used to estimate service performance degradation after the fault.

Samples	Median, s	Mean, s	Std dev	95% percentile, s
85	0.45	0.47	0.065	0.61

6.21.3.1.2.5.2.3.2. Service performance degradation

The tested service has measurable performance degradation during the following time period(s).

#	Time to recover, s	Absolute degradation, s	Relative degradation
1	8.63 ±0.12	1.18 ±1.00	3.5 ±2.1